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ICML
2008
IEEE
16 years 7 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
ICML
2008
IEEE
16 years 7 months ago
Efficiently solving convex relaxations for MAP estimation
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
M. Pawan Kumar, Philip H. S. Torr
ICML
2006
IEEE
16 years 7 months ago
The support vector decomposition machine
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
Francisco Pereira, Geoffrey J. Gordon
ICML
2006
IEEE
16 years 7 months ago
An analytic solution to discrete Bayesian reinforcement learning
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
ICML
2002
IEEE
16 years 7 months ago
Action Refinement in Reinforcement Learning by Probability Smoothing
In many reinforcement learning applications, the set of possible actions can be partitioned by the programmer into subsets of similar actions. This paper presents a technique for ...
Carles Sierra, Dídac Busquets, Ramon L&oacu...
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