Abstract--Multiple instance learning (MIL) is a recently researched technique used for learning a target concept in the presence of noise. Previously, a random set framework for mu...
With random inputs, certain decision problems undergo a “phase transition”. We prove similar behavior in an optimization context. Given a conjunctive normal form (CNF) formula...
Don Coppersmith, David Gamarnik, Mohammad Taghi Ha...
In this work we present a unified view on Markov random fields and recently proposed continuous tight convex relaxations for multi-label assignment in the image plane. These rel...
We consider the problem of computing the k-sparse approximation to the discrete Fourier transform of an ndimensional signal. We show: • An O(k log n)-time randomized algorithm f...
Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric ...
In this paper we develop a model for random walk-based search mechanisms in unstructured P2P networks. This model is used to obtain analytical expressions for the performance metr...