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ICASSP
2010
IEEE
15 years 7 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»
15 years 11 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
206
Voted
ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
16 years 14 days 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»
15 years 1 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»
15 years 8 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