Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Abstract. A well-known difficulty with solving Constraint Satisfaction Problems (CSPs) is that, while one formulation of a CSP may enable a solver to solve it quickly, a different ...
Abstract. Constraint satisfaction and propositional satisfiability problems are often solved using backtracking search. Previous studies have shown that a technique called randomi...
Abstract--Support vector machines (SVMs) were initially proposed to solve problems with two classes. Despite the myriad of schemes for multiclassification with SVMs proposed since ...
Joaquim F. Pinto da Costa, Ricardo Sousa, Jaime S....
Abstract. We propose a new graph-based label propagation algorithm for transductive learning. Each example is associated with a vertex in an undirected graph and a weighted edge be...