'Sparsity' diaporamas de présentation

EE 359: Wireless Communications

EE 359: Wireless Communications. Advanced Topics in Wireless. Topics. EE360. EE360. EE360. EE360. Future wireless networks Software-defined and low-complexity radios Advanced design of cellular systems Wireless network convergence and SDN Ad-hoc and sensor networks

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Computer examples

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Community Structure in Large Social and Information Networks

Community Structure in Large Social and Information Networks. Michael W. Mahoney Yahoo Research ( For more info, see: http://www.cs.yale.edu/homes/mmahoney ) Joint work with: Jure Leskovec, Kevin Lang and Anirban Dasgupta. Lots and lots of large data! .

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Fast Algorithms for Structured Sparsity

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Deep Learning

Deep Learning. Supervised Learning. Works well if we have right features Domains like computer vision, audio processing, and natural language processing requires feature engineering. Feature Engineering is tough job Manually finding right features does not scale well. What?.

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Learning with Structured Sparsity

Learning with Structured Sparsity. Authors: Junzhou Huang, Tong Zhang, Dimitris Metaxas. Introduction. Fixed set of p basis vectors where for each j . -->

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Sparse Fourier Transform

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Genomic Data Privacy Protection Using Compressive Sensing

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Sparse representation for coarse and fine object recognition

Sparse representation for coarse and fine object recognition. Thang V. Pham & Arnold W. M. Smeulders ISIS research group University of Amsterdam, the Netherlands. AIO-SOOS. Content. Coarse and fine recognition with PCA A new representation Gaussian derivative bases Experimental results

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Exploiting Graphical Structure in Decision-Making

Exploiting Graphical Structure in Decision-Making. Ben Van Roy Stanford University. Overview. Graphical models in decision-making Singly-connected ? efficient computation General decision problems ? intractable Sparsity ? reduction in computation? Sequential decision-making

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Inferring rankings under constrained sensing

Inferring rankings under constrained sensing. Srikanth Jagabathula Devavrat Shah NIPS 2008. A motivating example. . Consider a pre-election scenario in a democratic country with n potential candidates. Each person (or voter) has certain ranking of these candidates in mind (consciously or

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MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions

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Preventing Sexual Unprotected Intercourse

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