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» Spectral Algorithms for Supervised Learning
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ICDM
2006
IEEE
100views Data Mining» more  ICDM 2006»
15 years 3 months ago
Meta Clustering
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...
CGO
2010
IEEE
15 years 2 months ago
Taming hardware event samples for FDO compilation
Feedback-directed optimization (FDO) is effective in improving application runtime performance, but has not been widely adopted due to the tedious dual-compilation model, the dif...
Dehao Chen, Neil Vachharajani, Robert Hundt, Shih-...
RSS
2007
145views Robotics» more  RSS 2007»
14 years 11 months ago
Semantic Modeling of Places using Objects
— While robot mapping has seen massive strides , higher level abstractions in map representation are still not widespread. Maps containing semantic concepts such as objects and l...
Ananth Ranganathan, Frank Dellaert
CIKM
2011
Springer
13 years 9 months ago
Towards feature selection in network
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Quanquan Gu, Jiawei Han
IUI
2010
ACM
15 years 4 months ago
From documents to tasks: deriving user tasks from document usage patterns
A typical knowledge worker is involved in multiple tasks and switches frequently between them every work day. These frequent switches become expensive because each task switch req...
Oliver Brdiczka