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» Approximation Methods for Supervised Learning
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KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 10 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
CVPR
2008
IEEE
15 years 10 hour ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele
ICML
2009
IEEE
14 years 10 months ago
Constraint relaxation in approximate linear programs
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Marek Petrik, Shlomo Zilberstein
AAAI
2006
13 years 11 months ago
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Shimon Whiteson, Peter Stone
MLMI
2007
Springer
14 years 4 months ago
Automatic Annotation of Dialogue Structure from Simple User Interaction
Abstract. In [1], we presented a method for automatic detection of action items from natural conversation. This method relies on supervised classification techniques that are trai...
Matthew Purver, John Niekrasz, Patrick Ehlen