We consider the problem of learning sparse parities in the presence of noise. For learning parities on r out of n variables, we give an algorithm that runs in time poly log 1 δ , ...
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other popular techniques that instead aim to reduce versio...
Abstract. Ontologies constitute an approach for knowledge representation that can be shared establishing a shared vocabulary for different applications and are also the backbone of...
We study the problem of learning parity functions that depend on at most k variables (kparities) attribute-efficiently in the mistake-bound model. We design a simple, deterministi...
Active learning is a framework that has attracted a lot of research interest in the content-based image retrieval (CBIR) in recent years. To be effective, an active learning syste...