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» A Framework for Exploring Optimization Properties
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PG
1999
IEEE
14 years 1 months ago
Mesh Approximation Using a Volume-Based Metric
In this paper we introduce a mesh approximation method that uses a volume-based metric. After a geometric simplification, we minimize the volume between the simplified mesh and th...
Pierre Alliez, Nathalie Laurent, Henri Sanson, Fra...
GECCO
2006
Springer
165views Optimization» more  GECCO 2006»
14 years 12 days ago
Comparing mathematical models on the problem of network inference
In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different mathemat...
Christian Spieth, Nadine Hassis, Felix Streichert
TIP
2002
98views more  TIP 2002»
13 years 8 months ago
Joint-MAP Bayesian tomographic reconstruction with a gamma-mixture prior
We address the problem of Bayesian image reconstruction with a prior that captures the notion of a clustered intensity histogram. The problem is formulated in the framework of a j...
Ing-Tsung Hsiao, Anand Rangarajan, Gene Gindi
AAAI
2011
12 years 8 months ago
Coordinated Multi-Agent Reinforcement Learning in Networked Distributed POMDPs
In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND...
Chongjie Zhang, Victor R. Lesser
JMLR
2012
11 years 11 months ago
Marginal Regression For Multitask Learning
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
Mladen Kolar, Han Liu