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Support Recovery of Sparse Signals in the Presence of Multiple Measurement Vectors

IEEE transactions on information theory, 2013-05, Vol.59 (5), p.3139-3157

2013

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Limits on Support Recovery of Sparse Signals via Multiple-Access Communication Techniques

IEEE transactions on information theory, 2011-12, Vol.57 (12), p.7877-7892

2011

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Algorithms for robust linear regression by exploiting the connection to sparse signal recovery

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010, p.3830-3833

2010

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Sparse lexical representation for semantic entity resolution

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013, p.8575-8579

2013

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The Gap Between Trustworthy AI Research and Trustworthy Software Research: A Tertiary Study

ACM computing surveys, 2024-09

2024

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Insights into the stable recovery of sparse solutions in overcomplete representations using network information theory

2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008, p.3921-3924

2008

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On the role of the properties of the nonzero entries on sparse signal recovery

2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, 2010, p.753-757

2010

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Spectral Estimation of Voiced Speech using a Family of MVDR Estimates

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007, Vol.4, p.IV-1069-IV-1072

2007

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Energy efficient GPS acquisition with Sparse-GPS

IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, 2014, p.155-166

2014

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MultiPass lasso algorithms for sparse signal recovery

2011 IEEE International Symposium on Information Theory Proceedings, 2011, p.1417-1421

2011

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Performance limits of matching pursuit algorithms

2008 IEEE International Symposium on Information Theory, 2008, p.2444-2448

2008

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Sparse signal recovery in the presence of intra-vector and inter-vector correlation

2012 International Conference on Signal Processing and Communications (SPCOM), 2012, p.1-5

2012

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Algorithm Development for Sparse Signal Recovery and Performance Limits Using Multiple-User Information Theory

Jin, Yuzhe

2011

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Optoelectronic Properties of GaN-Based Light-Emitting Diodes with Different Mesa Structures

Materials sciences and applications, 2012-12, Vol.3 (12), p.838-842

2012

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Research on Aging-Friendly Design Evaluation Model of Wearable Devices Based on Implicit Interaction Theory

Advances in Mechanical Design, p.397-417

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Performance tradeoffs for exact support recovery of sparse signals

2010 IEEE International Symposium on Information Theory, 2010, p.1558-1562

2010

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COIN-GPS: indoor localization from direct GPS receiving

Proceedings of the 12th annual international conference on Mobile systems, applications, and services, 2014, p.301-314

2014

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Entity linking at the tail: sparse signals, unknown entities, and phrase models

Proceedings of the 7th ACM international conference on Web search and data mining, 2014, p.453-462

2014

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Energy efficient GPS acquisition with sparse-gps

Proceedings of the 13th international symposium on Information processing in sensor networks, 2014, p.155-166

2014

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CO-GPS: Energy Efficient GPS Sensing with Cloud Offloading

IEEE transactions on mobile computing, 2016-06, Vol.15 (6), p.1348-1361

2016

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SparseGPS: energy efficient GPS acquisition via sparse approximation

Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, 2013, p.1-2

2013

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Revealing a steroid receptor ligand as a unique PPARγ 3gonist

细胞研究：英文版, 2012, Vol.22 (4), p.746-756

Shengchen Lin Ying Han Yuzhe Shi Hui Rong Songyang Zheng Shikan Jin Shu-Yong Lin Sheng-Cai Lin Yong Li

2012

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Technological catch-up by east Asian firms: Trends, issues, and future research agenda

Asia Pacific journal of management, 2018-09, Vol.35 (3), p.639-669

2018

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Natural disasters and corporate tax burden: Evidence from chinese energy sector

Energy economics, 2024-02, Vol.130, p.107322, Article 107322

2024

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Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks

Nature communications, 2023-10, Vol.14 (1), p.6155-15, Article 6155

2023

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Support Recovery of Sparse Signals in the Presence of Multiple Measurement Vectors

Limits on Support Recovery of Sparse Signals via Multiple-Access Communication Techniques

Algorithms for robust linear regression by exploiting the connection to sparse signal recovery

Sparse lexical representation for semantic entity resolution

The Gap Between Trustworthy AI Research and Trustworthy Software Research: A Tertiary Study

Insights into the stable recovery of sparse solutions in overcomplete representations using network information theory

On the role of the properties of the nonzero entries on sparse signal recovery

Spectral Estimation of Voiced Speech using a Family of MVDR Estimates

Energy efficient GPS acquisition with Sparse-GPS

MultiPass lasso algorithms for sparse signal recovery

Performance limits of matching pursuit algorithms

Sparse signal recovery in the presence of intra-vector and inter-vector correlation

Algorithm Development for Sparse Signal Recovery and Performance Limits Using Multiple-User Information Theory

Optoelectronic Properties of GaN-Based Light-Emitting Diodes with Different Mesa Structures

Research on Aging-Friendly Design Evaluation Model of Wearable Devices Based on Implicit Interaction Theory

Performance tradeoffs for exact support recovery of sparse signals

COIN-GPS: indoor localization from direct GPS receiving

Entity linking at the tail: sparse signals, unknown entities, and phrase models

Energy efficient GPS acquisition with sparse-gps

CO-GPS: Energy Efficient GPS Sensing with Cloud Offloading

SparseGPS: energy efficient GPS acquisition via sparse approximation

Revealing a steroid receptor ligand as a unique PPARγ 3gonist

Technological catch-up by east Asian firms: Trends, issues, and future research agenda

Natural disasters and corporate tax burden: Evidence from chinese energy sector

Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks

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