Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
We offer a new formal criterion for agent-centric learning in multi-agent systems, that is, learning that maximizes one’s rewards in the presence of other agents who might also...
In 1998, Impagliazzo and Wigderson [IW98] proved a hardness vs. randomness tradeoff for BPP in the uniform setting, which was subsequently extended to give optimal tradeoffs for t...
Scalability of object detectors with respect to the number of classes is a very important issue for applications where many object classes need to be detected. While combining sin...
The present paper deals with the averagecase complexity of various algorithms for learning univariate polynomials. For this purpose an appropriate framework is introduced. Based o...