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ECAI
2010
Springer

339views Artificial Intelligence» more ECAI 2010»

Bayesian Monte Carlo for the Global Optimization of Expensive Functions

14 years 4 months ago

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In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...

Perry Groot, Adriana Birlutiu, Tom Heskes

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Id	Views	Title	Status

1	339	Bayesian Monte Carlo for the Global Optimization of Expensive Functions	claim
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64	212	ISAC - Instance-Specific Algorithm Configuration	claim
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66	211	Case-Based Multiagent Reinforcement Learning: Cases as Heuristics for Selection of Actions	claim
67	211	Computation in Extended Argumentation Frameworks	claim
68	211	Restarts and Nogood Recording in Qualitative Constraint-based Reasoning	claim
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70	211	Improving the Global Constraint SoftPrec	claim
71	210	Using Bayesian Networks in an Industrial Setting: Making Printing Systems Adaptive	claim
72	210	Relative-Order Abstractions for the Pancake Problem	claim
73	210	The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks	claim
74	209	A Unified Framework for Non-standard Reasoning Services in Description Logics	claim
75	209	Majority Merging: from Boolean Spaces to Affine Spaces	claim
76	209	Kernel Methods for Revealed Preference Analysis	claim
77	208	Detecting Ironic Intent in Creative Comparisons	claim
78	208	On the Verification of Very Expressive Temporal Properties of Non-terminating Golog Programs	claim
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102	181	LP Solvable Models for Multiagent Fair Allocation Problems	claim
103	180	Joint handling of Rational and Behavioral reactions in Assistant Conversational Agents	claim
104	180	Integrating Probability Constraints into Bayesian Nets	claim
105	176	Strengthening Landmark Heuristics via Hitting Sets	claim
106	174	Modelling Multilateral Negotiation in Linear Logic	claim

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