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ICML
2006
IEEE
16 years 7 months ago
Learning algorithms for online principal-agent problems (and selling goods online)
In a principal-agent problem, a principal seeks to motivate an agent to take a certain action beneficial to the principal, while spending as little as possible on the reward. This...
Vincent Conitzer, Nikesh Garera
ICML
2006
IEEE
16 years 7 months ago
An analytic solution to discrete Bayesian reinforcement learning
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
ICML
2006
IEEE
16 years 7 months ago
Iterative RELIEF for feature weighting
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
Yijun Sun, Jian Li
ICML
2005
IEEE
16 years 7 months ago
Multi-way distributional clustering via pairwise interactions
We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...
Ron Bekkerman, Ran El-Yaniv, Andrew McCallum
ICML
2005
IEEE
16 years 7 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
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