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COLT
2010
Springer
13 years 8 months ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer
ICONIP
2007
13 years 11 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor
NIPS
2004
13 years 11 months ago
A Machine Learning Approach to Conjoint Analysis
Choice-based conjoint analysis builds models of consumer preferences over products with answers gathered in questionnaires. Our main goal is to bring tools from the machine learni...
Olivier Chapelle, Zaïd Harchaoui
ICML
2005
IEEE
14 years 11 months ago
New approaches to support vector ordinal regression
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
Wei Chu, S. Sathiya Keerthi
ICML
1996
IEEE
14 years 2 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos