Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
On-line decision making often involves query processing over time-varying data which arrives in the form of data streams from distributed locations. In such environments typically...
Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
Boosted by technology advancements, government and commercial interest, ad-hoc wireless networks are emerging as a serious platform for distributed mission-critical applications. G...
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...