We introduce a new model for distributed algorithms designed for large scale systems that need a low-overhead solution to allow the processes to communicate with each other. We as...
We study the complexity of satisfiability for the expressive extension ICPDL of PDL (Propositional Dynamic Logic), which admits intersection and converse as program operations. Ou...
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
We present a reduction from graphical games to Markov random fields so that pure Nash equilibria in the former can be found by statistical inference on the latter. Our result, wh...
Constantinos Daskalakis, Christos H. Papadimitriou
We propose a model of computation where a Turing machine is given random access to an advice string. With random access, an advice string of exponential length becomes meaningful ...