Sciweavers

PR
2006
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13 years 9 months ago
Geometric visualization of clusters obtained from fuzzy clustering algorithms
Fuzzy-clustering methods, such as fuzzy k-means and Expectation Maximization, allow an object to be assigned to multiple clusters with different degrees of membership. However, th...
Luis Rueda, Yuanquan Zhang
NIPS
1998
13 years 10 months ago
Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
Tony Jebara, Alex Pentland
UAI
2003
13 years 10 months ago
The Information Bottleneck EM Algorithm
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...
Gal Elidan, Nir Friedman
ECML
2006
Springer
14 years 1 months ago
Learning Process Models with Missing Data
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
Will Bridewell, Pat Langley, Steve Racunas, Stuart...
IDEAL
2007
Springer
14 years 3 months ago
Partitioning-Clustering Techniques Applied to the Electricity Price Time Series
Clustering is used to generate groupings of data from a large dataset, with the intention of representing the behavior of a system as accurately as possible. In this sense, cluster...
Francisco Martínez-Álvarez, Alicia T...
AI
2009
Springer
14 years 4 months ago
Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Abstract. We use a hierarchical Bayesian approach to model user preferences in different contexts or settings. Unlike many previous recommenders, our approach is content-based. We...
Daniel Pomerantz, Gregory Dudek
AI
2009
Springer
14 years 4 months ago
Exploratory Analysis of Co-Change Graphs for Code Refactoring
Abstract. Version Control Systems (VCS) have always played an essential role for developing reliable software. Recently, many new ways of utilizing the information hidden in VCS ha...
Hassan Khosravi, Recep Colak
EACL
2009
ACL Anthology
14 years 10 months ago
EM Works for Pronoun Anaphora Resolution
We present an algorithm for pronounanaphora (in English) that uses Expectation Maximization (EM) to learn virtually all of its parameters in an unsupervised fashion. While EM freq...
Eugene Charniak, Micha Elsner
ICML
2001
IEEE
14 years 10 months ago
Estimating a Kernel Fisher Discriminant in the Presence of Label Noise
Data noise is present in many machine learning problems domains, some of these are well studied but others have received less attention. In this paper we propose an algorithm for ...
Bernhard Schölkopf, Neil D. Lawrence
ICIP
2002
IEEE
14 years 11 months ago
Likelihood-based object detection and object tracking using color histograms and EM
The topic of this paper is the integration of Expectation Maximization (EM) background modeling and template matching using color histograms as templates to improve person trackin...
Paul J. Withagen, Klamer Schutte, Frans C. A. Groe...