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» On Aggregating Teams of Learning Machines
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ML
2008
ACM
248views Machine Learning» more  ML 2008»
14 years 9 months ago
Feature selection via sensitivity analysis of SVM probabilistic outputs
Feature selection is an important aspect of solving data-mining and machine-learning problems. This paper proposes a feature-selection method for the Support Vector Machine (SVM) l...
Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar ...
ICDCS
2009
IEEE
15 years 7 months ago
CLIQUE: Role-Free Clustering with Q-Learning for Wireless Sensor Networks
Clustering and aggregation inherently increase wireless sensor network (WSN) lifetime by collecting information within a cluster at a cluster head, reducing the amount of data thr...
Anna Förster, Amy L. Murphy
KDD
1998
ACM
113views Data Mining» more  KDD 1998»
15 years 2 months ago
Targeting Business Users with Decision Table Classifiers
Business users and analysts commonly use spreadsheets and 2D plots to analyze and understand their data. On-line Analytical Processing (OLAP) provides these users with added flexi...
Ron Kohavi, Dan Sommerfield
EMNLP
2011
13 years 9 months ago
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...
SIGMOD
2007
ACM
125views Database» more  SIGMOD 2007»
15 years 10 months ago
Optimizing mpf queries: decision support and probabilistic inference
Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
Héctor Corrada Bravo, Raghu Ramakrishnan