Abstract-- In this paper, we consider the distributed computation of equilibria arising in monotone stochastic Nash games over continuous strategy sets. Such games arise in setting...
We give a new model of learning motivated by smoothed analysis (Spielman and Teng, 2001). In this model, we analyze two new algorithms, for PAC-learning DNFs and agnostically learn...
Adam Tauman Kalai, Alex Samorodnitsky, Shang-Hua T...
We propose a lattice-based functional encryption scheme for inner product predicates whose security follows from the difficulty of the learning with errors (LWE) problem. This co...
Shweta Agrawal, David Mandell Freeman, Vinod Vaiku...
We present a statistical method that PAC learns the class of stochastic perceptrons with arbitrary monotonic activation function and weights wi {-1, 0, +1} when the probability d...
In recent work, Kalai, Klivans, Mansour, and Servedio [KKMS05] studied a variant of the "Low-Degree (Fourier) Algorithm" for learning under the uniform probability distr...