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» Learning to learn with the informative vector machine
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TCBB
2010
176views more  TCBB 2010»
13 years 4 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
FECS
2010
236views Education» more  FECS 2010»
13 years 3 months ago
Development of a system for teaching CS1 in C/C++ with Lego NXT robots
This paper describes the development of a system for teaching C/C++ using a LegoTM NXT in a CSI college course on introductory programming. The programming of the NXT robot has be...
Amy Delman, Adiba Ishak, Lawrence Goetz, Mikhail K...
SIAMIS
2011
13 years 22 days ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
IWDW
2007
Springer
13 years 12 months ago
Steganalysis Versus Splicing Detection
Aiming at detecting secret information hidden in a given image using steganographic tools, steganalysis has been of interest since the end of 1990’s. In particular, universal ste...
Yun Q. Shi, Chunhua Chen, Guorong Xuan, Wei Su
APPROX
2006
Springer
89views Algorithms» more  APPROX 2006»
13 years 9 months ago
Online Algorithms to Minimize Resource Reallocations and Network Communication
Abstract. In this paper, we consider two new online optimization problems (each with several variants), present similar online algorithms for both, and show that one reduces to the...
Sashka Davis, Jeff Edmonds, Russell Impagliazzo