Background: Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on differen...
Marc Vincent, Andrea Passerini, Matthieu Labb&eacu...
Machine learning of limit programs (i.e., programs allowed finitely many mind changes about their legitimate outputs) for computable functions is studied. Learning of iterated lim...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
The Modular Architecture for Bootstrapped Learning Experiments (MABLE) is a system that is being developed to allow humans to teach computers in the most natural manner possible: ...
Roger Mailler, Daniel Bryce, Jiaying Shen, Ciaran ...