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AI
1999
Springer
13 years 8 months ago
Bucket Elimination: A Unifying Framework for Reasoning
Bucket elimination is an algorithmic framework that generalizes dynamic programming to accommodate many problem-solving and reasoning tasks. Algorithms such as directional-resolut...
Rina Dechter
STOC
2004
ACM
150views Algorithms» more  STOC 2004»
14 years 9 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 2 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
TASLP
2011
13 years 3 months ago
A Probabilistic Interaction Model for Multipitch Tracking With Factorial Hidden Markov Models
—We present a simple and efficient feature modeling approach for tracking the pitch of two simultaneously active speakers. We model the spectrogram features of single speakers u...
Michael Wohlmayr, Michael Stark, Franz Pernkopf
ECCV
2008
Springer
14 years 10 months ago
Beyond Loose LP-Relaxations: Optimizing MRFs by Repairing Cycles
This paper presents a new MRF optimization algorithm, which is derived from Linear Programming and manages to go beyond current state-of-the-art techniques (such as those based on ...
Nikos Komodakis, Nikos Paragios