We develop a method for predicting query performance by computing the relative entropy between a query language model and the corresponding collection language model. The resultin...
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
After a quick overview of the field of study known as “Lexical Semantics”, where we advocate the need of accessing additional information besides syntax and Montaguestyle sema...
Christian Bassac, Bruno Mery, Christian Retor&eacu...
We propose a mathematical framework for query selection as a mechanism for reducing the cost of constructing information retrieval test collections. In particular, our mathematica...
Mehdi Hosseini, Ingemar J. Cox, Natasa Milic-Frayl...
Abstract. This paper presents a theory that encompasses both "plenoptic" (microlens based) and "heterodyning" (mask based) cameras in a single frequency-domain ...