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» Distance Approximating Trees: Complexity and Algorithms
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SIGMOD
2011
ACM
206views Database» more  SIGMOD 2011»
12 years 10 months ago
Sampling based algorithms for quantile computation in sensor networks
We study the problem of computing approximate quantiles in large-scale sensor networks communication-efficiently, a problem previously studied by Greenwald and Khana [12] and Shri...
Zengfeng Huang, Lu Wang, Ke Yi, Yunhao Liu
IPPS
2003
IEEE
14 years 21 days ago
Channel Assignment on Strongly-Simplicial Graphs
Given a vector ( 1 2 ::: t) of non increasing positive integers, and an undirected graph G = (V E), an L( 1 2 ::: t)-coloring of G is a function f from the vertex set V to a set o...
Alan A. Bertossi, Maria Cristina Pinotti, Romeo Ri...
ICML
2005
IEEE
14 years 8 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
JAIR
2008
120views more  JAIR 2008»
13 years 7 months ago
Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach
Machine learning techniques are gaining prevalence in the production of a wide range of classifiers for complex real-world applications with nonuniform testing and misclassificati...
Saher Esmeir, Shaul Markovitch
ICALP
2004
Springer
14 years 24 days ago
The Black-Box Complexity of Nearest Neighbor Search
We define a natural notion of efficiency for approximate nearest-neighbor (ANN) search in general n-point metric spaces, namely the existence of a randomized algorithm which answ...
Robert Krauthgamer, James R. Lee