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127
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CORR
2010
Springer
207views Education» more  CORR 2010»
15 years 2 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
107
Voted
CORR
2010
Springer
156views Education» more  CORR 2010»
15 years 2 months ago
Selling Privacy at Auction
We initiate the study of markets for private data, through the lens of differential privacy. Although the purchase and sale of private data has already begun on a large scale, a t...
Arpita Ghosh, Aaron Roth
109
Voted
TSMC
2008
99views more  TSMC 2008»
15 years 2 months ago
Robust Regularized Kernel Regression
Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual fo...
Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
132
Voted
TVCG
2008
116views more  TVCG 2008»
15 years 2 months ago
On Linear Variational Surface Deformation Methods
This survey reviews the recent advances in linear variational mesh deformation techniques. These methods were developed for editing detailed high-resolution meshes like those produ...
Mario Botsch, Olga Sorkine
103
Voted
CORR
2004
Springer
87views Education» more  CORR 2004»
15 years 2 months ago
Exploring tradeoffs in pleiotropy and redundancy using evolutionary computing
Evolutionary computation algorithms are increasingly being used to solve optimization problems as they have many advantages over traditional optimization algorithms. In this paper...
Matthew J. Berryman, Wei-Li Khoo, Hiep Nguyen, Eri...