14 citations · 31 across the 10 of their papers we have counts for
6 papers · 1 filter
Sanity Checks for Saliency Metrics
Richard Tomsett, Dan Harborne, Supriyo Chakraborty +2
Saliency maps are a popular approach to creating post-hoc explanations of image classifier outputs. These methods produce estimates of the relevance of each pixel to the classifica…
Wasserstein Distance Based Domain Adaptation for Object Detection
Pengcheng Xu, Prudhvi Gurram, Gene Whipps +1
In this paper, we present an adversarial unsupervised domain adaptation framework for object detection. Prior approaches utilize adversarial training based on cross entropy between…
Distributed Deep Learning with Event-Triggered Communication
Jemin George, Prudhvi Gurram
We develop a Distributed Event-Triggered Stochastic GRAdient Descent (DETSGRAD) algorithm for solving non-convex optimization problems typically encountered in distributed deep lea…
Distributed Stochastic Gradient Method for Non-Convex Problems with Applications in Supervised Learning
Jemin George, Tao Yang, He Bai +1
We develop a distributed stochastic gradient descent algorithm for solving non-convex optimization problems under the assumption that the local objective functions are twice contin…
A Bayesian Theory of Change Detection in Statistically Periodic Random Processes
Taposh Banerjee, Prudhvi Gurram, Gene Whipps
A new class of stochastic processes called independent and periodically identically distributed (i.p.i.d.) processes is defined to capture periodically varying statistical behavior…
Minimax-Optimal Algorithms for Detecting Changes in Statistically Periodic Random Processes
Taposh Banerjee, Prudhvi Gurram, Gene Whipps
Theory and algorithms are developed for detecting changes in the distribution of statistically periodic random processes. The statistical periodicity is modeled using independent a…