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JMLR
2012
13 years 9 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
JMLR
2012
13 years 9 months ago
Multi Kernel Learning with Online-Batch Optimization
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
Francesco Orabona, Jie Luo, Barbara Caputo
171
Voted
ICML
2009
IEEE
16 years 7 months ago
Learning structural SVMs with latent variables
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...
Chun-Nam John Yu, Thorsten Joachims
ICML
1996
IEEE
16 years 7 months ago
Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement Learning
Research in reinforcementlearning (RL)has thus far concentrated on two optimality criteria: the discounted framework, which has been very well-studied, and the averagereward frame...
Sridhar Mahadevan
CHI
2003
ACM
16 years 7 months ago
Kana no senshi (kana warrior): a new interface for learning Japanese characters
This paper presents the design and testing of Kana Warrior, a new interface for basic Japanese character recognition based on a game-style user interface. Kana Warrior is a game d...
Kristen Stubbs