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IJCAI
2007
13 years 8 months ago
Concept Sampling: Towards Systematic Selection in Large-Scale Mixed Concepts in Machine Learning
This paper addresses the problem of concept sampling. In many real-world applications, a large collection of mixed concepts is available for decision making. However, the collecti...
Yi Zhang 0010, Xiaoming Jin
ICML
2008
IEEE
14 years 7 months ago
Stopping conditions for exact computation of leave-one-out error in support vector machines
We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-OneOut error computation. The stopping condition ...
Klaus-Robert Müller, Pavel Laskov, Vojtech Fr...
COLT
2010
Springer
13 years 4 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
ICML
1998
IEEE
14 years 7 months ago
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization
In this work, we present a new bottom-up algorithmfor decision tree pruning that is very e cient requiring only a single pass through the given tree, and prove a strong performanc...
Michael J. Kearns, Yishay Mansour
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 6 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng