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PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
15 years 4 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
DATE
2008
IEEE
204views Hardware» more  DATE 2008»
15 years 4 months ago
Deep Submicron Interconnect Timing Model with Quadratic Random Variable Analysis
Shrinking feature sizes and process variations are of increasing concern in modern technology. It is urgent that we develop statistical interconnect timing models which are harmon...
Jun-Kuei Zeng, Chung-Ping Chen
ICDM
2008
IEEE
224views Data Mining» more  ICDM 2008»
15 years 4 months ago
A Non-parametric Approach to Pair-Wise Dynamic Topic Correlation Detection
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
Yang Song, Lu Zhang 0007, C. Lee Giles
ICRA
2008
IEEE
149views Robotics» more  ICRA 2008»
15 years 4 months ago
Monocular range sensing: A non-parametric learning approach
Abstract— Mobile robots rely on the ability to sense the geometry of their local environment in order to avoid obstacles or to explore the surroundings. For this task, dedicated ...
Christian Plagemann, Felix Endres, Juergen Michael...
IJCNN
2008
IEEE
15 years 4 months ago
A neural network approach to ordinal regression
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
Jianlin Cheng, Zheng Wang, Gianluca Pollastri