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» Regret Bounds for Prediction Problems
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JMLR
2008
230views more  JMLR 2008»
13 years 9 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
SIGMOD
2007
ACM
165views Database» more  SIGMOD 2007»
14 years 10 months ago
Statistical analysis of sketch estimators
Sketching techniques can provide approximate answers to aggregate queries either for data-streaming or distributed computation. Small space summaries that have linearity propertie...
Florin Rusu, Alin Dobra
ICS
2010
Tsinghua U.
14 years 7 months ago
Cryptography by Cellular Automata or How Fast Can Complexity Emerge in Nature?
Computation in the physical world is restricted by the following spatial locality constraint: In a single unit of time, information can only travel a bounded distance in space. A ...
Benny Applebaum, Yuval Ishai, Eyal Kushilevitz
COLT
2004
Springer
14 years 3 months ago
An Inequality for Nearly Log-Concave Distributions with Applications to Learning
Abstract— We prove that given a nearly log-concave distribution, in any partition of the space to two well separated sets, the measure of the points that do not belong to these s...
Constantine Caramanis, Shie Mannor
ALT
2007
Springer
14 years 1 months ago
Cluster Identification in Nearest-Neighbor Graphs
Abstract. Assume we are given a sample of points from some underlying distribution which contains several distinct clusters. Our goal is to construct a neighborhood graph on the sa...
Markus Maier, Matthias Hein, Ulrike von Luxburg