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» Learning How to Propagate Using Random Probing
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NIPS
1996
13 years 9 months ago
Continuous Sigmoidal Belief Networks Trained using Slice Sampling
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...
Brendan J. Frey
ICML
2008
IEEE
14 years 8 months ago
Apprenticeship learning using linear programming
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in tha...
Umar Syed, Michael H. Bowling, Robert E. Schapire
JMLR
2010
149views more  JMLR 2010»
13 years 2 months ago
Coherent Inference on Optimal Play in Game Trees
Round-based games are an instance of discrete planning problems. Some of the best contemporary game tree search algorithms use random roll-outs as data. Relying on a good policy, ...
Philipp Hennig, David H. Stern, Thore Graepel
ICDM
2003
IEEE
142views Data Mining» more  ICDM 2003»
14 years 1 months ago
Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques
Collaborative Filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. E-commerce sites use CF systems to suggest products to customers base...
Huseyin Polat, Wenliang Du
SIGMOD
2009
ACM
189views Database» more  SIGMOD 2009»
14 years 8 months ago
Query segmentation using conditional random fields
A growing mount of available text data are being stored in relational databases, giving rise to an increasing need for the RDBMSs to support effective text retrieval. In this pape...
Xiaohui Yu, Huxia Shi