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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 1 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
ICCV
2007
IEEE
16 years 2 months ago
The Joint Manifold Model for Semi-supervised Multi-valued Regression
Many computer vision tasks may be expressed as the problem of learning a mapping between image space and a parameter space. For example, in human body pose estimation, recent rese...
Ramanan Navaratnam, Andrew W. Fitzgibbon, Roberto ...
121
Voted
CORR
2010
Springer
136views Education» more  CORR 2010»
14 years 11 months ago
Viewpoints: A high-performance high-dimensional exploratory data analysis tool
Scientific data sets continue to increase in both size and complexity. In the past, dedicated graphics systems at supercomputing centers were required to visualize large data sets,...
Paul R. Gazis, C. Levit, Michael J. Way
123
Voted
ICML
2000
IEEE
16 years 1 months ago
On-line Learning for Humanoid Robot Systems
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Gaurav Tevatia, Jörg Conradt, Sethu Vijayakum...
OSDI
2008
ACM
15 years 3 months ago
DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language
DryadLINQ is a system and a set of language extensions that enable a new programming model for large scale distributed computing. It generalizes previous execution environments su...
Yuan Yu, Michael Isard, Dennis Fetterly, Mihai Bud...