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» Concurrency and the Principle of Data Locality
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NECO
1998
168views more  NECO 1998»
14 years 9 months ago
Constructive Incremental Learning from Only Local Information
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Stefan Schaal, Christopher G. Atkeson
ECCV
2008
Springer
15 years 11 months ago
Learning to Localize Objects with Structured Output Regression
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Matthew B. Blaschko, Christoph H. Lampert
ICPP
1994
IEEE
15 years 1 months ago
Optimizing IPC Performance for Shared-Memory Multiprocessors
We assert that in order to perform well, a shared-memory multiprocessorinter-process communication (IPC)facility mustavoid a) accessing any shared data, and b) acquiring any locks...
Benjamin Gamsa, Orran Krieger, Michael Stumm
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...
84
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IJAR
2010
130views more  IJAR 2010»
14 years 8 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki