We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Abstract— A distributed online learning framework for support vector machines (SVMs) is presented and analyzed. First, the generic binary classification problem is decomposed in...