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ICML
2003
IEEE
16 years 7 months ago
Margin Distribution and Learning
Recent theoretical results have shown that improved bounds on generalization error of classifiers can be obtained by explicitly taking the observed margin distribution of the trai...
Ashutosh Garg, Dan Roth
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
16 years 1 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...
PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
16 years 1 months ago
Considering Unseen States as Impossible in Factored Reinforcement Learning
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
16 years 1 months ago
Discrete Regularization for Perceptual Image Segmentation via Semi-Supervised Learning and Optimal Control
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
Hongwei Zheng, Olaf Hellwich
ILP
2007
Springer
16 years 27 days ago
Learning with Kernels and Logical Representations
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
Paolo Frasconi