This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
Given a quarter of petabyte click log data, how can we estimate the relevance of each URL for a given query? In this paper, we propose the Bayesian Browsing Model (BBM), a new mod...
We present a novel use of ordinal evaluation (OrdEval) algorithm as a promising technique to study various marketing phenomena. OrdEval algorithm has originated in data mining and ...
—An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules i...