Publications

2024

1. 

   Boundary-Aware Uncertainty for Feature Attribution Explainers

   Davin Hill, Aria Masoomi, Max Torop, Sandesh Ghimire, and Jennifer Dy

   In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, 02–04 may 2024

   Abs PDF

   Post-hoc explanation methods have become a critical tool for understanding black-box classifiers in high-stakes applications. However, high-performing classifiers are often highly nonlinear and can exhibit complex behavior around the decision boundary, leading to brittle or misleading local explanations. Therefore there is an impending need to quantify the uncertainty of such explanation methods in order to understand when explanations are trustworthy. In this work we propose the Gaussian Process Explanation unCertainty (GPEC) framework, which generates a unified uncertainty estimate combining decision boundary-aware uncertainty with explanation function approximation uncertainty. We introduce a novel geodesic-based kernel, which captures the complexity of the target black-box decision boundary. We show theoretically that the proposed kernel similarity increases with decision boundary complexity. The proposed framework is highly flexible; it can be used with any black-box classifier and feature attribution method. Empirical results on multiple tabular and image datasets show that the GPEC uncertainty estimate improves understanding of explanations as compared to existing methods.

2. 

   Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions

   Zulqarnain Q Khan, Davin Hill, Aria Masoomi, Joshua T Bone, and Jennifer Dy

   In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, 02–04 may 2024

   Abs PDF

   Machine learning methods have significantly improved in their predictive capabilities, but at the same time they are becoming more complex and less transparent. As a result, explainers are often relied on to provide interpretability to these black-box prediction models. As crucial diagnostics tools, it is important that these explainers themselves are robust. In this paper we focus on one particular aspect of robustness, namely that an explainer should give similar explanations for similar data inputs. We formalize this notion by introducing and defining explainer astuteness, analogous to astuteness of prediction functions. Our formalism allows us to connect explainer robustness to the predictor’s probabilistic Lipschitzness, which captures the probability of local smoothness of a function. We provide lower bound guarantees on the astuteness of a variety of explainers (e.g., SHAP, RISE, CXPlain) given the Lipschitzness of the prediction function. These theoretical results imply that locally smooth prediction functions lend themselves to locally robust explanations. We evaluate these results empirically on simulated as well as real datasets.

2023

1. 

   SmoothHess: ReLU Network Feature Interactions via Stein’s Lemma

   Max Torop, Aria Masoomi, Davin Hill, Kivanç Köse, Stratis Ioannidis, and Jennifer G. Dy

   In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 02–04 may 2023

2. 

   DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning

   Zifeng Wang, Zheng Zhan, Yifan Gong, Yucai Shao, Stratis Ioannidis, Yanzhi Wang, and Jennifer G. Dy

   In International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 02–04 may 2023
3. Graph transfer learning

   Andrey Gritsenko, Kimia Shayestehfard, Yuan Guo, Armin Moharrer, Jennifer G. Dy, and Stratis Ioannidis

   Knowl. Inf. Syst., 02–04 may 2023
4. Transforming Complex Problems Into K-Means Solutions

   Hongfu Liu, Junxiang Chen, Jennifer G. Dy, and Yun Fu

   IEEE Trans. Pattern Anal. Mach. Intell., 02–04 may 2023
5. QueryForm: A Simple Zero-shot Form Entity Query Framework

   Zifeng Wang, Zizhao Zhang, Jacob Devlin, Chen-Yu Lee, Guolong Su, Hao Zhang, Jennifer G. Dy, Vincent Perot, and Tomas Pfister

   In Findings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada, July 9-14, 2023, 02–04 may 2023
6. International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain

   02–04 may 2023
7. High-precision regressors for particle physics

   Fady Bishara, Ayan Paul, and Jennifer G. Dy

   CoRR, 02–04 may 2023
8. Divide and Compose with Score Based Generative Models

   Sandesh Ghimire, Armand Comas Massague, Davin Hill, Aria Masoomi, Octavia I. Camps, and Jennifer G. Dy

   CoRR, 02–04 may 2023
9. Geometry of Score Based Generative Models

   Sandesh Ghimire, Jinyang Liu, Armand Comas Massague, Davin Hill, Aria Masoomi, Octavia I. Camps, and Jennifer G. Dy

   CoRR, 02–04 may 2023
10. Explanations of Black-Box Models based on Directional Feature Interactions

    Aria Masoomi, Davin Hill, Zhonghui Xu, Craig P. Hersh, Edwin K. Silverman, Peter J. Castaldi, Stratis Ioannidis, and Jennifer G. Dy

    CoRR, 02–04 may 2023
11. DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning

    Zifeng Wang, Zheng Zhan, Yifan Gong, Yucai Shao, Stratis Ioannidis, Yanzhi Wang, and Jennifer G. Dy

    CoRR, 02–04 may 2023
12. Multiverse at the Edge: Interacting Real World and Digital Twins for Wireless Beamforming

    Batool Salehi, Utku Demir, Debashri Roy, Suyash Pradhan, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

    CoRR, 02–04 may 2023

2022

1. A Computational Neural Model for Mapping Degenerate Neural Architectures

   Zulqarnain Khan, Yiyu Wang, Eli Sennesh, Jennifer G. Dy, Sarah Ostadabbas, Jan-Willem Meent, J. Benjamin Hutchinson, and Ajay B. Satpute

   Neuroinformatics, 02–04 may 2022
2. Deep Bayesian Unsupervised Lifelong Learning

   Tingting Zhao, Zifeng Wang, Aria Masoomi, and Jennifer G. Dy

   Neural Networks, 02–04 may 2022
3. Sample complexity of rank regression using pairwise comparisons

   Berkan Kadioglu, Peng Tian, Jennifer G. Dy, Deniz Erdogmus, and Stratis Ioannidis

   Pattern Recognit., 02–04 may 2022
4. Spectral Ranking Regression

   Ilkay Yildiz, Jennifer G. Dy, Deniz Erdogmus, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

   ACM Trans. Knowl. Discov. Data, 02–04 may 2022
5. Radio Frequency Fingerprinting on the Edge

   Tong Jian, Yifan Gong, Zheng Zhan, Runbin Shi, Nasim Soltani, Zifeng Wang, Jennifer G. Dy, Kaushik R. Chowdhury, Yanzhi Wang, and Stratis Ioannidis

   IEEE Trans. Mob. Comput., 02–04 may 2022
6. Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Network

   Batool Salehi, Guillem Reus Muns, Debashri Roy, Zifeng Wang, Tong Jian, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

   IEEE Trans. Veh. Technol., 02–04 may 2022

7. 

   Deep Layer-wise Networks Have Closed-Form Weights

   Chieh Tzu Wu, Aria Masoomi, Arthur Gretton, and Jennifer G. Dy

   In International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 28-30 March 2022, Virtual Event, 02–04 may 2022

8. 

   Learning to Prompt for Continual Learning

   Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, and Tomas Pfister

   In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, 02–04 may 2022
9. DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning

   Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, and 1 more author

   In Computer Vision - ECCV 2022 - 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXVI, 02–04 may 2022
10. Pruning Adversarially Robust Neural Networks without Adversarial Examples

    Tong Jian, Zifeng Wang, Yanzhi Wang, Jennifer G. Dy, and Stratis Ioannidis

    In IEEE International Conference on Data Mining, ICDM 2022, Orlando, FL, USA, November 28 - Dec. 1, 2022, 02–04 may 2022

11. 

    Explanations of Black-Box Models based on Directional Feature Interactions

    Aria Masoomi, Davin Hill, Zhonghui Xu, Craig P. Hersh, Edwin K. Silverman, Peter J. Castaldi, Stratis Ioannidis, and Jennifer G. Dy

    In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 02–04 may 2022
12. SparCL: Sparse Continual Learning on the Edge

    Zifeng Wang, Zheng Zhan, Yifan Gong, Geng Yuan, Wei Niu, Tong Jian, Bin Ren, Stratis Ioannidis, Yanzhi Wang, and Jennifer G. Dy

    In NeurIPS, 02–04 may 2022

13. 

    Explainable deep learning for insights in El Nino and river flows

    Yumin Liu, Kate Duffy, Jennifer G. Dy, and Auroop R. Ganguly

    CoRR, 02–04 may 2022
14. Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Network

    Batool Salehi, Guillem Reus Muns, Debashri Roy, Zifeng Wang, Tong Jian, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

    CoRR, 02–04 may 2022
15. Deep Layer-wise Networks Have Closed-Form Weights

    Chieh Wu, Aria Masoomi, Arthur Gretton, and Jennifer G. Dy

    CoRR, 02–04 may 2022
16. DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning

    Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, and 1 more author

    CoRR, 02–04 may 2022
17. Analyzing the Effects of Classifier Lipschitzness on Explainers

    Zulqarnain Khan, Aria Masoomi, Davin Hill, and Jennifer G. Dy

    CoRR, 02–04 may 2022
18. SparCL: Sparse Continual Learning on the Edge

    Zifeng Wang, Zheng Zhan, Yifan Gong, Geng Yuan, Wei Niu, Tong Jian, Bin Ren, Stratis Ioannidis, Yanzhi Wang, and Jennifer G. Dy

    CoRR, 02–04 may 2022
19. Explanation Uncertainty with Decision Boundary Awareness

    Davin Hill, Aria Masoomi, Sandesh Ghimire, Max Torop, and Jennifer G. Dy

    CoRR, 02–04 may 2022
20. Pruning Adversarially Robust Neural Networks without Adversarial Examples

    Tong Jian, Zifeng Wang, Yanzhi Wang, Jennifer G. Dy, and Stratis Ioannidis

    CoRR, 02–04 may 2022
21. QueryForm: A Simple Zero-shot Form Entity Query Framework

    Zifeng Wang, Zizhao Zhang, Jacob Devlin, Chen-Yu Lee, Guolong Su, Hao Zhang, Jennifer G. Dy, Vincent Perot, and Tomas Pfister

    CoRR, 02–04 may 2022
22. SAIF: Sparse Adversarial and Interpretable Attack Framework

    Tooba Imtiaz, Morgan Kohler, Jared Miller, Zifeng Wang, Mario Sznaier, Octavia I. Camps, and Jennifer G. Dy

    CoRR, 02–04 may 2022

2021

1. 

   Segmentation of cellular patterns in confocal images of melanocytic lesions in vivo via a multiscale encoder-decoder network (MED-Net)

   Kivanç Köse, Alican Bozkurt, Christi Alessi-Fox, Melissa Gill, Caterina Longo, Giovanni Pellacani, Jennifer G. Dy, Dana H. Brooks, and Milind Rajadhyaksha

   Medical Image Anal., 02–04 may 2021
2. Improved prediction of smoking status via isoform-aware RNA-seq deep learning models

   Zifeng Wang, Aria Masoomi, Zhonghui Xu, Adel Boueiz, Sool Lee, Tingting Zhao, Russell Bowler, Michael H. Cho, Edwin K. Silverman, Craig P. Hersh, and 2 more authors

   PLoS Comput. Biol., 02–04 may 2021
3. Predicting and Monitoring Upper-Limb Rehabilitation Outcomes Using Clinical and Wearable Sensor Data in Brain Injury Survivors

   Sunghoon Ivan Lee, Catherine P. Adans-Dester, Anne T. O’Brien, Gloria P. Vergara-Diaz, Randie Black-Schaffer, Ross Zafonte, Jennifer G. Dy, and Paolo Bonato

   IEEE Trans. Biomed. Eng., 02–04 may 2021
4. Deep Spectral Ranking

   Ilkay Yildiz, Jennifer G. Dy, Deniz Erdogmus, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

   In The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 02–04 may 2021
5. Rate-Regularization and Generalization in Variational Autoencoders

   Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana H. Brooks, Jennifer G. Dy, and Jan-Willem Meent

   In The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 02–04 may 2021
6. Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling

   Setareh Ariafar, Zelda Mariet, Dana H. Brooks, Jennifer G. Dy, and Jasper Snoek

   In The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, 02–04 may 2021
7. Graph Transfer Learning

   Andrey Gritsenko, Yuan Guo, Kimia Shayestehfard, Armin Moharrer, Jennifer G. Dy, and Stratis Ioannidis

   In IEEE International Conference on Data Mining, ICDM 2021, Auckland, New Zealand, December 7-10, 2021, 02–04 may 2021
8. Structural Visual Guidance Attention Networks In Retinopathy Of Prematurity

   Veysi Yildiz, Stratis Ioannidis, Ilkay Yildiz, Peng Tian, John Peter Campbell, Susan Ostmo, Jayashree Kalpathy-Cramer, Michael F. Chiang, Deniz Erdogmus, and Jennifer G. Dy

   In 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021, Nice, France, April 13-16, 2021, 02–04 may 2021
9. Deep Learning on Visual and Location Data for V2I mmWave Beamforming

   Guillem Reus Muns, Batool Salehi, Debashri Roy, Tong Jian, Zifeng Wang, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

   In 17th International Conference on Mobility, Sensing and Networking, MSN 2021, Exeter, United Kingdom, December 13-15, 2021, 02–04 may 2021
10. Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness

    Zifeng Wang, Tong Jian, Aria Masoomi, Stratis Ioannidis, and Jennifer G. Dy

    In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 02–04 may 2021

11. 

    Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space

    Sandesh Ghimire, Aria Masoomi, and Jennifer G. Dy

    In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 02–04 may 2021
12. Automated ROP Diagnostic System based on Comparisons and U-Net Segmentation

    Peng Tian, Jennifer G. Dy, Deniz Erdogmus, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

    In PETRA ’21: The 14th PErvasive Technologies Related to Assistive Environments Conference, Virtual Event, Greece, 29 June - 2 July, 2021, 02–04 may 2021
13. Structurally Guided Channel Attention Networks: SGCA-Net

    Veysi Yildiz, Jennifer G. Dy, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, Stratis Ioannidis, and Deniz Erdogmus

    In PETRA ’21: The 14th PErvasive Technologies Related to Assistive Environments Conference, Virtual Event, Greece, 29 June - 2 July, 2021, 02–04 may 2021
14. Machine Learning on Camera Images for Fast mmWave Beamforming

    Batool Salehi, Mauro Belgiovine, Sara Garcia Sanchez, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

    CoRR, 02–04 may 2021
15. On the Sample Complexity of Rank Regression from Pairwise Comparisons

    Berkan Kadioglu, Peng Tian, Jennifer G. Dy, Deniz Erdogmus, and Stratis Ioannidis

    CoRR, 02–04 may 2021
16. Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness

    Zifeng Wang, Tong Jian, Aria Masoomi, Stratis Ioannidis, and Jennifer G. Dy

    CoRR, 02–04 may 2021
17. Deep Bayesian Unsupervised Lifelong Learning

    Tingting Zhao, Zifeng Wang, Aria Masoomi, and Jennifer G. Dy

    CoRR, 02–04 may 2021
18. Reliable Estimation of KL Divergence using a Discriminator in Reproducing Kernel Hilbert Space

    Sandesh Ghimire, Aria Masoomi, and Jennifer G. Dy

    CoRR, 02–04 may 2021
19. Unsupervised Approaches for Out-Of-Distribution Dermoscopic Lesion Detection

    Max Torop, Sandesh Ghimire, WenQian Liu, Dana H. Brooks, Octavia I. Camps, Milind Rajadhyaksha, Jennifer G. Dy, and Kivanç Köse

    CoRR, 02–04 may 2021
20. Learning to Prompt for Continual Learning

    Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, and Tomas Pfister

    CoRR, 02–04 may 2021

2020

1. More Is Better: Data Augmentation for Channel-Resilient RF Fingerprinting

   Nasim Soltani, Kunal Sankhe, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

   IEEE Commun. Mag., 02–04 may 2020
2. Deep Learning for RF Fingerprinting: A Massive Experimental Study

   Tong Jian, Bruno Costa Rendon, Emmanuel Ojuba, Nasim Soltani, Zifeng Wang, Kunal Sankhe, Andrey Gritsenko, Jennifer G. Dy, Kaushik R. Chowdhury, and Stratis Ioannidis

   IEEE Internet Things Mag., 02–04 may 2020
3. Enabling precision rehabilitation interventions using wearable sensors and machine learning to track motor recovery

   Catherine P. Adans-Dester, Nicolas Hankov, Anne T. O’Brien, Gloria Vergara-Diaz, Randie Black-Schaffer, Ross Zafonte, Jennifer G. Dy, Sunghoon Ivan Lee, and Paolo Bonato

   npj Digit. Medicine, 02–04 may 2020
4. RF Fingerprinting Unmanned Aerial Vehicles With Non-Standard Transmitter Waveforms

   Nasim Soltani, Guillem Reus Muns, Batool Salehi, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

   IEEE Trans. Veh. Technol., 02–04 may 2020
5. Fast and Accurate Ranking Regression

   Ilkay Yildiz, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

   In The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], 02–04 may 2020
6. A Quantitative Machine Learning Approach to Master Students Admission for Professional Institutions

   Yijun Zhao, Bryan Lackaye, Jennifer G. Dy, and Carla E. Brodley

   In Proceedings of the 13th International Conference on Educational Data Mining, EDM 2020, Fully virtual conference, July 10-13, 2020, 02–04 may 2020

7. 

   Open-World Class Discovery with Kernel Networks

   Zifeng Wang, Batool Salehi, Andrey Gritsenko, Kaushik R. Chowdhury, Stratis Ioannidis, and Jennifer G. Dy

   In 20th IEEE International Conference on Data Mining, ICDM 2020, Sorrento, Italy, November 17-20, 2020, 02–04 may 2020
8. Learn-Prune-Share for Lifelong Learning

   Zifeng Wang, Tong Jian, Kaushik R. Chowdhury, Yanzhi Wang, Jennifer G. Dy, and Stratis Ioannidis

   In 20th IEEE International Conference on Data Mining, ICDM 2020, Sorrento, Italy, November 17-20, 2020, 02–04 may 2020
9. Using Undersampling with Ensemble Learning to Identify Factors Contributing to Preterm Birth

   Shi Dong, Zlatan Feric, Guangyu Li, Chieh Wu, April Z. Gu, Jennifer G. Dy, John Meeker, Ingrid Y. Padilla, José Cordero, Carmen Velez Vega, and 3 more authors

   In 19th IEEE International Conference on Machine Learning and Applications, ICMLA 2020, Miami, FL, USA, December 14-17, 2020, 02–04 may 2020
10. Exposing the Fingerprint: Dissecting the Impact of the Wireless Channel on Radio Fingerprinting

    Amani Al-Shawabka, Francesco Restuccia, Salvatore D’Oro, Tong Jian, Bruno Costa Rendon, Nasim Soltani, Jennifer G. Dy, Stratis Ioannidis, Kaushik R. Chowdhury, and Tommaso Melodia

    In 39th IEEE Conference on Computer Communications, INFOCOM 2020, Toronto, ON, Canada, July 6-9, 2020, 02–04 may 2020
11. Climate Downscaling Using YNet: A Deep Convolutional Network with Skip Connections and Fusion

    Yumin Liu, Auroop R. Ganguly, and Jennifer G. Dy

    In KDD ’20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020, 02–04 may 2020
12. Machine Learning on Camera Images for Fast mmWave Beamforming

    Batool Salehi, Mauro Belgiovine, Sara Garcia Sanchez, Jennifer G. Dy, Stratis Ioannidis, and Kaushik R. Chowdhury

    In 17th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2020, Delhi, India, December 10-13, 2020, 02–04 may 2020

13. 

    Instance-wise Feature Grouping

    Aria Masoomi, Chieh Wu, Tingting Zhao, Zifeng Wang, Peter J. Castaldi, and Jennifer G. Dy

    In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 02–04 may 2020
14. Neural Topographic Factor Analysis for fMRI Data

    Eli Sennesh, Zulqarnain Khan, Yiyu Wang, J. Benjamin Hutchinson, Ajay B. Satpute, Jennifer G. Dy, and Jan-Willem Meent

    In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 02–04 may 2020
15. Deep Kernel Learning for Clustering

    Chieh Wu, Zulqarnain Khan, Stratis Ioannidis, and Jennifer G. Dy

    In Proceedings of the 2020 SIAM International Conference on Data Mining, SDM 2020, Cincinnati, Ohio, USA, May 7-9, 2020, 02–04 may 2020
16. Segmentation of Cellular Patterns in Confocal Images of Melanocytic Lesions in vivo via a Multiscale Encoder-Decoder Network (MED-Net)

    Kivanç Köse, Alican Bozkurt, Christi Alessi-Fox, Melissa Gill, Caterina Longo, Giovanni Pellacani, Jennifer G. Dy, Dana H. Brooks, and Milind Rajadhyaksha

    CoRR, 02–04 may 2020
17. Weighting Is Worth the Wait: Bayesian Optimization with Importance Sampling

    Setareh Ariafar, Zelda Mariet, Ehsan Elhamifar, Dana H. Brooks, Jennifer G. Dy, and Jasper Snoek

    CoRR, 02–04 may 2020
18. Deep Markov Spatio-Temporal Factorization

    Amirreza Farnoosh, Behnaz Rezaei, Eli Zachary Sennesh, Zulqarnain Khan, Jennifer G. Dy, Ajay B. Satpute, J. Benjamin Hutchinson, Jan-Willem Meent, and Sarah Ostadabbas

    CoRR, 02–04 may 2020
19. Layer-wise Learning of Kernel Dependence Networks

    Chieh Wu, Aria Masoomi, Arthur Gretton, and Jennifer G. Dy

    CoRR, 02–04 may 2020
20. Kernel Dependence Network

    Chieh Wu, Aria Masoomi, Arthur Gretton, and Jennifer G. Dy

    CoRR, 02–04 may 2020
21. Learn-Prune-Share for Lifelong Learning

    Zifeng Wang, Tong Jian, Kaushik R. Chowdhury, Yanzhi Wang, Jennifer G. Dy, and Stratis Ioannidis

    CoRR, 02–04 may 2020
22. Open-World Class Discovery with Kernel Networks

    Zifeng Wang, Batool Salehi, Andrey Gritsenko, Kaushik R. Chowdhury, Stratis Ioannidis, and Jennifer G. Dy

    CoRR, 02–04 may 2020

2019

1. ADMMBO: Bayesian Optimization with Unknown Constraints using ADMM

   Setareh Ariafar, Jaume Coll-Font, Dana H. Brooks, and Jennifer G. Dy

   J. Mach. Learn. Res., 02–04 may 2019
2. Classification and comparison via neural networks

   Ilkay Yildiz, Peng Tian, Jennifer G. Dy, Deniz Erdogmus, James M. Brown, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

   Neural Networks, 02–04 may 2019
3. Intelligent Labeling Based on Fisher Information for Medical Image Segmentation Using Deep Learning

   Jamshid Sourati, Ali Gholipour, Jennifer G. Dy, Xavier Tomas-Fernandez, Sila Kurugol, and Simon K. Warfield

   IEEE Trans. Medical Imaging, 02–04 may 2019
4. Variational Inference from Ranked Samples with Features

   Yuan Guo, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

   In Proceedings of The 11th Asian Conference on Machine Learning, ACML 2019, 17-19 November 2019, Nagoya, Japan, 02–04 may 2019
5. Structured Disentangled Representations

   Babak Esmaeili, Hao Wu, Sarthak Jain, Alican Bozkurt, N. Siddharth, Brooks Paige, Dana H. Brooks, Jennifer G. Dy, and Jan-Willem Meent

   In The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, 02–04 may 2019
6. Finding a ’New’ Needle in the Haystack: Unseen Radio Detection in Large Populations Using Deep Learning

   Andrey Gritsenko, Zifeng Wang, Tong Jian, Jennifer G. Dy, Kaushik R. Chowdhury, and Stratis Ioannidis

   In 2019 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2019, Newark, NJ, USA, November 11-14, 2019, 02–04 may 2019
7. MAC ID Spoofing-Resistant Radio Fingerprinting

   Tong Jian, Bruno Costa Rendon, Andrey Gritsenko, Jennifer G. Dy, Kaushik R. Chowdhury, and Stratis Ioannidis

   In 2019 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019, Ottawa, ON, Canada, November 11-14, 2019, 02–04 may 2019
8. A Severity Score for Retinopathy of Prematurity

   Peng Tian, Yuan Guo, Jayashree Kalpathy-Cramer, Susan Ostmo, John Peter Campbell, Michael F. Chiang, Jennifer G. Dy, Deniz Erdogmus, and Stratis Ioannidis

   In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019, 02–04 may 2019
9. Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data - An Application to Climate Prediction

   Yumin Liu, Junxiang Chen, Auroop R. Ganguly, and Jennifer G. Dy

   In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019, 02–04 may 2019
10. Impairment Shift Keying: Covert Signaling by Deep Learning of Controlled Radio Imperfections

    Kunal Sankhe, Kaushik R. Chowdhury, Francesco Restuccia, Salvatore D’Oro, Tong Jian, Zifeng Wang, Amani Al-Shawabka, Jennifer G. Dy, Tommaso Melodia, and Stratis Ioannidis

    In 2019 IEEE Military Communications Conference, MILCOM 2019, Norfolk, VA, USA, November 12-14, 2019, 02–04 may 2019
11. Solving Interpretable Kernel Dimensionality Reduction

    Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, and Jennifer G. Dy

    In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 02–04 may 2019
12. Accelerated Experimental Design for Pairwise Comparisons

    Yuan Guo, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

    In Proceedings of the 2019 SIAM International Conference on Data Mining, SDM 2019, Calgary, Alberta, Canada, May 2-4, 2019, 02–04 may 2019
13. Accelerated Experimental Design for Pairwise Comparisons

    Yuan Guo, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, and Stratis Ioannidis

    CoRR, 02–04 may 2019
14. Adaptive Nonparametric Variational Autoencoder

    Tingting Zhao, Zifeng Wang, Aria Masoomi, and Jennifer G. Dy

    CoRR, 02–04 may 2019
15. Neural Topographic Factor Analysis for fMRI Data

    Eli Sennesh, Zulqarnain Khan, Jennifer G. Dy, Ajay B. Satpute, J. Benjamin Hutchinson, and Jan-Willem Meent

    CoRR, 02–04 may 2019
16. Deep Kernel Learning for Clustering

    Chieh Wu, Zulqarnain Khan, Yale Chang, Stratis Ioannidis, and Jennifer G. Dy

    CoRR, 02–04 may 2019
17. Solving Interpretable Kernel Dimension Reduction

    Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, and Jennifer G. Dy

    CoRR, 02–04 may 2019
18. Iterative Spectral Method for Alternative Clustering

    Chieh Wu, Stratis Ioannidis, Mario Sznaier, Xiangyu Li, David R. Kaeli, and Jennifer G. Dy

    CoRR, 02–04 may 2019
19. Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion

    Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, and Jennifer G. Dy

    CoRR, 02–04 may 2019
20. Evaluating Combinatorial Generalization in Variational Autoencoders

    Alican Bozkurt, Babak Esmaeili, Dana H. Brooks, Jennifer G. Dy, and Jan-Willem Meent

    CoRR, 02–04 may 2019

2018

1. A Probabilistic Active Learning Algorithm Based on Fisher Information Ratio

   Jamshid Sourati, Murat Akçakaya, Deniz Erdogmus, Todd K. Leen, and Jennifer G. Dy

   IEEE Trans. Pattern Anal. Mach. Intell., 02–04 may 2018
2. Iterative Spectral Method for Alternative Clustering

   Chieh Wu, Stratis Ioannidis, Mario Sznaier, Xiangyu Li, David R. Kaeli, and Jennifer G. Dy

   In International Conference on Artificial Intelligence and Statistics, AISTATS 2018, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, Spain, 02–04 may 2018
3. Crowdclustering with Partition Labels

   Junxiang Chen, Yale Chang, Peter J. Castaldi, Michael H. Cho, Brian Hobbs, and Jennifer G. Dy

   In International Conference on Artificial Intelligence and Statistics, AISTATS 2018, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, Spain, 02–04 may 2018
4. Interactive Kernel Dimension Alternative Clustering on GPUs

   Xiangyu Li, Chieh Wu, Shi Dong, Jennifer G. Dy, and David R. Kaeli

   In IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018, Barcelona, Spain, August 28-31, 2018, 02–04 may 2018
5. A Hybrid Approach to Identifying Key Factors in Environmental Health Studies

   Shi Dong, Zlatan Feric, Xiangyu Li, Sheikh Mokhlesur Rahman, Guangyu Li, Chieh Wu, April Z. Gu, Jennifer G. Dy, David R. Kaeli, John Meeker, and 5 more authors

   In IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018, 02–04 may 2018
6. Experimental Design under the Bradley-Terry Model

   Yuan Guo, Peng Tian, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Deniz Erdogmus, Jennifer G. Dy, and Stratis Ioannidis

   In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden, 02–04 may 2018
7. Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning

   Thomas Vandal, Evan Kodra, Jennifer G. Dy, Sangram Ganguly, Ramakrishna R. Nemani, and Auroop R. Ganguly

   In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2018, London, UK, August 19-23, 2018, 02–04 may 2018
8. Active Deep Learning with Fisher Information for Patch-Wise Semantic Segmentation

   Jamshid Sourati, Ali Gholipour, Jennifer G. Dy, Sila Kurugol, and Simon K. Warfield

   In Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support - 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings, 02–04 may 2018
9. A Multiresolution Convolutional Neural Network with Partial Label Training for Annotating Reflectance Confocal Microscopy Images of Skin

   Alican Bozkurt, Kivanç Köse, Christi Alessi-Fox, Melissa Gill, Jennifer G. Dy, Dana H. Brooks, and Milind Rajadhyaksha

   In Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 - 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part II, 02–04 may 2018
10. Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018

    02–04 may 2018
11. A Multiresolution Deep Learning Framework for Automated Annotation of Reflectance Confocal Microscopy Images

    Kivanç Köse, Alican Bozkurt, Christi Alessi-Fox, Melissa Gill, Dana H. Brooks, Jennifer G. Dy, and Milind Rajadhyaksha

    CoRR, 02–04 may 2018
12. Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning

    Thomas Vandal, Evan Kodra, Jennifer G. Dy, Sangram Ganguly, Ramakrishna R. Nemani, and Auroop R. Ganguly

    CoRR, 02–04 may 2018
13. Deep feature transfer between localization and segmentation tasks

    Szu-Yeu Hu, Andrew Beers, Ken Chang, Kathi Höbel, J. Peter Campbell, Deniz Erdogmus, Stratis Ioannidis, Jennifer G. Dy, Michael F. Chiang, Jayashree Kalpathy-Cramer, and 1 more author

    CoRR, 02–04 may 2018
14. Can VAEs Generate Novel Examples?

    Alican Bozkurt, Babak Esmaeili, Dana H. Brooks, Jennifer G. Dy, and Jan-Willem Meent

    CoRR, 02–04 may 2018

2017

1. Asymptotic Analysis of Objectives Based on Fisher Information in Active Learning

   Jamshid Sourati, Murat Akçakaya, Todd K. Leen, Deniz Erdogmus, and Jennifer G. Dy

   J. Mach. Learn. Res., 02–04 may 2017
2. A Robust-Equitable Measure for Feature Ranking and Selection

   A. Adam Ding, Jennifer G. Dy, Yi Li, and Yale Chang

   J. Mach. Learn. Res., 02–04 may 2017
3. Subject-specific abnormal region detection in traumatic brain injury using sparse model selection on high dimensional diffusion data

   Matineh Shaker, Deniz Erdogmus, Jennifer G. Dy, and Sylvain Bouix

   Medical Image Anal., 02–04 may 2017
4. Automated Target Detection for Geophysical Applications

   Uri Pe’er, and Jennifer G. Dy

   IEEE Trans. Geosci. Remote. Sens., 02–04 may 2017
5. A Marked Poisson Process Driven Latent Shape Model for 3D Segmentation of Reflectance Confocal Microscopy Image Stacks of Human Skin

   Sindhu Ghanta, Michael I. Jordan, Kivanç Köse, Dana H. Brooks, Milind Rajadhyaksha, and Jennifer G. Dy

   IEEE Trans. Image Process., 02–04 may 2017
6. A Bayesian Nonparametric Model for Disease Subtyping: Application to Emphysema Phenotypes

   James C. Ross, Peter J. Castaldi, Michael H. Cho, Junxiang Chen, Yale Chang, Jennifer G. Dy, Edwin K. Silverman, George R. Washko, and Raúl San José Estépar

   IEEE Trans. Medical Imaging, 02–04 may 2017
7. Informative Subspace Learning for Counterfactual Inference

   Yale Chang, and Jennifer G. Dy

   In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA, 02–04 may 2017
8. Rate Optimal Estimation for High Dimensional Spatial Covariance Matrices

   Yi Li, Aidong Adam Ding, and Jennifer G. Dy

   In Proceedings of The 9th Asian Conference on Machine Learning, ACML 2017, Seoul, Korea, November 15-17, 2017, 02–04 may 2017
9. Clustering from Multiple Uncertain Experts

   Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, and Jennifer G. Dy

   In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA, 02–04 may 2017
10. Delineation of Skin Strata in Reflectance Confocal Microscopy Images with Recurrent Convolutional Networks

    Alican Bozkurt, Trevor Gale, Kivanç Köse, Christi Alessi-Fox, Dana H. Brooks, Milind Rajadhyaksha, and Jennifer G. Dy

    In 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2017, Honolulu, HI, USA, July 21-26, 2017, 02–04 may 2017
11. Multiple Clustering Views from Multiple Uncertain Experts

    Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, and Jennifer G. Dy

    In Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, 02–04 may 2017
12. Clustering with Domain-Specific Usefulness Scores

    Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, and Jennifer G. Dy

    In Proceedings of the 2017 SIAM International Conference on Data Mining, Houston, Texas, USA, April 27-29, 2017, 02–04 may 2017
13. Delineation of Skin Strata in Reflectance Confocal Microscopy Images using Recurrent Convolutional Networks with Toeplitz Attention

    Alican Bozkurt, Kivanç Köse, Jaume Coll-Font, Christi Alessi-Fox, Dana H. Brooks, Jennifer G. Dy, and Milind Rajadhyaksha

    CoRR, 02–04 may 2017

2016

1. Classification Active Learning Based on Mutual Information

   Jamshid Sourati, Murat Akçakaya, Jennifer G. Dy, Todd K. Leen, and Deniz Erdogmus

   Entropy, 02–04 may 2016
2. Exploring image-based indicators of crime and economic well-being in sub-saharan Africa

   Payden Mcbee, Jennifer G. Dy, and John Irvine

   In 2016 IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2016, Washington, DC, USA, October 18-20, 2016, 02–04 may 2016
3. A Robust-Equitable Copula Dependence Measure for Feature Selection

   Yale Chang, Yi Li, A. Adam Ding, and Jennifer G. Dy

   In Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, AISTATS 2016, Cadiz, Spain, May 9-11, 2016, 02–04 may 2016
4. Assessing subsets of analytes in context of detecting laboratory errors

   Jamshid Sourati, Steven C. Kazmierczak, Murat Akçakaya, Jennifer G. Dy, Todd K. Leen, and Deniz Erdogmus

   In 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, FL, USA, August 16-20, 2016, 02–04 may 2016
5. Interpretable Clustering via Discriminative Rectangle Mixture Model

   Junxiang Chen, Yale Chang, Brian Hobbs, Peter J. Castaldi, Michael H. Cho, Edwin K. Silverman, and Jennifer G. Dy

   In IEEE 16th International Conference on Data Mining, ICDM 2016, December 12-15, 2016, Barcelona, Spain, 02–04 may 2016
6. A Non-parametric Approach to Detect Epileptogenic Lesions using Restricted Boltzmann Machines

   Yijun Zhao, Bilal Ahmed, Thomas Thesen, Karen E. Blackmon, Jennifer G. Dy, Carla E. Brodley, Ruben Kuzniecky, and Orrin Devinsky

   In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 13-17, 2016, 02–04 may 2016
7. Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy

   Bilal Ahmed, Thomas Thesen, Karen E. Blackmon, Ruben Kuzniecky, Orrin Devinsky, Jennifer G. Dy, and Carla E. Brodley

   In Proceedings of the 1st Machine Learning in Health Care, MLHC 2016, Los Angeles, CA, USA, August 19-20, 2016, 02–04 may 2016
8. A Generative Block-Diagonal Model for Clustering

   Junxiang Chen, and Jennifer G. Dy

   In Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, UAI 2016, June 25-29, 2016, New York City, NY, USA, 02–04 may 2016
9. Asymptotic Analysis of Objectives based on Fisher Information in Active Learning

   Jamshid Sourati, Murat Akçakaya, Todd K. Leen, Deniz Erdogmus, and Jennifer G. Dy

   CoRR, 02–04 may 2016
10. Evaluating Crowdsourcing Participants in the Absence of Ground-Truth

    Ramanathan Subramanian, Rómer Rosales, Glenn Fung, and Jennifer G. Dy

    CoRR, 02–04 may 2016
11. Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy

    Bilal Ahmed, Thomas Thesen, Karen E. Blackmon, Ruben Kuzniecky, Orrin Devinsky, Jennifer G. Dy, and Carla E. Brodley

    CoRR, 02–04 may 2016

2015

1. MultiClust special issue on discovering, summarizing and using multiple clusterings

   Emmanuel Müller, Ira Assent, Stephan Günnemann, Thomas Seidl, and Jennifer G. Dy

   Mach. Learn., 02–04 may 2015
2. A Sparse Combined Regression-Classification Formulation for Learning a Physiological Alternative to Clinical Post-Traumatic Stress Disorder Scores

   Sarah Marie Brown, Andrea Webb, Rami Mangoubi, and Jennifer G. Dy

   In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 25-30, 2015, Austin, Texas, USA, 02–04 may 2015
3. Domain Induced Dirichlet Mixture of Gaussian Processes: An Application to Predicting Disease Progression in Multiple Sclerosis Patients

   Yijun Zhao, Tanuja Chitnis, Brian C. Healy, Jennifer G. Dy, and Carla E. Brodley

   In 2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, November 14-17, 2015, 02–04 may 2015
4. Securing virtual execution environments through machine learning-based intrusion detection

   Fatemeh Azmandian, David R. Kaeli, Jennifer G. Dy, and Javed A. Aslam

   In 25th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2015, Boston, MA, USA, September 17-20, 2015, 02–04 may 2015
5. Sparse model learning for high dimensional diffusion MRI data in traumatic brain injury

   Matineh Shaker, Deniz Erdogmus, Jennifer G. Dy, and Sylvain Bouix

   In 25th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2015, Boston, MA, USA, September 17-20, 2015, 02–04 may 2015
6. Clustering and Ranking in Heterogeneous Information Networks via Gamma-Poisson Model

   Junxiang Chen, Wei Dai, Yizhou Sun, and Jennifer G. Dy

   In Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30 - May 2, 2015, 02–04 may 2015

2014

1. Harnessing the Power of GPUs to Speed Up Feature Selection for Outlier Detection

   Fatemeh Azmandian, Ayse Yilmazer, Jennifer G. Dy, Javed A. Aslam, and David R. Kaeli

   J. Comput. Sci. Technol., 02–04 may 2014
2. Learning from multiple annotators with varying expertise

   Yan Yan, Rómer Rosales, Glenn Fung, Subramanian Ramanathan, and Jennifer G. Dy

   Mach. Learn., 02–04 may 2014
3. Iterative Discovery of Multiple AlternativeClustering Views

   Donglin Niu, Jennifer G. Dy, and Michael I. Jordan

   IEEE Trans. Pattern Anal. Mach. Intell., 02–04 may 2014
4. Editorial to the Special Issue of Selected Papers of SDM 2013

   Jennifer G. Dy, and Zhi-Hua Zhou

   Stat. Anal. Data Min., 02–04 may 2014
5. Accelerated Learning-Based Interactive Image Segmentation Using Pairwise Constraints

   Jamshid Sourati, Deniz Erdogmus, Jennifer G. Dy, and Dana H. Brooks

   IEEE Trans. Image Process., 02–04 may 2014
6. Active learning from uncertain crowd annotations

   Yan Yan, Rómer Rosales, Glenn Fung, and Jennifer G. Dy

   In 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014, Allerton Park & Retreat Center, Monticello, IL, USA, September 30 - October 3, 2014, 02–04 may 2014
7. Airway labeling using a Hidden Markov Tree Model

   James C. Ross, Alejandro A. Dı́az, Yuka Okajima, Demian Wassermann, George R. Washko, Jennifer G. Dy, and Raúl San José Estépar

   In IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29 - May 2, 2014, Beijing, Chin, Beijing, China, 02–04 may 2014
8. Dual beta process priors for latent cluster discovery in chronic obstructive pulmonary disease

   James C. Ross, Peter J. Castaldi, Michael H. Cho, and Jennifer G. Dy

   In The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’14, New York, NY, USA - August 24 - 27, 2014, 02–04 may 2014
9. System Call Anomaly Detection Using Multi-HMMs

   Esra N. Yolacan, Jennifer G. Dy, and David R. Kaeli

   In IEEE Eighth International Conference on Software Security and Reliability, SERE 2014, San Francisco, CA, USA, June 30 - July 2, 2014 - Companion Volume, 02–04 may 2014

2013

1. Nonparametric Mixture of Gaussian Processes with Constraints

   James C. Ross, and Jennifer G. Dy

   In Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013, 02–04 may 2013

2012

1. A Computational model for compressed sensing RNAi cellular screening

   Hua Tan, Jing Fan, Jiguang Bao, Jennifer G. Dy, and Xiaobo Zhou

   BMC Bioinform., 02–04 may 2012
2. A quantitative analytic pipeline for evaluating neuronal activities by high-throughput synaptic vesicle imaging

   Jing Fan, Xiaofeng Xia, Ying Li, Jennifer G. Dy, and Stephen T. C. Wong

   NeuroImage, 02–04 may 2012
3. Unsupervised wrinkle detection in reflectance confocal microscopy images of the human skin

   Jamshid Sourati, Dana H. Brooks, Jennifer G. Dy, Esra Ataer Cansizoglu, Deniz Erdogmus, and Milind Rajadhyaksha

   In 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2012, Kyoto, Japan, March 25-30, 2012, 02–04 may 2012
4. Feature Weighting and Selection Using Hypothesis Margin of Boosting

   Malak Alshawabkeh, Javed A. Aslam, Jennifer G. Dy, and David R. Kaeli

   In 12th IEEE International Conference on Data Mining, ICDM 2012, Brussels, Belgium, December 10-13, 2012, 02–04 may 2012
5. GPU-Accelerated Feature Selection for Outlier Detection Using the Local Kernel Density Ratio

   Fatemeh Azmandian, Ayse Yilmazer, Jennifer G. Dy, Javed A. Aslam, and David R. Kaeli

   In 12th IEEE International Conference on Data Mining, ICDM 2012, Brussels, Belgium, December 10-13, 2012, 02–04 may 2012
6. Constrained spectral clustering for image segmentation

   Jamshid Sourati, Dana H. Brooks, Jennifer G. Dy, and Deniz Erdogmus

   In IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012, Santander, Spain, September 23-26, 2012, 02–04 may 2012
7. Local Kernel Density Ratio-Based Feature Selection for Outlier Detection

   Fatemeh Azmandian, Jennifer G. Dy, Javed A. Aslam, and David R. Kaeli

   In Proceedings of the 4th Asian Conference on Machine Learning, ACML 2012, Singapore, Singapore, November 4-6, 2012, 02–04 may 2012
8. A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views

   Donglin Niu, Jennifer G. Dy, and Zoubin Ghahramani

   In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2012, La Palma, Canary Islands, Spain, April 21-23, 2012, 02–04 may 2012
9. Active Learning from Multiple Knowledge Sources

   Yan Yan, Rómer Rosales, Glenn Fung, Faisal Farooq, Bharat Rao, and Jennifer G. Dy

   In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2012, La Palma, Canary Islands, Spain, April 21-23, 2012, 02–04 may 2012
10. Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario

    Yan Yan, Rómer Rosales, Glenn Fung, and Jennifer G. Dy

    CoRR, 02–04 may 2012

2011

1. Virtual machine monitor-based lightweight intrusion detection

   Fatemeh Azmandian, Micha Moffie, Malak Alshawabkeh, Jennifer G. Dy, Javed A. Aslam, and David R. Kaeli

   ACM SIGOPS Oper. Syst. Rev., 02–04 may 2011
2. Quantitative synaptic vesicle imaging for evaluating neuron activities in neurodegenerative diseases

   Jing Fan, Xiaofeng Xia, Jennifer G. Dy, and Stephen T. C. Wong

   In Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers, ACSCC 2011, Pacific Grove, CA, USA, November 6-9, 2011, 02–04 may 2011
3. Longitudinal monitoring of patients with Parkinson’s disease via wearable sensor technology in the home setting

   Shyamal Patel, Bor-rong Chen, Chiara Mancinelli, Sabrina Paganoni, Ludy Shih, Matt Welsh, Jennifer G. Dy, and Paolo Bonato

   In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2011, Boston, MA, USA, August 30 - Sept. 3, 2011, 02–04 may 2011
4. Centerline extraction with principal curve tracing to improve 3D level set esophagus segmentation in CT images

   Sila Kurugol, Erhan Bas, Deniz Erdogmus, Jennifer G. Dy, Gregory C. Sharp, and Dana H. Brooks

   In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2011, Boston, MA, USA, August 30 - Sept. 3, 2011, 02–04 may 2011
5. A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection

   Yue Guan, Jennifer G. Dy, and Michael I. Jordan

   In Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, June 28 - July 2, 2011, 02–04 may 2011
6. Active Learning from Crowds

   Yan Yan, Rómer Rosales, Glenn Fung, and Jennifer G. Dy

   In Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, June 28 - July 2, 2011, 02–04 may 2011
7. Feature Selection Metric Using AUC Margin for Small Samples and Imbalanced Data Classification Problems

   Malak Alshawabkeh, Javed A. Aslam, Jennifer G. Dy, and David R. Kaeli

   In 10th International Conference on Machine Learning and Applications and Workshops, ICMLA 2011, Honolulu, Hawaii, USA, December 18-21, 2011. Volume 1: Main Conference, 02–04 may 2011
8. A Novel Feature Selection for Intrusion Detection in Virtual Machine Environments

   Malak Alshawabkeh, Javed A. Aslam, David R. Kaeli, and Jennifer G. Dy

   In IEEE 23rd International Conference on Tools with Artificial Intelligence, ICTAI 2011, Boca Raton, FL, USA, November 7-9, 2011, 02–04 may 2011
9. Workload Characterization at the Virtualization Layer

   Fatemeh Azmandian, Micha Moffie, Jennifer G. Dy, Javed A. Aslam, and David R. Kaeli

   In MASCOTS 2011, 19th Annual IEEE/ACM International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Singapore, 25-27 July, 2011, 02–04 may 2011
10. Dimensionality Reduction for Spectral Clustering

    Donglin Niu, Jennifer G. Dy, and Michael I. Jordan

    In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2011, Fort Lauderdale, USA, April 11-13, 2011, 02–04 may 2011

2010

1. A Novel Approach to Monitor Rehabilitation Outcomes in Stroke Survivors Using Wearable Technology

   Shyamal Patel, Richard Hughes, Todd Hester, Joel Stein, Metin Akay, Jennifer G. Dy, and Paolo Bonato

   Proc. IEEE, 02–04 may 2010
2. MultiClust 2010: discovering, summarizing and using multiple clusterings

   Xiaoli Z. Fern, Ian Davidson, and Jennifer G. Dy

   SIGKDD Explor., 02–04 may 2010
3. Learning multiple nonredundant clusterings

   Ying Cui, Xiaoli Z. Fern, and Jennifer G. Dy

   ACM Trans. Knowl. Discov. Data, 02–04 may 2010
4. From Transformation-Based Dimensionality Reduction to Feature Selection

   Mahdokht Masaeli, Glenn Fung, and Jennifer G. Dy

   In Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel, 02–04 may 2010
5. Multiple Non-Redundant Spectral Clustering Views

   Donglin Niu, Jennifer G. Dy, and Michael I. Jordan

   In Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel, 02–04 may 2010
6. Effective Virtual Machine Monitor Intrusion Detection Using Feature Selection on Highly Imbalanced Data

   Malak Alshawabkeh, Micha Moffie, Fatemeh Azmandian, Javed A. Aslam, Jennifer G. Dy, and David R. Kaeli

   In The Ninth International Conference on Machine Learning and Applications, ICMLA 2010, Washington, DC, USA, 12-14 December 2010, 02–04 may 2010
7. Locally Deformable Shape Model to Improve 3D Level Set Based Esophagus Segmentation

   Sila Kurugol, Necmiye Ozay, Jennifer G. Dy, Gregory C. Sharp, and Dana H. Brooks

   In 20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, Turkey, 23-26 August 2010, 02–04 may 2010
8. 3D level set esophagus segmentation in thoracic CT images using spatial, appearance and shape models

   Sila Kurugol, Jennifer G. Dy, Gregory C. Sharp, and Dana H. Brooks

   In Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Rotterdam, The Netherlands, 14-17 April, 2010, 02–04 may 2010
9. Medical coding classification by leveraging inter-code relationships

   Yan Yan, Glenn Fung, Jennifer G. Dy, and Rómer Rosales

   In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, July 25-28, 2010, 02–04 may 2010
10. Convex Principal Feature Selection

    Mahdokht Masaeli, Yan Yan, Ying Cui, Glenn Fung, and Jennifer G. Dy

    In Proceedings of the SIAM International Conference on Data Mining, SDM 2010, April 29 - May 1, 2010, Columbus, Ohio, USA, 02–04 may 2010
11. Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario

    Yan Yan, Rómer Rosales, Glenn Fung, and Jennifer G. Dy

    In UAI 2010, Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, July 8-11, 2010, 02–04 may 2010
12. Modeling annotator expertise: Learning when everybody knows a bit of something

    Yan Yan, Rómer Rosales, Glenn Fung, Mark Schmidt, Gerardo Hermosillo Valadez, Luca Bogoni, Linda Moy, and Jennifer G. Dy

    In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2010, Chia Laguna Resort, Sardinia, Italy, May 13-15, 2010, 02–04 may 2010

2009

1. A fuzzy logics clustering approach to computing human attention allocation using eyegaze movement cue

   Yingzi Lin, Wen-Jun Zhang, Chieh Wu, G. Yang, and Jennifer G. Dy

   Int. J. Hum. Comput. Stud., 02–04 may 2009
2. Using Local Dependencies within Batches to Improve Large Margin Classifiers

   Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, and R. Bharat Rao

   J. Mach. Learn. Res., 02–04 may 2009
3. An Automated Pipeline for Dendrite Spine Detection and Tracking of 3D Optical Microscopy Neuron Images of In Vivo Mouse Models

   Jing Fan, Xiaobo Zhou, Jennifer G. Dy, Yong Zhang, and Stephen T. C. Wong

   Neuroinformatics, 02–04 may 2009
4. Monitoring Motor Fluctuations in Patients With Parkinson’s Disease Using Wearable Sensors

   Shyamal Patel, Konrad Lorincz, Richard Hughes, Nancy Huggins, John Growdon, David G. Standaert, Metin Akay, Jennifer G. Dy, Matt Welsh, and Paolo Bonato

   IEEE Trans. Inf. Technol. Biomed., 02–04 may 2009
5. Multi-Class Classifiers and their Underlying Shared Structure

   Volkan Vural, Glenn Fung, Rómer Rosales, and Jennifer G. Dy

   In IJCAI 2009, Proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, USA, July 11-17, 2009, 02–04 may 2009
6. Localizing the Dermis/Epidermis Boundary in Reflectance Confocal Microscopy Images with a Hybrid Classification Algorithm

   Sila Kurugol, Jennifer G. Dy, Milind Rajadhyaksha, and Dana H. Brooks

   In Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28 - July 1, 2009, 02–04 may 2009
7. Sparse Probabilistic Principal Component Analysis

   Yue Guan, and Jennifer G. Dy

   In Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, AISTATS 2009, Clearwater Beach, Florida, USA, April 16-18, 2009, 02–04 may 2009

2008

1. Fast semi-supervised SVM classifiers using \empha priori metric information

   Volkan Vural, Glenn Fung, Jennifer G. Dy, and Bharat Rao

   Optim. Methods Softw., 02–04 may 2008
2. Impact of imputation of missing values on classification error for discrete data

   Alireza Farhangfar, Lukasz A. Kurgan, and Jennifer G. Dy

   Pattern Recognit., 02–04 may 2008
3. Detection of the dermis/epidermis boundary in reflectance confocal images using multi-scale classifier with adaptive texture features

   Sila Kurugol, Jennifer G. Dy, Milind Rajadhyaksha, and Dana H. Brooks

   In Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Paris, France, May 14-17, 2008, 02–04 may 2008
4. Learning methods for lung tumor markerless gating in image-guided radiotherapy

   Ying Cui, Jennifer G. Dy, Gregory C. Sharp, Brian M. Alexander, and Steve B. Jiang

   In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, Nevada, USA, August 24-27, 2008, 02–04 may 2008

2007

1. In search of deterministic methods for initializing K-means and Gaussian mixture clustering

   Ting Su, and Jennifer G. Dy

   Intell. Data Anal., 02–04 may 2007
2. Non-redundant Multi-view Clustering via Orthogonalization

   Ying Cui, Xiaoli Z. Fern, and Jennifer G. Dy

   In Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), October 28-31, 2007, Omaha, Nebraska, USA, 02–04 may 2007

2006

1. Batch Classification with Applications in Computer Aided Diagnosis

   Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, and R. Bharat Rao

   In Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings, 02–04 may 2006

2005

1. Evolving Feature Selection

   Huan Liu, Edward R. Dougherty, Jennifer G. Dy, Kari Torkkola, Eugene Tuv, Hanchuan Peng, Chris H. Q. Ding, Fuhui Long, Michael E. Berens, Lance Parsons, and 3 more authors

   IEEE Intell. Syst., 02–04 may 2005
2. Enabling a RealTime Solution for Neuron Detection with Reconfigurable Hardware (abstract only)

   Ben Cordes, Jennifer G. Dy, Miriam Leeser, and James Goebel

   In Proceedings of the ACM/SIGDA 13th International Symposium on Field Programmable Gate Arrays, FPGA 2005, Monterey, California, USA, February 20-22, 2005, 02–04 may 2005
3. A multinomial clustering model for fast simulation of computer architecture designs

   Kaushal Sanghai, Ting Su, Jennifer G. Dy, and David R. Kaeli

   In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, Illinois, USA, August 21-24, 2005, 02–04 may 2005
4. Enabling a Real-Time Solution for Neuron Detection with Reconfigurable Hardware

   Ben Cordes, Jennifer G. Dy, Miriam Leeser, and James Goebel

   In 16th IEEE International Workshop on Rapid System Prototyping (RSP 2005), 8-10 June 2005, Montreal, Canada, 02–04 may 2005

2004

1. Feature Selection for Unsupervised Learning

   Jennifer G. Dy, and Carla E. Brodley

   J. Mach. Learn. Res., 02–04 may 2004
2. Automated hierarchical mixtures of probabilistic principal component analyzers

   Ting Su, and Jennifer G. Dy

   In Machine Learning, Proceedings of the Twenty-first International Conference (ICML 2004), Banff, Alberta, Canada, July 4-8, 2004, 02–04 may 2004
3. A hierarchical method for multi-class support vector machines

   Volkan Vural, and Jennifer G. Dy

   In Machine Learning, Proceedings of the Twenty-first International Conference (ICML 2004), Banff, Alberta, Canada, July 4-8, 2004, 02–04 may 2004
4. A Deterministic Method for Initializing K-Means Clustering

   Ting Su, and Jennifer G. Dy

   In 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 15-17 November 2004, Boca Raton, FL, USA, 02–04 may 2004

2003

1. Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images

   Jennifer G. Dy, Carla E. Brodley, Avinash C. Kak, Lynn S. Broderick, and Alex M. Aisen

   IEEE Trans. Pattern Anal. Mach. Intell., 02–04 may 2003

2000

1. Feature Subset Selection and Order Identification for Unsupervised Learning

   Jennifer G. Dy, and Carla E. Brodley

   In Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29 - July 2, 2000, 02–04 may 2000
2. Visualization and interactive feature selection for unsupervised data

   Jennifer G. Dy, and Carla E. Brodley

   In Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, Boston, MA, USA, August 20-23, 2000, 02–04 may 2000

1999

1. Content-Based Retrieval from Medical Image Databases: A Synergy of Human Interaction, Machine Learning and Computer Vision

   Carla E. Brodley, Avinash C. Kak, Chi-Ren Shyu, Jennifer G. Dy, Lynn S. Broderick, and Alex M. Aisen

   In Proceedings of the Sixteenth National Conference on Artificial Intelligence and Eleventh Conference on Innovative Applications of Artificial Intelligence, July 18-22, 1999, Orlando, Florida, USA, 02–04 may 1999
2. The Customized-Queries Approach to CBIR Using EM

   Jennifer G. Dy, Carla E. Brodley, Avinash C. Kak, Chi-Ren Shyu, and Lynn S. Broderick

   In 1999 Conference on Computer Vision and Pattern Recognition (CVPR ’99), 23-25 June 1999, Ft. Collins, CO, USA, 02–04 may 1999
3. Customized-queries approach to CBIR

   Jennifer G. Dy, Carla E. Brodley, Avinash C. Kak, Chi-Ren Shyu, and Lynn S. Broderick

   In Storage and Retrieval for Image and Video Databases VII, San Jose, CA, USA, January 26-29, 1999, 02–04 may 1999