activity
20192021
most citedRevisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness

8 citations · 10 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20211 cited

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

Sandesh Ghimire, Aria Masoomi, Jennifer Dy

Estimating Kullback Leibler (KL) divergence from samples of two distributions is essential in many machine learning problems. Variational methods using neural network discriminator…

cs.LG20211 cited

Deep Bayesian Unsupervised Lifelong Learning

Tingting Zhao, Zifeng Wang, Aria Masoomi +1

Lifelong Learning (LL) refers to the ability to continually learn and solve new problems with incremental available information over time while retaining previous knowledge. Much a…

cs.LG20218 cited

Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness

Zifeng Wang, Tong Jian, Aria Masoomi +2

We investigate the HSIC (Hilbert-Schmidt independence criterion) bottleneck as a regularizer for learning an adversarially robust deep neural network classifier. In addition to the…

cs.LG2020

Kernel Dependence Network

Chieh Wu, Aria Masoomi, Arthur Gretton +1

We propose a greedy strategy to spectrally train a deep network for multi-class classification. Each layer is defined as a composition of linear weights with the feature map of a G…

stat.ML2019

Streaming Adaptive Nonparametric Variational Autoencoder

Tingting Zhao, Zifeng Wang, Aria Masoomi +1

We develop a data driven approach to perform clustering and end-to-end feature learning simultaneously for streaming data that can adaptively detect novel clusters in emerging data…