Can we leverage learning techniques to build a fast nearest-neighbor (ANN) retrieval data structure? We present a general learning framework for the NN problem in which sample que...
Abstract. We investigate the use of parameterized state machine models to drive integration testing, in the case where the models of components are not available beforehand. Theref...
— We develop a systematic approach to incorporating uncertainty into planning manipulation tasks with frictional contacts. We consider the canonical problem of assembling a peg i...
Peng Cheng, David J. Cappelleri, Bogdan Gavrea, Vi...
— A simple approach for mobile robots to exploit multipath fading in order to improve received radio signal strength (RSS), is presented. The strategy is to sample the RSS at dis...
Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixedpo...