We discuss information retrieval methods that aim at serving a diverse stream of user queries such as those submitted to commercial search engines. We propose methods that emphasi...
Hongyuan Zha, Zhaohui Zheng, Haoying Fu, Gordon Su...
In this paper, we investigate multi-agent learning (MAL) in a multi-agent resource selection problem (MARS) in which a large group of agents are competing for common resources. Si...
We consider the problem of learning incoherent sparse and lowrank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the spa...
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...