60 citations · 124 across the 19 of their papers we have counts for
11 papers · 1 filter
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
Zihang Meng, Rudrasis Chakraborty, Vikas Singh
We present an efficient stochastic algorithm (RSG+) for canonical correlation analysis (CCA) using a reparametrization of the projection matrices. We show how this reparametrizatio…
Simpler Certified Radius Maximization by Propagating Covariances
Xingjian Zhen, Rudrasis Chakraborty, Vikas Singh
One strategy for adversarially training a robust model is to maximize its certified radius -- the neighborhood around a given training sample for which the model's prediction remai…
Learning Invariant Representations using Inverse Contrastive Loss
Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi +1
Learning invariant representations is a critical first step in a number of machine learning tasks. A common approach corresponds to the so-called information bottleneck principle i…
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center
Teja Kanchinadam, Zihang Meng, Joseph Bockhorst +2
Customer satisfaction is an important factor in creating and maintaining long-term relationships with customers. Near real-time identification of potentially dissatisfied customers…
Generating Accurate Pseudo-labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations
Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh +2
Rectified Linear Units (ReLUs) are among the most widely used activation function in a broad variety of tasks in vision. Recent theoretical results suggest that despite their excel…
Fooling Computer Vision into Inferring the Wrong Body Mass Index
Owen Levin, Zihang Meng, Vikas Singh +1
Recently it's been shown that neural networks can use images of human faces to accurately predict Body Mass Index (BMI), a widely used health indicator. In this paper we demonstrat…