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ICML
2010
IEEE
13 years 8 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
BMCBI
2010
125views more  BMCBI 2010»
13 years 7 months ago
Large-scale prediction of protein-protein interactions from structures
Background: The prediction of protein-protein interactions is an important step toward the elucidation of protein functions and the understanding of the molecular mechanisms insid...
Martial Hue, Michael Riffle, Jean-Philippe Vert, W...
STACS
1999
Springer
13 years 11 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
BMCBI
2010
110views more  BMCBI 2010»
13 years 7 months ago
Discovering local patterns of co - evolution: computational aspects and biological examples
Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
Tamir Tuller, Yifat Felder, Martin Kupiec
JCP
2007
121views more  JCP 2007»
13 years 7 months ago
Learning by Discrimination: A Constructive Incremental Approach
Abstract— This paper presents i-AA1 , a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1 , learning consists of ...
Christophe G. Giraud-Carrier, Tony R. Martinez