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» Functional Programming in Sublinear Space
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AI
2002
Springer
13 years 9 months ago
Improving heuristic mini-max search by supervised learning
This article surveys three techniques for enhancing heuristic game-tree search pioneered in the author's Othello program Logistello, which dominated the computer Othello scen...
Michael Buro
ICCAD
1997
IEEE
108views Hardware» more  ICCAD 1997»
14 years 2 months ago
Negative thinking by incremental problem solving: application to unate covering
We introduce a new technique to solve exactly a discrete optimization problem, based on the paradigm of “negative” thinking. The motivation is that when searching the space of...
Evguenii I. Goldberg, Luca P. Carloni, Tiziano Vil...
WABI
2010
Springer
128views Bioinformatics» more  WABI 2010»
13 years 8 months ago
Sparsification of RNA Structure Prediction Including Pseudoknots
Background: Although many RNA molecules contain pseudoknots, computational prediction of pseudoknotted RNA structure is still in its infancy due to high running time and space con...
Mathias Möhl, Raheleh Salari, Sebastian Will,...
JMLR
2012
12 years 8 days ago
Random Search for Hyper-Parameter Optimization
Grid search and manual search are the most widely used strategies for hyper-parameter optimization. This paper shows empirically and theoretically that randomly chosen trials are ...
James Bergstra, Yoshua Bengio
NIPS
2007
13 years 11 months ago
A New View of Automatic Relevance Determination
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
David P. Wipf, Srikantan S. Nagarajan