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» Approximate algorithms for neural-Bayesian approaches
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KDD
2006
ACM
163views Data Mining» more  KDD 2006»
15 years 10 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
WSDM
2009
ACM
131views Data Mining» more  WSDM 2009»
15 years 4 months ago
Diversifying search results
We study the problem of answering ambiguous web queries in a setting where there exists a taxonomy of information, and that both queries and documents may belong to more than one ...
Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverso...
ICFCA
2009
Springer
15 years 4 months ago
Factor Analysis of Incidence Data via Novel Decomposition of Matrices
Matrix decomposition methods provide representations of an object-variable data matrix by a product of two different matrices, one describing relationship between objects and hidd...
Radim Belohlávek, Vilém Vychodil
EMO
2009
Springer
219views Optimization» more  EMO 2009»
15 years 4 months ago
An Elitist GRASP Metaheuristic for the Multi-objective Quadratic Assignment Problem
We propose an elitist Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic algorithm, called mGRASP/MH, for approximating the Pareto-optimal front in the multi-objecti...
Hui Li, Dario Landa Silva
AVSS
2008
IEEE
15 years 4 months ago
Person Tracking with Audio-Visual Cues Using the Iterative Decoding Framework
Tracking humans in an indoor environment is an essential part of surveillance systems. Vision based and microphone array based trackers have been extensively researched in the pas...
Shankar T. Shivappa, Mohan M. Trivedi, Bhaskar D. ...