This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Abstract--We present an algorithm that coevolves fitness predictors, optimized for the solution population, which reduce fitness evaluation cost and frequency, while maintaining ev...
Statistical estimation and approximate query processing have become increasingly prevalent applications for database systems. However, approximation is usually of little use witho...
— This paper addresses model reduction for a Markov chain on a large state space. A simulation-based framework is introduced to perform state aggregation of the Markov chain base...
We study an extension of the unit-demand pricing problem in which the seller may offer bundles of items. If a customer buys such a bundle she is guaranteed to get one item out of i...