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» Variational methods for Reinforcement Learning
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ATAL
2006
Springer
13 years 11 months ago
Efficient agents for cliff-edge environments with a large set of decision options
This paper proposes an efficient agent for competing in Cliff Edge (CE) environments, such as sealed-bid auctions, dynamic pricing and the ultimatum game. The agent competes in on...
Ron Katz, Sarit Kraus
KDD
2010
ACM
289views Data Mining» more  KDD 2010»
13 years 5 months ago
Exploitation and exploration in a performance based contextual advertising system
The dynamic marketplace in online advertising calls for ranking systems that are optimized to consistently promote and capitalize better performing ads. The streaming nature of on...
Wei Li 0010, Xuerui Wang, Ruofei Zhang, Ying Cui, ...
ICML
2009
IEEE
14 years 8 months ago
MedLDA: maximum margin supervised topic models for regression and classification
Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
Jun Zhu, Amr Ahmed, Eric P. Xing
ICML
2007
IEEE
14 years 8 months ago
A permutation-augmented sampler for DP mixture models
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Percy Liang, Michael I. Jordan, Benjamin Taskar
ICML
2010
IEEE
13 years 8 months ago
Gaussian Process Change Point Models
We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to loca...
Yunus Saatci, Ryan Turner, Carl Edward Rasmussen