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» Introduction to Randomized Algorithms
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IROS
2007
IEEE
158views Robotics» more  IROS 2007»
15 years 9 months ago
Feature selection in conditional random fields for activity recognition
Abstract— Temporal classification, such as activity recognition, is a key component for creating intelligent robot systems. In the case of robots, classification algorithms mus...
Douglas L. Vail, John D. Lafferty, Manuela M. Velo...
SP
2006
IEEE
193views Security Privacy» more  SP 2006»
15 years 9 months ago
Analysis of the Linux Random Number Generator
Linux is the most popular open source project. The Linux random number generator is part of the kernel of all Linux distributions and is based on generating randomness from entrop...
Zvi Gutterman, Benny Pinkas, Tzachy Reinman
SIGECOM
2006
ACM
143views ECommerce» more  SIGECOM 2006»
15 years 9 months ago
Braess's paradox in large random graphs
Braess’s Paradox is the counterintuitive but well-known fact that removing edges from a network with “selfish routing” can decrease the latency incurred by traffic in an eq...
Gregory Valiant, Tim Roughgarden
SIGIR
2006
ACM
15 years 9 months ago
Answering complex questions with random walk models
We present a novel framework for answering complex questions that relies on question decomposition. Complex questions are decomposed by a procedure that operates on a Markov chain...
Sanda M. Harabagiu, V. Finley Lacatusu, Andrew Hic...
SIGIR
2005
ACM
15 years 9 months ago
A Markov random field model for term dependencies
This paper develops a general, formal framework for modeling term dependencies via Markov random fields. The model allows for arbitrary text features to be incorporated as eviden...
Donald Metzler, W. Bruce Croft