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» Spectral Algorithms for Supervised Learning
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ATAL
2008
Springer
14 years 11 months ago
Efficient multi-agent reinforcement learning through automated supervision
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
COLING
1996
14 years 11 months ago
Unsupervised Discovery of Phonological Categories through Supervised Learning of Morphological Rules
We describe a case study in tit(', application of symbolic machinc learning techniques for the discow;ry of linguistic rules and categories. A supervised rule induction algor...
Walter Daelemans, Peter Berck, Steven Gillis
ICML
2003
IEEE
15 years 10 months ago
Transductive Learning via Spectral Graph Partitioning
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...
Thorsten Joachims
ICPR
2010
IEEE
15 years 4 months ago
Semi-Supervised Distance Metric Learning by Quadratic Programming
This paper introduces a semi-supervised distance metric learning algorithm which uses pair-wise equivalence (similarity and dissimilarity) constraints to improve the original dist...
Hakan Cevikalp
ACL
2011
14 years 1 months ago
Semi-supervised latent variable models for sentence-level sentiment analysis
We derive two variants of a semi-supervised model for fine-grained sentiment analysis. Both models leverage abundant natural supervision in the form of review ratings, as well as...
Oscar Täckström, Ryan T. McDonald