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JMLR
2008
151views more  JMLR 2008»
15 years 6 months ago
Learning to Combine Motor Primitives Via Greedy Additive Regression
The computational complexities arising in motor control can be ameliorated through the use of a library of motor synergies. We present a new model, referred to as the Greedy Addit...
Manu Chhabra, Robert A. Jacobs
NECO
2007
258views more  NECO 2007»
15 years 6 months ago
Reinforcement Learning Through Modulation of Spike-Timing-Dependent Synaptic Plasticity
The persistent modification of synaptic efficacy as a function of the relative timing of pre- and postsynaptic spikes is a phenomenon known as spiketiming-dependent plasticity (...
Razvan V. Florian
JMLR
2010
148views more  JMLR 2010»
15 years 1 months ago
A Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
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
PATAT
2004
Springer
130views Education» more  PATAT 2004»
15 years 12 months ago
Learning User Preferences in Distributed Calendar Scheduling
Abstract. Within the field of software agents, there has been increasing interest in automating the process of calendar scheduling in recent years. Calendar (or meeting) schedulin...
Jean Oh, Stephen F. Smith