Background: Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-ev...
Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary ...
Paul D. Yoo, Abdur R. Sikder, Bing Bing Zhou, Albe...
Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In ...
We describe a novel framework for the design and analysis of online learning algorithms based on the notion of duality in constrained optimization. We cast a sub-family of universa...
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...