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151
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STOC
2012
ACM
217views Algorithms» more  STOC 2012»
13 years 6 months ago
Tight lower bounds for the online labeling problem
We consider the file maintenance problem (also called the online labeling problem) in which n integer items from the set {1, . . . , r} are to be stored in an array of size m ≥...
Jan Bulánek, Michal Koucký, Michael ...
133
Voted
FOCS
2005
IEEE
15 years 9 months ago
Lower Bounds for the Noisy Broadcast Problem
We prove the first non-trivial (super linear) lower bound in the noisy broadcast model, defined by El Gamal in [6]. In this model there are n + 1 processors P0, P1, . . . , Pn, ...
Navin Goyal, Guy Kindler, Michael E. Saks
141
Voted
ICML
2005
IEEE
16 years 4 months ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III
118
Voted
ICASSP
2009
IEEE
15 years 10 months ago
Map approach to learning sparse Gaussian Markov networks
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
Narges Bani Asadi, Irina Rish, Katya Scheinberg, D...
122
Voted
LION
2009
Springer
129views Optimization» more  LION 2009»
15 years 10 months ago
Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...