111 citations · 1k across the 103 of their papers we have counts for
8 papers · 1 filter
MR-GAN: Manifold Regularized Generative Adversarial Networks
Qunwei Li, Bhavya Kailkhura, Rushil Anirudh +3
Despite the growing interest in generative adversarial networks (GANs), training GANs remains a challenging problem, both from a theoretical and a practical standpoint. To address…
MimicGAN: Corruption-Mimicking for Blind Image Recovery & Adversarial Defense
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura +1
Solving inverse problems continues to be a central challenge in computer vision. Existing techniques either explicitly construct an inverse mapping using prior knowledge about the…
Universal Decision-Based Black-Box Perturbations: Breaking Security-Through-Obscurity Defenses
Thomas A. Hogan, Bhavya Kailkhura
We study the problem of finding a universal (image-agnostic) perturbation to fool machine learning (ML) classifiers (e.g., neural nets, decision tress) in the hard-label black-box…
Coverage-Based Designs Improve Sample Mining and Hyper-Parameter Optimization
Gowtham Muniraju, Bhavya Kailkhura, Jayaraman J. Thiagarajan +3
Sampling one or more effective solutions from large search spaces is a recurring idea in machine learning, and sequential optimization has become a popular solution. Typical exampl…
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen +3
As application demands for zeroth-order (gradient-free) optimization accelerate, the need for variance reduced and faster converging approaches is also intensifying. This paper add…
An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks
Rushil Anirudh, Jayaraman J. Thiagarajan, Bhavya Kailkhura +1
Solving inverse problems continues to be a challenge in a wide array of applications ranging from deblurring, image inpainting, source separation etc. Most existing techniques solv…
Byzantine-Resilient Locally Optimum Detection Using Collaborative Autonomous Networks
Bhavya Kailkhura, Priyadip Ray, Deepak Rajan +3
In this paper, we propose a locally optimum detection (LOD) scheme for detecting a weak radioactive source buried in background clutter. We develop a decentralized algorithm, based…
Human-Machine Inference Networks For Smart Decision Making: Opportunities and Challenges
Aditya Vempaty, Bhavya Kailkhura, Pramod K. Varshney
The emerging paradigm of Human-Machine Inference Networks (HuMaINs) combines complementary cognitive strengths of humans and machines in an intelligent manner to tackle various inf…