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IJCAI
2007
13 years 9 months ago
Explanation-Based Feature Construction
Choosing good features to represent objects can be crucial to the success of supervised machine learning algorithms. Good high-level features are those that concentrate informatio...
Shiau Hong Lim, Li-Lun Wang, Gerald DeJong
IJCAI
2007
13 years 9 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
NIPS
2008
13 years 9 months ago
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Guangzhi Cao, Charles A. Bouman
NIPS
2007
13 years 9 months ago
Fast and Scalable Training of Semi-Supervised CRFs with Application to Activity Recognition
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
Maryam Mahdaviani, Tanzeem Choudhury
PDPTA
2007
13 years 9 months ago
Python-based Distributed Programming with Trickle
Abstract Trickle is a an extension to the Python programming language that provides explicit but simple mechanisms to write distributed scripts and programs. Trickle links together...
Gregory Benson, Alexey Fedosov