Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, and protein or RNA transport. Thus, le...
Learning models for recognizing objects with few or no training examples is important, due to the intrinsic longtailed distribution of objects in the real world. In this paper, we...
We present a novel approach to learn distance metric for information retrieval. Learning distance metric from a number of queries with side information, i.e., relevance judgements...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...