—It is well-known that the linear scale-space theory in computer vision is mainly based on the Gaussian kernel. The purpose of the paper is to propose a scale-space theory based ...
Boolean satisfiability (SAT) based methods have traditionally been popular for formally verifying properties for digital circuits. We present a novel methodology for formulating a...
Saurabh K. Tiwary, Anubhav Gupta, Joel R. Phillips...
Identifying peptides, which are short polymeric chains of amino acid residues in a protein sequence, is of fundamental importance in systems biology research. The most popular appr...
Abstract—Computer systems are increasingly driven by workloads that reflect large-scale social behavior, such as rapid changes in the popularity of media items like videos. Capa...
We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizo...