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CHI
2010
ACM
15 years 4 months ago
Examining multiple potential models in end-user interactive concept learning
End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
ECAI
2004
Springer
15 years 3 months ago
Towards Efficient Learning of Neural Network Ensembles from Arbitrarily Large Datasets
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Kang Peng, Zoran Obradovic, Slobodan Vucetic
ML
2002
ACM
143views Machine Learning» more  ML 2002»
14 years 9 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
JMLR
2010
88views more  JMLR 2010»
14 years 4 months ago
Unsupervised Aggregation for Classification Problems with Large Numbers of Categories
Classification problems with a very large or unbounded set of output categories are common in many areas such as natural language and image processing. In order to improve accurac...
Ivan Titov, Alexandre Klementiev, Kevin Small, Dan...
MONET
2002
85views more  MONET 2002»
14 years 9 months ago
Bringing the Web to the Network Edge: Large Caches and Satellite Distribution
In this paper we discuss the performance of a document distribution model that interconnects Web caches through a satellite channel. During recent years Web caching has emerged as...
Pablo Rodriguez, Ernst Biersack