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HPCC
2007
Springer
15 years 1 months ago
Energy-Aware Online Algorithm to Satisfy Sampling Rates with Guaranteed Probability for Sensor Applications
Abstract. Energy consumption is a major factor that limits the performance of sensor applications. Sensor nodes have varying sampling rates since they face continuously changing en...
Meikang Qiu, Edwin Hsing-Mean Sha
DCC
2010
IEEE
14 years 8 months ago
Neural Markovian Predictive Compression: An Algorithm for Online Lossless Data Compression
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
Erez Shermer, Mireille Avigal, Dana Shapira
GECCO
2009
Springer
153views Optimization» more  GECCO 2009»
15 years 2 months ago
Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed
In this paper, we benchmark the (1+1) Evolution Strategy (ES) with one-fifth success rule which is one of the first and simplest adaptive search algorithms proposed for optimiza...
Anne Auger
ML
1998
ACM
102views Machine Learning» more  ML 1998»
14 years 9 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha
KDD
2003
ACM
194views Data Mining» more  KDD 2003»
15 years 10 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee