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» Randomized Algorithms and Complexity Theory
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KDD
1998
ACM
120views Data Mining» more  KDD 1998»
15 years 7 months ago
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
Tim Oates, David Jensen
STACS
1993
Springer
15 years 7 months ago
The Complexity of Logic-Based Abduction
Abduction is an important form of nonmonotonic reasoning allowing one to find explanations for certain symptoms or manifestations. When the application domain is described by a l...
Thomas Eiter, Georg Gottlob
ATAL
2008
Springer
15 years 5 months ago
Complexity of terminating preference elicitation
Complexity theory is a useful tool to study computational issues surrounding the elicitation of preferences, as well as the strategic manipulation of elections aggregating togethe...
Toby Walsh
NAACL
2007
15 years 4 months ago
Worst-Case Synchronous Grammar Rules
We relate the problem of finding the best application of a Synchronous ContextFree Grammar (SCFG) rule during parsing to a Markov Random Field. This representation allows us to u...
Daniel Gildea, Daniel Stefankovic
ACMSE
2006
ACM
15 years 9 months ago
Discovering communities in complex networks
We propose an efficient and novel approach for discovering communities in real-world random networks. Communities are formed by subsets of nodes in a graph, which are closely rela...
Hemant Balakrishnan, Narsingh Deo