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BMCBI
2007
215views more  BMCBI 2007»
15 years 4 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
JMLR
2008
124views more  JMLR 2008»
15 years 4 months ago
Learning Control Knowledge for Forward Search Planning
A number of today's state-of-the-art planners are based on forward state-space search. The impressive performance can be attributed to progress in computing domain independen...
Sung Wook Yoon, Alan Fern, Robert Givan
CORR
2011
Springer
178views Education» more  CORR 2011»
14 years 7 months ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
STACS
1999
Springer
15 years 8 months ago
Costs of General Purpose Learning
Leo Harrington surprisingly constructed a machine which can learn any computable function f according to the following criterion (called Bc∗ -identification). His machine, on t...
John Case, Keh-Jiann Chen, Sanjay Jain
CORR
2008
Springer
116views Education» more  CORR 2008»
15 years 4 months ago
Learning to rank with combinatorial Hodge theory
Abstract. We propose a number of techniques for learning a global ranking from data that may be incomplete and imbalanced -- characteristics that are almost universal to modern dat...
Xiaoye Jiang, Lek-Heng Lim, Yuan Yao, Yinyu Ye