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ICPR
2010
IEEE
14 years 7 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
SODA
2003
ACM
125views Algorithms» more  SODA 2003»
14 years 11 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 1 days 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 2 days 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»
14 years 9 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