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COLT
2008
Springer
15 years 8 months ago
High-Probability Regret Bounds for Bandit Online Linear Optimization
We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ( ...
Peter L. Bartlett, Varsha Dani, Thomas P. Hayes, S...
NIPS
2007
15 years 8 months ago
A Risk Minimization Principle for a Class of Parzen Estimators
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
ICML
2010
IEEE
15 years 7 months ago
Accelerated dual decomposition for MAP inference
Approximate MAP inference in graphical models is an important and challenging problem for many domains including computer vision, computational biology and natural language unders...
Vladimir Jojic, Stephen Gould, Daphne Koller
ICML
2010
IEEE
15 years 7 months ago
Deep networks for robust visual recognition
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
Yichuan Tang, Chris Eliasmith
ICML
2010
IEEE
15 years 7 months ago
Random Spanning Trees and the Prediction of Weighted Graphs
We show that the mistake bound for predicting the nodes of an arbitrary weighted graph is characterized (up to logarithmic factors) by the cutsize of a random spanning tree of the...
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio...