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JMLR
2012
11 years 10 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey
NIPS
1993
13 years 9 months ago
Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming
Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have ...
Christopher G. Atkeson
ISCIS
2003
Springer
14 years 23 days ago
A New Continuous Action-Set Learning Automaton for Function Optimization
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorr...
Hamid Beigy, Mohammad Reza Meybodi
JMLR
2012
11 years 10 months ago
Lifted coordinate descent for learning with trace-norm regularization
We consider the minimization of a smooth loss with trace-norm regularization, which is a natural objective in multi-class and multitask learning. Even though the problem is convex...
Miroslav Dudík, Zaïd Harchaoui, J&eacu...
JMLR
2012
11 years 10 months ago
Beyond Logarithmic Bounds in Online Learning
We prove logarithmic regret bounds that depend on the loss L∗ T of the competitor rather than on the number T of time steps. In the general online convex optimization setting, o...
Francesco Orabona, Nicolò Cesa-Bianchi, Cla...