POMDPs and their decentralized multiagent counterparts, DEC-POMDPs, offer a rich framework for sequential decision making under uncertainty. Their computational complexity, howeve...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
Decision tree induction techniques attempt to find small trees that fit a training set of data. This preference for smaller trees, which provides a learning bias, is often justifie...
Christian Bessiere, Emmanuel Hebrard, Barry O'Sull...
Hyperspectral unmixing is a process of extracting hidden spectral signatures (or endmembers) and the corresponding proportions (or abundances) of a scene, from its hyperspectral o...
Non-stationarity is often found in session-to-session transfers of Brain Computer Interfaces (BCIs). To cope with the problem, a framework based on Common Spatial Patterns (CSP), ...
In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...