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ESANN
2006
15 years 1 months ago
Using sampling methods to improve binding site predictions
Currently the best algorithms for transcription factor binding site prediction are severely limited in accuracy. In previous work we combine random selection under-sampling with th...
Yi Sun, Mark Robinson, Rod Adams, Rene te Boekhors...
106
Voted
CORR
2010
Springer
86views Education» more  CORR 2010»
15 years 16 days ago
Matching with Couples Revisited
It is well known that a stable matching in a many-to-one matching market with couples need not exist. We introduce a new matching algorithm for such markets and show that for a ge...
Itai Ashlagi, Mark Braverman, Avinatan Hassidim
101
Voted
IJAHUC
2008
83views more  IJAHUC 2008»
15 years 13 days ago
Connectivity of a Gaussian network
: Following Etherington, Hoge and Parkes, we consider a network consisting of (approximately) N transceivers in the plane R2 distributed randomly with density given by a Gaussian d...
Paul N. Balister, Béla Bollobás, Ami...
117
Voted
CORR
2011
Springer
148views Education» more  CORR 2011»
14 years 7 months ago
How well can we estimate a sparse vector?
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Emmanuel J. Candès, Mark A. Davenport
ICML
2006
IEEE
16 years 1 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil