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ICPR
2010
IEEE
14 years 11 months ago
Cross Entropy Optimization of the Random Set Framework for Multiple Instance Learning
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...
Jeremy Bolton, Paul D. Gader
96
Voted
SODA
2003
ACM
125views Algorithms» more  SODA 2003»
15 years 3 months ago
Random MAX SAT, random MAX CUT, and their phase transitions
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...
CVPR
2012
IEEE
13 years 4 months ago
What is optimized in tight convex relaxations for multi-label problems?
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...
Christopher Zach, Christian Hane, Marc Pollefeys
STOC
2012
ACM
192views Algorithms» more  STOC 2012»
13 years 4 months ago
Nearly optimal sparse fourier transform
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 ...
CN
2007
148views more  CN 2007»
15 years 1 months ago
Optimizing random walk search algorithms in P2P networks
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...
Nabhendra Bisnik, Alhussein A. Abouzeid