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ICANN
2009
Springer
15 years 5 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
JMLR
2010
107views more  JMLR 2010»
14 years 8 months ago
Learning Instance-Specific Predictive Models
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Shyam Visweswaran, Gregory F. Cooper
143
Voted
AAAI
2012
13 years 4 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
ACL
2012
13 years 4 months ago
Joint Feature Selection in Distributed Stochastic Learning for Large-Scale Discriminative Training in SMT
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...
Patrick Simianer, Stefan Riezler, Chris Dyer
KDD
2007
ACM
211views Data Mining» more  KDD 2007»
16 years 2 months ago
Enhanced max margin learning on multimodal data mining in a multimedia database
The problem of multimodal data mining in a multimedia database can be addressed as a structured prediction problem where we learn the mapping from an input to the structured and i...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...