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KDD
2004
ACM
158views Data Mining» more  KDD 2004»
15 years 10 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
ECAI
2004
Springer
15 years 1 months ago
Instance-Based Prediction with Guaranteed Confidence
Instance-based learning (IBL) algorithms have proved to be successful in many applications. However, as opposed to standard statistical methods, a prediction in IBL is usually give...
Eyke Hüllermeier
SYNTHESE
2008
84views more  SYNTHESE 2008»
14 years 9 months ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
Thomas Bartz-Beielstein
INFOCOM
2007
IEEE
15 years 4 months ago
When TCP Friendliness Becomes Harmful
Abstract— Short TCP flows may suffer significant responsetime performance degradations during network congestion. Unfortunately, this creates an incentive for misbehavior by cl...
Amit Mondal, Aleksandar Kuzmanovic
SDM
2008
SIAM
138views Data Mining» more  SDM 2008»
14 years 11 months ago
Learning Markov Network Structure using Few Independence Tests
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Parichey Gandhi, Facundo Bromberg, Dimitris Margar...