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» Application Insight Through Performance Modeling
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PADS
2003
ACM
15 years 7 months ago
Maya: a Multi-Paradigm Network Modeling Framework
This paper presents Maya, a multi-paradigm, scalable and extensible network modeling framework for emulating distributed applications. A novel three-tier architecture is proposed ...
Junlan Zhou, Zhengrong Ji, Mineo Takai, Rajive Bag...
IJCAI
2003
15 years 3 months ago
Gaussian Process Models of Spatial Aggregation Algorithms
Multi-level spatial aggregates are important for data mining in a variety of scientific and engineering applications, from analysis of weather data (aggregating temperature and p...
Naren Ramakrishnan, Christopher Bailey-Kellogg
SENSYS
2010
ACM
14 years 11 months ago
Adaptive decentralized control of underwater sensor networks for modeling underwater phenomena
Understanding the dynamics of bodies of water and their impact on the global environment requires sensing information over the full volume of water. We develop a gradientbased dec...
Carrick Detweiler, Marek Doniec, Mingshun Jiang, M...
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
16 years 2 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
WSC
2008
15 years 4 months ago
Data Farming around the world overview
Data Farming combines the rapid prototyping capability inherent in certain simulation models with the exploratory power of high performance computing to rapidly generate insight i...
Gary E. Horne, Klaus-Peter Schwierz