Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
In this paper, we present an algorithm to simultaneously align three biological sequences with affine gap model and infer their common ancestral sequence. Our algorithm can be fu...
Human gait and activity analysis from video is presently attracting a lot of attention in the computer vision community. In this paper, we analyze the role of two of the most impo...
Ashok Veeraraghavan, Amit K. Roy Chowdhury, Rama C...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...