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AAAI
2006
15 years 1 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
FORMATS
2006
Springer
15 years 3 months ago
Extended Directed Search for Probabilistic Timed Reachability
Current numerical model checkers for stochastic systems can efficiently analyse stochastic models. However, the fact that they are unable to provide debugging information constrain...
Husain Aljazzar, Stefan Leue
ICML
2009
IEEE
16 years 16 days ago
Online dictionary learning for sparse coding
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
ICML
2000
IEEE
16 years 16 days ago
Reinforcement Learning in POMDP's via Direct Gradient Ascent
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
Jonathan Baxter, Peter L. Bartlett
INFOCOM
2010
IEEE
14 years 10 months ago
Retiring Replicants: Congestion Control for Intermittently-Connected Networks
Abstract—The widespread availability of mobile wireless devices offers growing opportunities for the formation of temporary networks with only intermittent connectivity. These in...
Nathanael Thompson, Samuel C. Nelson, Mehedi Bakht...