In this work we present a new string similarity feature, the sparse spatial sample (SSS). An SSS is a set of short substrings at specific spatial displacements contained in the or...
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
In this paper, we motivate the need for and challenges involved in supporting imprecise queries over Web databases. Then we briefly explain our solution, AIMQ - a domain independe...
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...