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ICASSP
2010
IEEE
13 years 9 months ago
A general formalism for the analysis of distributed algorithms
The major contribution of this paper is the presentation of a general unifying description of distributed algorithms allowing to map local, node-based, algorithms onto a single gl...
Ondrej Sluciak, Thibault Hilaire, Markus Rupp
STOC
2000
ACM
174views Algorithms» more  STOC 2000»
14 years 1 months ago
Noise-tolerant learning, the parity problem, and the statistical query model
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
Avrim Blum, Adam Kalai, Hal Wasserman
ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
14 years 2 months ago
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
Thomas Takeo Osugi, Kun Deng, Stephen D. Scott
CDC
2010
IEEE
113views Control Systems» more  CDC 2010»
13 years 3 months ago
Independent vs. joint estimation in multi-agent iterative learning control
This paper studies iterative learning control (ILC) in a multi-agent framework. A group of agents simultaneously and repeatedly perform the same task. The agents improve their perf...
Angela Schöllig, Javier Alonso-Mora, Raffaell...
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 10 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won