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» On Learning Monotone DNF under Product Distributions
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CDC
2010
IEEE
104views Control Systems» more  CDC 2010»
13 years 2 months ago
Single timescale regularized stochastic approximation schemes for monotone Nash games under uncertainty
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...
Jayash Koshal, Angelia Nedic, Uday V. Shanbhag
FOCS
2009
IEEE
13 years 5 months ago
Learning and Smoothed Analysis
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...
ASIACRYPT
2011
Springer
12 years 7 months ago
Functional Encryption for Inner Product Predicates from Learning with Errors
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...
NIPS
1994
13 years 8 months ago
Learning Stochastic Perceptrons Under k-Blocking Distributions
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...
Mario Marchand, Saeed Hadjifaradji
COLT
2008
Springer
13 years 9 months ago
Polynomial Regression under Arbitrary Product Distributions
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...
Eric Blais, Ryan O'Donnell, Karl Wimmer