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ICML
2008
IEEE
16 years 4 months ago
Democratic approximation of lexicographic preference models
Previous algorithms for learning lexicographic preference models (LPMs) produce a "best guess" LPM that is consistent with the observations. Our approach is more democra...
Fusun Yaman, Thomas J. Walsh, Michael L. Littman, ...
ICAPR
2009
Springer
15 years 10 months ago
Hierarchical Local Maps for Robust Approximate Nearest Neighbor Computation
In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserv...
Pratyush Bhatt, Anoop M. Namboodiri
ICDM
2007
IEEE
124views Data Mining» more  ICDM 2007»
15 years 10 months ago
Community Learning by Graph Approximation
Learning communities from a graph is an important problem in many domains. Different types of communities can be generalized as link-pattern based communities. In this paper, we p...
Bo Long, Xiaoyun Xu, Zhongfei (Mark) Zhang, Philip...
STACS
2005
Springer
15 years 9 months ago
Worst-Case and Average-Case Approximations by Simple Randomized Search Heuristics
Abstract. In recent years, probabilistic analyses of algorithms have received increasing attention. Despite results on the average-case complexity and smoothed complexity of exact ...
Carsten Witt
ATAL
2005
Springer
15 years 9 months ago
A decentralized bargaining protocol on dependent continuous multi-issue for approximate pareto optimal outcomes
Negotiation techniques have been demonstrated to be effective in solving complex multi-objective problems. When the optimization process operates on continuous variables, it can b...
Nicola Gatti, Francesco Amigoni