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» On the Complexity of Exclusion Algorithms for Optimization
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ICML
2006
IEEE
16 years 7 months ago
Agnostic active learning
We state and analyze the first active learning algorithm which works in the presence of arbitrary forms of noise. The algorithm, A2 (for Agnostic Active), relies only upon the ass...
Maria-Florina Balcan, Alina Beygelzimer, John Lang...
CORR
2007
Springer
89views Education» more  CORR 2007»
15 years 6 months ago
Speeding up Simplification of Polygonal Curves using Nested Approximations
: We develop a multiresolution approach to the problem of polygonal curve approximation. We show theoretically and experimentally that, if the simplification algorithm A used betwe...
Pierre-Francois Marteau, Gildas Ménier
NIPS
2007
15 years 8 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
GECCO
2004
Springer
137views Optimization» more  GECCO 2004»
16 years 2 days ago
Evolving Better Multiple Sequence Alignments
Aligning multiple DNA or protein sequences is a fundamental step in the analyses of phylogeny, homology and molecular structure. Heuristic algorithms are applied because optimal mu...
Luke Sheneman, James A. Foster
SIGMOD
2011
ACM
276views Database» more  SIGMOD 2011»
14 years 9 months ago
Schedule optimization for data processing flows on the cloud
Scheduling data processing workflows (dataflows) on the cloud is a very complex and challenging task. It is essentially an optimization problem, very similar to query optimizati...
Herald Kllapi, Eva Sitaridi, Manolis M. Tsangaris,...