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» Ensemble Methods in Machine Learning
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ICML
2008
IEEE
16 years 5 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang
ICML
2006
IEEE
16 years 5 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
156
Voted
ICML
2005
IEEE
16 years 5 months ago
Q-learning of sequential attention for visual object recognition from informative local descriptors
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Lucas Paletta, Gerald Fritz, Christin Seifert
ICML
1999
IEEE
16 years 5 months ago
Making Better Use of Global Discretization
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
Eibe Frank, Ian H. Witten
140
Voted
ECTEL
2009
Springer
15 years 11 months ago
Assessing Collaboration Quality in Synchronous CSCL Problem-Solving Activities: Adaptation and Empirical Evaluation of a Rating
The work described is part of an ongoing interdisciplinary collaboration between two research teams of the University of Patras, Greece and the University of Freiburg, Germany, whi...
Georgios Kahrimanis, Anne Meier, Irene-Angelica Ch...