7 citations · 13 across the 4 of their papers we have counts for
5 papers
Learning to Approximate a Bregman Divergence
Ali Siahkamari, Xide Xia, Venkatesh Saligrama +2
Bregman divergences generalize measures such as the squared Euclidean distance and the KL divergence, and arise throughout many areas of machine learning. In this paper, we focus o…
Multi-Agent Discrete Search with Limited Visibility
Huanyu Ding, David Castanon
The problem of search by multiple agents to find and localize objects arises in many important applications. In this paper, we study a class of multi-agent search problems in which…
Optimal Solutions for Adaptive Search Problems with Entropy Objectives
Huanyu Ding, David A. Castañón
The problem of searching for an unknown object occurs in important applications ranging from security, medicine and defense. Sensors with the capability to process information rapi…
Multi-Stage Classifier Design
Kirill Trapeznikov, Venkatesh Saligrama, David Castanon
In many classification systems, sensing modalities have different acquisition costs. It is often {\it unnecessary} to use every modality to classify a majority of examples. We stud…
Structural Similarity and Distance in Learning
Joseph Wang, Venkatesh Saligrama, David A. Castañón
We propose a novel method of introducing structure into existing machine learning techniques by developing structure-based similarity and distance measures. To learn structural inf…