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» Randomized Algorithms and Complexity Theory
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KDD
1998
ACM
120views Data Mining» more  KDD 1998»
15 years 11 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 10 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 8 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 8 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
16 years 20 days 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