Publications

Efficient CDF Approximations for Normalizing Flows

C.S. Sastry, A. Lehrmann, M. Brubaker, and A. Radovic. Transactions on Machine Learning Research (TMLR), 2022

Learning And Generalization

PUMA: Performance Unchanged Model Augmentation for Training Data Removal

G. Wu, M. Hashemi, and C. Srinivasa. Association for the Advancement of Artificial Intelligence (AAAI), 2022

Learning And Generalization

Heterogeneous Multi-task Learning with Expert Diversity

R. Aoki, F. Tung, and G. Oliveira. Transactions on Computational Biology and Bioinformatics (TCBB), 2022

Learning And Generalization; Multi-task Learning

Evaluating Lossy Compression Rates of Deep Generative Models

*S. Huang, *A. Makhzani, Y. Cao, and R. Grosse. International Conference on Machine Learning (ICML), 2020

Generative Models; Learning And Generalization

Learning User Representations for Open Vocabulary Image Hashtag Prediction

T. Durand. The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2020

Computer Vision; Learning And Generalization

Max-Margin Adversarial Training: Direct Input Space Margin Maximization through Adversarial Training

G. W. Ding, Y. Sharma, K. Lui, and R. Huang. International Conference on Learning Representations (ICLR), 2020

Learning And Generalization; Responsible AI

Better Long-Range Dependency by Bootstrapping A Mutual Information Regularizer

*Y. Cao, and *P. Xu. International Conference on Artificial Intelligence and Statistics (AISTATS), 2020

Learning And Generalization; Natural Language Processing

Lifelong GAN: Continual Learning for Conditional Image Generation

*M. Zhai, *L. Chen, F. Tung, J. He, M. Nawhal, and G. Mori. International Conference on Computer Vision (ICCV), 2019

Generative Models; Learning And Generalization

Similarity-Preserving Knowledge Distillation

F. Tung, and G. Mori. International Conference on Computer Vision (ICCV), 2019

Computer Vision; Learning And Generalization

Uniform Stability and High Order Approximation of SGLD in Non-Convex Learning

M. Gazeau, and M. Li. International Conference on Machine Learning Workshop on Understanding and Improving Generalization in Deep Learning (ICML), 2019

Learning And Generalization

On the Sensitivity of Adversarial Robustness to Input Data Distributions

G. W. Ding, K. Y. C. Lui, T. Jin, L. Wang, and R. Huang. International Conference on Learning Representations (ICLR), 2019

Learning And Generalization; Responsible AI

Few-Shot Self Reminder to Overcome Catastrophic Forgetting

J. Wen, Y. Cao, and R. Huang. Conference on Neural Information Processing Systems Workshop on Continual Learning (NeurIPS), 2018

Learning And Generalization