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» Approximation Algorithms for the Max-coloring Problem
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AAAI
2011
12 years 7 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
ICDE
1998
IEEE
270views Database» more  ICDE 1998»
14 years 9 months ago
Cyclic Association Rules
We study the problem of discovering association rules that display regular cyclic variation over time. For example, if we compute association rules over monthly sales data, we may...
Banu Özden, Sridhar Ramaswamy, Abraham Silber...
GECCO
2005
Springer
186views Optimization» more  GECCO 2005»
14 years 1 months ago
Subproblem optimization by gene correlation with singular value decomposition
Several ways of using singular value decomposition (SVD), a linear algebra technique typically used for information retrieval, to decompose problems into subproblems are investiga...
Jacob G. Martin
STOC
2007
ACM
100views Algorithms» more  STOC 2007»
14 years 8 months ago
Reordering buffers for general metric spaces
In the reordering buffer problem, we are given an input sequence of requests for service each of which corresponds to a point in a metric space. The cost of serving the requests h...
Matthias Englert, Harald Räcke, Matthias West...
TACAS
2007
Springer
165views Algorithms» more  TACAS 2007»
14 years 1 months ago
Multi-objective Model Checking of Markov Decision Processes
We study and provide efficient algorithms for multi-objective model checking problems for Markov Decision Processes (MDPs). Given an MDP, M, and given multiple linear-time (ω-regu...
Kousha Etessami, Marta Z. Kwiatkowska, Moshe Y. Va...