We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
Pattern variation is a major factor that affects the performance of recognition systems. In this paper, a novel manifold tangent modeling method called Discriminant Additive Tange...
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
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...
Natural language is full of patterns that appear to fit with general linguistic rules but are ungrammatical. There has been much debate over how children acquire these ‘‘ling...