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» Learning Approximate Consistencies
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RECOMB
2007
Springer
16 years 7 months ago
Minimizing and Learning Energy Functions for Side-Chain Prediction
Abstract. Side-chain prediction is an important subproblem of the general protein folding problem. Despite much progress in side-chain prediction, performance is far from satisfact...
Chen Yanover, Ora Schueler-Furman, Yair Weiss
NIPS
1996
15 years 8 months ago
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Scott Davies
ICGI
2004
Springer
16 years 11 days ago
Learning Stochastic Finite Automata
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We report here a number of results concerning the learnability of th...
Colin de la Higuera, José Oncina
CORR
2010
Springer
141views Education» more  CORR 2010»
15 years 5 months ago
Learning Functions of Few Arbitrary Linear Parameters in High Dimensions
Let us assume that f is a continuous function defined on the unit ball of Rd , of the form f(x) = g(Ax), where A is a k×d matrix and g is a function of k variables for k ≪ d. ...
Massimo Fornasier, Karin Schnass, Jan Vybír...
ECCV
2006
Springer
16 years 9 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...