10 citations · 16 across the 3 of their papers we have counts for
5 papers
Escaping Saddle-Points Faster under Interpolation-like Conditions
Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi +1
In this paper, we show that under over-parametrization several standard stochastic optimization algorithms escape saddle-points and converge to local-minimizers much faster. One of…
Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point Optimization
Abhishek Roy, Yifang Chen, Krishnakumar Balasubramanian +1
Saddle-point optimization problems are an important class of optimization problems with applications to game theory, multi-agent reinforcement learning and machine learning. A majo…
Suspicion-Free Adversarial Attacks on Clustering Algorithms
Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
Clustering algorithms are used in a large number of applications and play an important role in modern machine learning-- yet, adversarial attacks on clustering algorithms seem to b…
Multi-Point Bandit Algorithms for Nonstationary Online Nonconvex Optimization
Abhishek Roy, Krishnakumar Balasubramanian, Saeed Ghadimi +1
Bandit algorithms have been predominantly analyzed in the convex setting with function-value based stationary regret as the performance measure. In this paper, motivated by online…
Strong Black-box Adversarial Attacks on Unsupervised Machine Learning Models
Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
Machine Learning (ML) and Deep Learning (DL) models have achieved state-of-the-art performance on multiple learning tasks, from vision to natural language modelling. With the growi…