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» On the Generalization Ability of On-Line Learning Algorithms
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FLAIRS
2004
15 years 1 months ago
A Faster Algorithm for Generalized Multiple-Instance Learning
In our prior work, we introduced a generalization of the multiple-instance learning (MIL) model in which a bag's label is not based on a single instance's proximity to a...
Qingping Tao, Stephen D. Scott
PAMI
2012
13 years 2 months ago
Sparse Algorithms Are Not Stable: A No-Free-Lunch Theorem
Abstract—We consider two desired properties of learning algorithms: sparsity and algorithmic stability. Both properties are believed to lead to good generalization ability. We sh...
Huan Xu, Constantine Caramanis, Shie Mannor
87
Voted
ICASSP
2010
IEEE
14 years 12 months ago
A general formalism for the analysis of distributed algorithms
The major contribution of this paper is the presentation of a general unifying description of distributed algorithms allowing to map local, node-based, algorithms onto a single gl...
Ondrej Sluciak, Thibault Hilaire, Markus Rupp
IJCNN
2006
IEEE
15 years 5 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
ICML
2009
IEEE
16 years 17 days ago
A least squares formulation for a class of generalized eigenvalue problems in machine learning
Many machine learning algorithms can be formulated as a generalized eigenvalue problem. One major limitation of such formulation is that the generalized eigenvalue problem is comp...
Liang Sun, Shuiwang Ji, Jieping Ye