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» Learning to rank from Bayesian decision inference
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ICML
2007
IEEE
14 years 6 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
AAAI
2011
12 years 5 months ago
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
Marion Neumann, Babak Ahmadi, Kristian Kersting
IFIP12
2008
13 years 6 months ago
Bayesian Networks Optimization Based on Induction Learning Techniques
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...
IPPS
2007
IEEE
13 years 11 months ago
Protein Secondary Structure Prediction using Bayesian Inference method on Decision fusion algorithms
Prediction of protein secondary structure (alpha-helix, beta-sheet, coil) from primary sequence of amino acids is a very challenging task, and the problem has been approached from...
Somasheker Akkaladevi, Ajay K. Katangur
ICML
2001
IEEE
14 years 6 months ago
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
Bianca Zadrozny, Charles Elkan