MATH 592 SPRING 2010 TOPICS IN ERGODIC THEORY AND PROBABILITY PROBLEM SET 1 1. Let f : Fnp → C, let V be a subspace of Fnp , and write g = f · 1V . Show that gb(t) = Es∈V ⊥ fb(s + t)

Source URL: www.juliawolf.org

CS264: Beyond Worst-Case Analysis Lecture #9: A Taste Of Compressive Sensing∗ Tim Roughgarden† October 22,

Source URL: theory.stanford.edu

• Algebra
• Mathematics
• Linear algebra
• Matrix
• System of linear equations
• Compressed sensing
• Underdetermined system
• Kernel
• Inner product space
• Linear subspace
• Norm
• Row and column spaces

Cross Language Text Classification via Multi-view Subspace Learning Yuhong Guo and Min Xiao Department of Computer and Information Sciences, Temple University, Philadelphia, PAUSA

Source URL: km.aifb.kit.edu

HANDLING MISSING DATA IN HIGH-DIMENSIONAL SUBSPACE MODELING By Laura Kathryn Balzano A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE

Source URL: sunbeam.ece.wisc.edu

cvpr07-benchmark-final.dvi

Source URL: www.cis.jhu.edu

• Algebra
• Mathematics
• Linear algebra
• Functional analysis
• Random sample consensus
• SRI International
• Image segmentation
• Structure from motion
• Spectral clustering
• Linear subspace
• Motion estimation
• Market segmentation

ON THE SAMPLE COMPLEXITY OF SUBSPACE CLUSTERING WITH MISSING DATA D. Pimentel, R. Nowak L. Balzano University of Wisconsin

Source URL: nowak.ece.wisc.edu

A Note on Boundary Constraints for Linear Variational Surface Design Andrew Nealen TU Berlin Abstract This note presents a proof for the subspace property of linear variational methods for fair surface design. Specifical

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A Subspace Clustering Framework for Research Group Collaboration∗ Nitin Agarwal Ehtesham Haque Huan Liu

Source URL: www.public.asu.edu

Protocols for Learning Classifiers on Distributed Data Hal Daum´e III Je↵ M. Phillips University of Maryland, CP University of Utah Suresh Venkatasubramanian

Source URL: www.cs.utah.edu

• Linear classifier
• Classifier
• Gain
• Boosting methods for object categorization
• Random subspace method
• Statistics
• Statistical classification
• Margin classifier

Research Paper Recommender Systems: A Subspace Clustering Approach
Nitin Agarwal, Ehtesham Haque, Huan Liu, and Lance Parsons Arizona State University, Tempe AZ 85281, USA Abstract. Researchers from the same lab often s

Source URL: www.public.asu.edu