Model-based diagnostic reasoning often leads to a large number of diagnostic hypotheses. The set of diagnoses can be reduced by taking into account extra observations (passive mon...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
When dense matrix computations are too large to fit in cache, previous research proposes tiling to reduce or eliminate capacity misses. This paper presents a new algorithm for ch...
This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learni...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
Relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...
We state and analyze the first active learning algorithm which works in the presence of arbitrary forms of noise. The algorithm, A2 (for Agnostic Active), relies only upon the ass...
Maria-Florina Balcan, Alina Beygelzimer, John Lang...