activity
20182022
most citedMachine Learning on Camera Images for Fast mmWave Beamforming

21 citations · 38 across the 9 of their papers we have counts for

collaborators

14 papers

stat.ML2022

Deep Layer-wise Networks Have Closed-Form Weights

Chieh Wu, Aria Masoomi, Arthur Gretton +1

There is currently a debate within the neuroscience community over the likelihood of the brain performing backpropagation (BP). To better mimic the brain, training a network \texti…

cs.LG20224 cited

Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Network

Batool Salehi, Guillem Reus-Muns, Debashri Roy +5

Beam selection for millimeter-wave links in a vehicular scenario is a challenging problem, as an exhaustive search among all candidate beam pairs cannot be assuredly completed with…

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…

stat.ML2021

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…