We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
In recent years we have witnessed a great interest in large distributed computing platforms, also known as clouds. While these systems offer enormous computing power, they are howe...
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
—We formulate the problem of delay constrained energy-efficient broadcast in cooperative multihop wireless networks. We show that this important problem is not only NPcomplete, ...