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» Ensemble Methods in Machine Learning
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ML
2006
ACM
121views Machine Learning» more  ML 2006»
15 years 16 days ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
AAAI
2007
15 years 2 months ago
On the Prospects for Building a Working Model of the Visual Cortex
Human visual capability has remained largely beyond the reach of engineered systems despite intensive study and considerable progress in problem understanding, algorithms and comp...
Thomas Dean, Glenn Carroll, Richard Washington
ICML
2006
IEEE
16 years 1 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara
102
Voted
ICML
2004
IEEE
16 years 1 months ago
Distribution kernels based on moments of counts
Many applications in text and speech processing require the analysis of distributions of variable-length sequences. We recently introduced a general kernel framework, rational ker...
Corinna Cortes, Mehryar Mohri
85
Voted
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 6 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna