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» A distributed machine learning framework
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KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 3 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
PAMI
2012
13 years 5 months ago
Domain Transfer Multiple Kernel Learning
—Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has ...
Lixin Duan, Ivor W. Tsang, Dong Xu
PTS
2007
99views Hardware» more  PTS 2007»
15 years 4 months ago
Testing Input/Output Partial Order Automata
Abstract. We propose an extension of the Finite State Machine framework in distributed systems, using input/output partial order automata (IOPOA). In this model, transitions can be...
Stefan Haar, Claude Jard, Guy-Vincent Jourdan
ICML
2003
IEEE
16 years 4 months ago
Testing Exchangeability On-Line
The majority of theoretical work in machine learning is done under the assumption of exchangeability: essentially, it is assumed that the examples are generated from the same prob...
Vladimir Vovk, Ilia Nouretdinov, Alexander Gammerm...
NIPS
2000
15 years 4 months ago
High-temperature Expansions for Learning Models of Nonnegative Data
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
Oliver B. Downs