A dominant approach to Satisfiability Modulo Theories (SMT) relies on the integration of a Conflict-Driven-Clause-Learning (CDCL) SAT solver and of a decision procedure able to h...
Alberto Griggio, Quoc-Sang Phan, Roberto Sebastian...
We present a hierarchical feature fusion model for image classification that is constructed by an evolutionary learning algorithm. The model has the ability to combine local patch...
Fabien Scalzo, George Bebis, Mircea Nicolescu, Lea...
We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
We propose an unsupervised “local learning” algorithm for learning a metric in the input space. Geometrically, for a given query point, the algorithm finds the minimum volume ...
We study the learning models defined in [AKST97]: Learning with equivalence and limited membership queries and learning with equivalence and malicious membership queries. We show ...