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SAGA
2009
Springer
15 years 4 months ago
Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
Boris Defourny, Damien Ernst, Louis Wehenkel
NIPS
2007
14 years 11 months ago
A Spectral Regularization Framework for Multi-Task Structure Learning
Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
CVPR
2009
IEEE
16 years 4 months ago
Learning from Ambiguously Labeled Images
In many image and video collections, we have access only to partially labeled data. For example, personal photo collections often contain several faces per image and a caption t...
Benjamin Sapp, Benjamin Taskar, Chris Jordan, Timo...
ICML
2008
IEEE
15 years 10 months ago
No-regret learning in convex games
Quite a bit is known about minimizing different kinds of regret in experts problems, and how these regret types relate to types of equilibria in the multiagent setting of repeated...
Geoffrey J. Gordon, Amy R. Greenwald, Casey Marks
ICML
2003
IEEE
15 years 10 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty