In this paper we describe a problem of discovering query clusters from a click-through graph of web search logs. The graph consists of a set of web search queries, a set of pages ...
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...
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
We investigate the theoretical limits of positioning algorithms. In particular, we study scenarios where the nodes do not receive anchors directly (multi-hop) and where no physica...