Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
On large datasets, the popular training approach has been stochastic gradient descent (SGD). This paper proposes a modification of SGD, called averaged SGD with feedback (ASF), tha...
This paper proposes a hybrid approximate pattern matching/ transform-based compression engine. The idea is to use regular video interframe prediction as a pattern matching algorit...
In this paper, we present a method to speed up video encoding of GPU rendered 3D scenes, which is particularly suited for the efficient and low-delay encoding of 3D game output as...
Abstract--We study how to effectively integrate reinforcement learning (RL) and programming languages via adaptation-based programming, where programs can include non-deterministic...