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» Termination Analysis with Algorithmic Learning
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NN
2006
Springer
108views Neural Networks» more  NN 2006»
15 years 2 months ago
Performance analysis of LVQ algorithms: A statistical physics approach
Learning vector quantization (LVQ) constitutes a powerful and intuitive method for adaptive nearest prototype classification. However, original LVQ has been introduced based on he...
Anarta Ghosh, Michael Biehl, Barbara Hammer
132
Voted
VMCAI
2009
Springer
15 years 9 months ago
Shape-Value Abstraction for Verifying Linearizability
lue Abstraction for Verifying Linearizability Viktor Vafeiadis Microsoft Research, Cambridge, UK This paper presents a novel abstraction for heap-allocated data structures that kee...
Viktor Vafeiadis
121
Voted
APWEB
2005
Springer
15 years 8 months ago
An Incremental Subspace Learning Algorithm to Categorize Large Scale Text Data
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...
Jun Yan, QianSheng Cheng, Qiang Yang, Benyu Zhang
128
Voted
COLT
2007
Springer
15 years 8 months ago
Minimax Bounds for Active Learning
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Rui Castro, Robert D. Nowak
148
Voted
SIAMJO
2010
127views more  SIAMJO 2010»
14 years 9 months ago
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye