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» Learning to learn with the informative vector machine
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SIGIR
2011
ACM
14 years 9 months ago
Fast context-aware recommendations with factorization machines
The situation in which a choice is made is an important information for recommender systems. Context-aware recommenders take this information into account to make predictions. So ...
Steffen Rendle, Zeno Gantner, Christoph Freudentha...
AIIA
2005
Springer
16 years 11 days ago
Handling Continuous-Valued Attributes in Incremental First-Order Rules Learning
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
ML
1998
ACM
220views Machine Learning» more  ML 1998»
15 years 6 months ago
Learning to Improve Coordinated Actions in Cooperative Distributed Problem-Solving Environments
Abstract. Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all...
Toshiharu Sugawara, Victor R. Lesser
ALENEX
2008
133views Algorithms» more  ALENEX 2008»
15 years 8 months ago
Comparing Online Learning Algorithms to Stochastic Approaches for the Multi-Period Newsvendor Problem
The multi-period newsvendor problem describes the dilemma of a newspaper salesman--how many paper should he purchase each day to resell, when he doesn't know the demand? We d...
Shawn O'Neil, Amitabh Chaudhary
ICML
2009
IEEE
16 years 7 months ago
Learning from measurements in exponential families
Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...
Percy Liang, Michael I. Jordan, Dan Klein