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» Learning Monotonic Linear Functions
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ICML
2003
IEEE
14 years 8 months ago
Learning Distance Functions using Equivalence Relations
We address the problem of learning distance metrics using side-information in the form of groups of "similar" points. We propose to use the RCA algorithm, which is a sim...
Aharon Bar-Hillel, Tomer Hertz, Noam Shental, Daph...
ECSQARU
2007
Springer
14 years 1 months ago
On Decision Support Under Risk by the WOWA Optimization
Abstract. The problem of averaging outcomes under several scenarios to form overall objective functions is of considerable importance in decision support under uncertainty. The fuz...
Wlodzimierz Ogryczak, Tomasz Sliwinski
AAAI
1997
13 years 9 months ago
Worst-Case Absolute Loss Bounds for Linear Learning Algorithms
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
Tom Bylander
ESANN
2004
13 years 9 months ago
High-accuracy value-function approximation with neural networks applied to the acrobot
Several reinforcement-learning techniques have already been applied to the Acrobot control problem, using linear function approximators to estimate the value function. In this pape...
Rémi Coulom
FOCS
2008
IEEE
14 years 2 months ago
Submodular Approximation: Sampling-based Algorithms and Lower Bounds
We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems i...
Zoya Svitkina, Lisa Fleischer