This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...
Kevin Miller, M. Pawan Kumar, Benjamin Packer, Dan...
Historical prices are important information that can help consumers decide whether the time is right to buy a product. They provide both a context to the users, and facilitate the...
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
In this work we address the problem of managing interconnect timing in high-level synthesis by generating a layoutfriendly microarchitecture. A metric called spreading score is pr...