105 citations · 195 across the 28 of their papers we have counts for
6 papers · 1 filter
Learning to Prompt for Continual Learning
Zifeng Wang, Zizhao Zhang, Chen-Yu Lee +7
The mainstream paradigm behind continual learning has been to adapt the model parameters to non-stationary data distributions, where catastrophic forgetting is the central challeng…
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…
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…
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…
On the Sample Complexity of Rank Regression from Pairwise Comparisons
Berkan Kadioglu, Peng Tian, Jennifer Dy +2
We consider a rank regression setting, in which a dataset of samples with features in is ranked by an oracle via pairwise comparisons. Specifically, there ex…
Machine Learning on Camera Images for Fast mmWave Beamforming
Batool Salehi, Mauro Belgiovine, Sara Garcia Sanchez +3
Perfect alignment in chosen beam sectors at both transmit- and receive-nodes is required for beamforming in mmWave bands. Current 802.11ad WiFi and emerging 5G cellular standards s…