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JCST
2010
153views more  JCST 2010»
13 years 7 months ago
Model Failure and Context Switching Using Logic-Based Stochastic Models
Abstract We define a notion of context that represents invariant, stable-over-time behavior in an environment and we propose an algorithm for detecting context changes in a stream ...
Nikita A. Sakhanenko, George F. Luger
JCB
2006
185views more  JCB 2006»
14 years 12 days ago
A Probabilistic Methodology for Integrating Knowledge and Experiments on Biological Networks
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
AAAI
1998
14 years 1 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies
EMNLP
2006
14 years 1 months ago
Discriminative Methods for Transliteration
We present two discriminative methods for name transliteration. The methods correspond to local and global modeling approaches in modeling structured output spaces. Both methods d...
Dmitry Zelenko, Chinatsu Aone
AAAI
2008
14 years 2 months ago
Learning and Inference with Constraints
Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
ISMIR
2003
Springer
150views Music» more  ISMIR 2003»
14 years 5 months ago
Automatic rhythm transcription from multiphonic MIDI signals
For automatically transcribing human-performed polyphonic music recorded in the MIDI format, rhythm and tempo are decomposed through probabilistic modeling using Viterbi search in...
Haruto Takeda, Takuya Nishimoto, Shigeki Sagayama
ICLP
2009
Springer
15 years 1 months ago
Generative Modeling by PRISM
PRISM is a probabilistic extension of Prolog. It is a high level language for probabilistic modeling capable of learning statistical parameters from observed data. After reviewing ...
Taisuke Sato
ICPR
2002
IEEE
15 years 1 months ago
Probabilistic Model-Based Detection of Bent-Double Radio Galaxies
We describe an application of probabilistic modeling to the problem of recognizing radio galaxies with a bentdouble morphology. The type of galaxies in question contain distinctiv...
Sergey Kirshner, Igor V. Cadez, Padhraic Smyth, Ch...