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ICMAS
1998
15 years 7 months ago
Multi-Machine Scheduling - A Multi-Agent Learning Approach
Multi-machine scheduling, that is, the assigment of jobs to machines such that certain performance demands like cost and time effectiveness are fulfilled, is a ubiquitous and comp...
Wilfried Brauer, Gerhard Weiß
JMLR
2008
168views more  JMLR 2008»
15 years 6 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
ICDAR
2007
IEEE
16 years 19 days ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
ICML
2006
IEEE
16 years 7 months ago
Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution
The Dirichlet compound multinomial (DCM) distribution, also called the multivariate Polya distribution, is a model for text documents that takes into account burstiness: the fact ...
Charles Elkan
IFIP12
2008
15 years 7 months ago
A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System
Sampling methods are a direct approach to tackle the problem of class imbalance. These methods sample a data set in order to alter the class distributions. Usually these methods ar...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...