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» Probabilistic models for pattern statistics
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151
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AGENTS
1998
Springer
15 years 7 months ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso
123
Voted
NIPS
2003
15 years 4 months ago
Link Prediction in Relational Data
Many real-world domains are relational in nature, consisting of a set of objects related to each other in complex ways. This paper focuses on predicting the existence and the type...
Benjamin Taskar, Ming Fai Wong, Pieter Abbeel, Dap...
162
Voted
ISNN
2009
Springer
15 years 10 months ago
A New Instance-Based Label Ranking Approach Using the Mallows Model
In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows mode...
Weiwei Cheng, Eyke Hüllermeier
219
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SPEECH
2011
14 years 10 months ago
Combining localization cues and source model constraints for binaural source separation
We describe a system for separating multiple sources from a two-channel recording based on interaural cues and prior knowledge of the statistics of the underlying source signals. ...
Ron J. Weiss, Michael I. Mandel, Daniel P. W. Elli...
115
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GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 9 months ago
Solving the MAXSAT problem using a multivariate EDA based on Markov networks
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
Alexander E. I. Brownlee, John A. W. McCall, Deryc...