Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
The past few years have experienced an explosive growth in scientific and regulatory documents related to the patent system. Relevant information is siloed into many heterogeneous...
Siddharth Taduri, Gloria T. Lau, Kincho H. Law, Ha...
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...
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...