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ICML
2010
IEEE
15 years 5 months ago
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is ...
Niranjan Srinivas, Andreas Krause, Sham Kakade, Ma...
PKDD
2010
Springer
183views Data Mining» more  PKDD 2010»
15 years 3 months ago
Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes
Abstract. In preference learning, the algorithm observes pairwise relative judgments (preference) between items as training data for learning an ordering of all items. This is an i...
Zhao Xu, Kristian Kersting, Thorsten Joachims
182
Voted
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
15 years 2 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
JMLR
2010
141views more  JMLR 2010»
14 years 11 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
122
Voted
TSP
2010
14 years 11 months ago
Joint nonlinear channel equalization and soft LDPC decoding with Gaussian processes
In this paper, we introduce a new approach for nonlinear equalization based on Gaussian processes for classification (GPC). We propose to measure the performance of this equalizer ...
Pablo M. Olmos, Juan José Murillo-Fuentes, ...