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» Evaluating algorithms that learn from data streams
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139
Voted
ICDE
2009
IEEE
179views Database» more  ICDE 2009»
15 years 10 months ago
Self-Tuning, Bandwidth-Aware Monitoring for Dynamic Data Streams
— We present SMART, a self-tuning, bandwidth-aware monitoring system that maximizes result precision of continuous aggregate queries over dynamic data streams. While prior approa...
Navendu Jain, Praveen Yalagandula, Michael Dahlin,...
MM
2004
ACM
155views Multimedia» more  MM 2004»
15 years 9 months ago
Disruption-tolerant content-aware video streaming
Communication between a pair of nodes in the network may get disrupted due to failures of links/nodes resulting in zero effective bandwidth between them during the recovery perio...
Tiecheng Liu, Srihari Nelakuditi
KDD
1995
ACM
248views Data Mining» more  KDD 1995»
15 years 7 months ago
Data Mining for Loan Evaluation at ABN AMRO: A Case Study
Wedescribe a case study in data miningfor personal loan evaluation, performed at the ABNAMRObank in the Netherlands. Historical data of clients and their pay-backbehaviourare used...
A. J. Feelders, A. J. F. le Loux, J. W. van't Zand
101
Voted
CVPR
2005
IEEE
16 years 6 months ago
Robust Boosting for Learning from Few Examples
We present and analyze a novel regularization technique based on enhancing our dataset with corrupted copies of our original data. The motivation is that since the learning algori...
Lior Wolf, Ian Martin
186
Voted
STAIRS
2008
175views Education» more  STAIRS 2008»
15 years 5 months ago
Learning Process Behavior with EDY: an Experimental Analysis
This paper presents an extensive evaluation, on artificial datasets, of EDY, an unsupervised algorithm for automatically synthesizing a Structured Hidden Markov Model (S-HMM) from ...
Ugo Galassi