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» Machine-Learning Applications of Algorithmic Randomness
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ICML
2008
IEEE
14 years 10 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye
ALT
2006
Springer
14 years 6 months ago
Risk-Sensitive Online Learning
We consider the problem of online learning in settings in which we want to compete not simply with the rewards of the best expert or stock, but with the best trade-off between rew...
Eyal Even-Dar, Michael J. Kearns, Jennifer Wortman
ICML
2004
IEEE
14 years 2 months ago
Towards tight bounds for rule learning
While there is a lot of empirical evidence showing that traditional rule learning approaches work well in practice, it is nearly impossible to derive analytical results about thei...
Ulrich Rückert, Stefan Kramer
ICML
2004
IEEE
14 years 2 months ago
Online learning of conditionally I.I.D. data
In this work we consider the task of relaxing the i.i.d assumption in online pattern recognition (or classification), aiming to make existing learning algorithms applicable to a ...
Daniil Ryabko
ECML
2006
Springer
14 years 29 days ago
Prioritizing Point-Based POMDP Solvers
Recent scaling up of POMDP solvers towards realistic applications is largely due to point-based methods such as PBVI, Perseus, and HSVI, which quickly converge to an approximate so...
Guy Shani, Ronen I. Brafman, Solomon Eyal Shimony