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AGENTS
1999
Springer
14 years 1 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 9 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
ATAL
2008
Springer
13 years 11 months ago
A statistical relational model for trust learning
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Achim Rettinger, Matthias Nickles, Volker Tresp
TSP
2008
167views more  TSP 2008»
13 years 7 months ago
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...
KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 9 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu