Zobrazeno 1 - 10 of 50 pro vyhledávání: '"Seldin, Y."'
2
PAC-Bayesian Analysis of Martingales and Multiarmed Bandits
Autor: Seldin, Y., Laciolette, F., Shaw-Taylor, J., Peters, J., Auer, P.
Publikováno v: Technical Reports of the Max Planck Institute for Biological Cybernetics
We present two alternative ways to apply PAC-Bayesian analysis to sequences of dependent random variables. The first is based on a new lemma that enables to bound expectations of convex functions of certain dependent random variables by expectations
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1874::4daad91cafac92fe45fb4ed4ed80572e
https://hdl.handle.net/11858/00-001M-0000-0013-BBE6-621.11116/0000-0002-0F75-B
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4
A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering
Autor: Seldin, Y.
Publikováno v: Technical Report of the Max Planck Institute for Biological Cybernetics
We formulate weighted graph clustering as a prediction problem: given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. This formulation enables practical and theoretical comparison of differen
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1874::9897f1214410b84b71fde58c8d284373
https://hdl.handle.net/21.11116/0000-0002-856D-E11858/00-001M-0000-0013-BE7A-2
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5
A PAC-Bayesian Analysis of Co-clustering, Graph Clustering, and Pairwise Clustering
Autor: Seldin, Y.
Publikováno v: ICML 2010 Workshop on Social Analytics: Learning from human interactions
We review briefly the PAC-Bayesian analysis of co-clustering (Seldin and Tishby, 2008, 2009, 2010), which provided generalization guarantees and regularization terms absent in the preceding formulations of this problem and achieved state-of-the-art p
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1874::711b530a99fa93558305a31a37f49f08
https://hdl.handle.net/21.11116/0000-0002-81D2-E11858/00-001M-0000-0013-BF92-2
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6
PAC-Bayesian Bounds for Discrete Density Estimation and Co-clustering Analysis
Autor: Seldin, Y., Tishby, N.
Publikováno v: Foundations and New Trends of PAC Bayesian Learning Workshop
We applied PAC-Bayesian framework to derive gen-eralization bounds for co-clustering1. The analysis yielded regularization terms that were absent in the preceding formulations of this task. The bounds suggested that co-clustering should optimize a tr
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1874::8058150a114f1866b403a2f791973afc
https://hdl.handle.net/11858/00-001M-0000-0013-C10E-121.11116/0000-0002-94D7-4
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7
A PAC-Bayesian Approach to Formulation of Clustering Objectives
Autor: Seldin, Y., Tishby, N.
Publikováno v: NIPS 2009 Workshop "Clustering: Science or Art? Towards Principled Approaches"
Clustering is a widely used tool for exploratory data analysis. However, the theoretical understanding of clustering is very limited. We still do not have a well-founded answer to the seemingly simple question of “how many clusters are present in t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1874::e52efd7517b73c93b14b2be8e9bca11d
https://hdl.handle.net/11858/00-001M-0000-0013-C1D6-E21.11116/0000-0002-CA59-7
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9
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10
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