PosterSession1 < SPARS2015

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---+ Poster Sessions

Papers will be grouped into the following topics at the three poster sessions:

<table border="0" cellpadding="0" cellspacing="0"><col width="44"></col> <col width="273"></col> <tbody> <tr> <td height="21" width="44"> *Code* </td> <td width="273"> *Topic* </td> </tr> <tr> <td height="21">A</td> <td>Iterative thresholding</td> </tr> <tr> <td height="21">B</td> <td>CS / Nullspace / RIP methods</td> </tr> <tr> <td height="21">C</td> <td>Support recovery</td> </tr> <tr> <td height="21">D</td> <td>Low-rank matrix methods</td> </tr> <tr> <td height="21">E</td> <td>Applications - denoising / deconvolution etc</td> </tr> <tr> <td height="21">F</td> <td>not used</td> </tr> <tr> <td height="21">G</td> <td>Least squares</td> </tr> <tr> <td height="21">H</td> <td>Structured sparsity</td> </tr> <tr> <td height="21">I</td> <td>L1 vs Lp norms & reweighting</td> </tr> <tr> <td height="21">J</td> <td>Sparse classifiers & machine learning</td> </tr> <tr> <td height="21">K</td> <td>Prony methods</td> </tr> <tr> <td height="21">L</td> <td>Adaptive sensing</td> </tr> <tr> <td height="21">M</td> <td>Dictionary learning</td> </tr> </tbody> </table>
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---++ <a name="poster1a"></a>Poster Session 1 - Monday, July 6, 14:30-16:30<br />Theoretical Aspects of Sparsity

<table border="0" cellpadding="0" cellspacing="0"> <tbody> <tr> <td height="21" width="44"> *Code* </td> <td width="273"> *Topic* </td> </tr> <tr> <td height="21">A</td> <td>Iterative thresholding</td> </tr> <tr> <td height="21">B</td> <td>CS / Nullspace / RIP methods</td> </tr> <tr> <td height="21">C</td> <td>Support recovery</td> </tr> <tr> <td height="21">D</td> <td>Low-rank matrix methods</td> </tr> <tr> <td height="21">I</td> <td>L1 vs Lp norms & reweighting</td> </tr> <tr> <td height="21">K</td> <td>Prony methods</td> </tr> </tbody> </table>
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<table border="0" cellpadding="0" cellspacing="0" style="width: 861px;"><col width="50"></col> <col width="45"></col> <col width="292"></col> <col width="474"></col> <tbody> <tr> <td height="19" width="50"> *Paper#* </td> <td width="45"> *Topic* </td> <td width="292"> *Title* </td> <td width="474"> *Authors* </td> </tr> <tr> <td height="19">1013</td> <td>A</td> <td>Iterative hard thresholding with joint constraints</td> <td>Thomas Blumensath*, University of Southampton</td> </tr> <tr> <td height="19">1071</td> <td>A</td> <td>Local Linear Convergence of Forward--Backward Splitting for Low Complexity Regularization</td> <td>Jingwei Liang*, Jalal Fadili, ENSICAEN; Gabriel Peyré, CNRS & Université Paris-Dauphine, CEREMADE</td> </tr> <tr> <td height="19">1088</td> <td>A</td> <td>Contrast re-enhancement of Total-Variation regularization jointly with the Douglas-Rachford iterations</td> <td>Charles-Alban Deledalle*, Nicolas Papadakis, IMB - CNRS, Univ Bordeaux; Joseph Salmon, CNRS LTCI &ndash; Télécom !ParisTech </td> </tr> <tr> <td height="19">1120</td> <td>A</td> <td>Local Linear Convergence of an Inertial ISTA</td> <td>Patrick Johnstone*, Pierre Moulin, University of Illinois</td> </tr> <tr> <td height="19">1143</td> <td>A</td> <td>Communication-Efficient Distributed IHT</td> <td>Puxiao Han*, Ruixin Niu, Virginia Commonwealth Univ.; Yonina Eldar, Technion</td> </tr> <tr> <td height="19">1036</td> <td>B</td> <td>Linear embeddings of low-dimensional subsets of a Hilbert space to R^m</td> <td>Gilles Puy*, INRIA; Mike Davies, U Edinburgh; Remi Gribonval, Centre de Recherche INRIA Rennes</td> </tr> <tr> <td height="19">1070</td> <td>B</td> <td>Improved RIP Guarantees for certain Deterministic Matrices based on Coherence</td> <td>Arash Amini*, Sharif University of Tech.</td> </tr> <tr> <td height="19">1031</td> <td>C</td> <td>Heuristic Optimality Checks for Noise-Aware Sparse Recovery by l1-Minimization</td> <td>Christoph Brauer*, Dirk Lorenz, TU Braunschweig; Andreas Tillmann, TU Darmstadt</td> </tr> <tr> <td height="19">1032</td> <td>C</td> <td>A sublinear parallel algorithm for combinatorial compressed sensing</td> <td>Rodrigo Mendoza Smith*, Jared Tanner, University of Oxford</td> </tr> <tr> <td height="19">1033</td> <td>C</td> <td>Phase Transitions in Group Testing</td> <td>Jonathan Scarlett*, Volkan Cevher, EPFL - Lausanne</td> </tr> <tr> <td height="19">1058</td> <td>C</td> <td>Geometric Conditions for Subspace-Sparse Recovery</td> <td>Chong You*, Rene Vidal, The Johns Hopkins University</td> </tr> <tr> <td height="19">1072</td> <td>C</td> <td>Asymptotic of Sparse Support Recovery for Positive Measures</td> <td>Quentin DENOYELLE*, Université Paris-Dauphine; Vincent Duval, INRIA Rocquencourt; Gabriel Peyré, CNRS & Université Paris-Dauphine, CEREMADE</td> </tr> <tr> <td height="19">1080</td> <td>C</td> <td>Time-data tradeoff for the sparse and cosparse regularizations of physics-driven inverse problems</td> <td>Srdan Kitic*, INRIA; Nancy Bertin, IRISA; Remi Gribonval, Centre de Recherche INRIA Rennes</td> </tr> <tr> <td height="19">1136</td> <td>C</td> <td>MRI SNR Improvement Utilizing Sparsity of Difference Between Slices</td> <td>Lior Weizman*, Jonatan Chernyak, Amit Solomon, Yonina Eldar, Moran Artzi, Dafna Ben Bashat, Technion</td> </tr> <tr> <td height="19">1087</td> <td>D</td> <td>Image inpainting using low-rank block Hankel structured matrix from local patches</td> <td>Kyong Hwan Jin, Jong Chul Ye*, Dept. of Bio and Brain Engineering, KAIST</td> </tr> <tr> <td height="19">1097</td> <td>D</td> <td>Online Robust Matrix Completion</td> <td>Brian Lois, Namrata Vaswani*, Iowa State University</td> </tr> <tr> <td height="19">1112</td> <td>D</td> <td>Low-Rank Matrix Recovery from Row&Column Measurements</td> <td>Avishai Wagner*, Or Zuk, Hebrew University of Jerusalem</td> </tr> <tr> <td height="19">1145</td> <td>D</td> <td>Sparse Self-Expressive Decompositions for Dimensionality Reduction and Clustering</td> <td>Eva Dyer*, Rehab. Inst. of Chicago; Raajen Patel, Rich Baraniuk, Rice University; Konrad Kording, Northwestern University; Tom Goldstein, University of Maryland</td> </tr> <tr> <td height="19">12</td> <td>I</td> <td>CEL0: a continuous alternative to l0 penalty</td> <td>Emmanuel Soubies*, Laure Blanc-Féraud, UNS, CNRS !I3S; Gilles Aubert, UNS, CNRS JAD</td> </tr> <tr> <td height="19">1016</td> <td>I</td> <td>Expected Patch Log Likelihood with a Sparse Enforcing Prior</td> <td>Jeremias Sulam*, Michael Elad, Technion</td> </tr> <tr> <td height="19">1024</td> <td>I</td> <td>Quadratically fast IRLS for sparse signal recovery</td> <td>Chiara Ravazzi*, Enrico Magli, Politecnico di Torino</td> </tr> <tr> <td height="19">1029</td> <td>I</td> <td>Compressive Gaussian Mixture Estimation by Orthogonal Matching Pursuit with Replacement</td> <td>Nicolas Keriven*, IRISA Rennes; Remi Gribonval, Centre de Recherche INRIA Rennes</td> </tr> <tr> <td height="19">1039</td> <td>I</td> <td>Sparse Gradient Regularisation in Discrete and Continuous Spaces</td> <td>Jan Lellmann*, University of Cambridge; Evgeny Strekalovskiy, Daniel Cremers, TU Munich</td> </tr> <tr> <td height="19">1041</td> <td>I</td> <td>Too Relaxed? Tightly Relaxed Non-convex Sparse Regularization</td> <td>Ankit Parekh*, Ivan Selesnick, New York University</td> </tr> <tr> <td height="19">1046</td> <td>I</td> <td>Markov-tree Bayesian Group-sparse Modeling: Efficient Solutions to Large Inverse Problems</td> <td>Ganchi Zhang*, Nick Kingsbury, University of Cambridge</td> </tr> <tr> <td height="19">1061</td> <td>I</td> <td>The Ordered Weighted l1 Norm: Atomic Formulation and Conditional Gradient Algorithm</td> <td>Mario Figueiredo*, Xiangrong Zeng, IT, IST, University of Lisbon</td> </tr> <tr> <td height="19">1073</td> <td>I</td> <td>Local Linear Convergence of Douglass--Rachford/ADMM for Low Complexity Regularization</td> <td>Jingwei Liang*, Jalal Fadili, ENSICAEN; Gabriel Peyré, CNRS & Université Paris-Dauphine, CEREMADE; Russell Luke, University of Göttingen</td> </tr> <tr> <td height="19">1085</td> <td>I</td> <td>Smoothing Doesn't Improve the Convergence Rate of LASSO</td> <td>Subhadip Mukherjee*, Chandra Sekhar Seelamantula, Indian Institute of Science</td> </tr> <tr> <td height="19">1092</td> <td>I</td> <td>Sparsity for Overparameterized Variational Problems</td> <td>Raja Giryes*, Duke University; Michael Elad, Alfred Bruckstein, Technion</td> </tr> <tr> <td height="19">1104</td> <td>I</td> <td>A Bayesian Method for Sparse Approximation of Functions</td> <td>Michael Tipping*, N/A</td> </tr> <tr> <td height="19">1113</td> <td>I</td> <td>On noise robustness in sparse analysis</td> <td>Marc Nicodème*, IMS; Charles Dossal, IMB; Flavius Turcu, IMS</td> </tr> <tr> <td height="19">1131</td> <td>I</td> <td>Pseudo Marginal MCMC for Parameter Estimation in Alpha Stable Distributions</td> <td>Marina Riabiz*, Fredrik Lindsten, Simon Godsill, University of Cambridge</td> </tr> <tr> <td height="19">1110</td> <td>K</td> <td>Prony&rsquo;s Method for Multivariate Signals</td> <td>Thomas Peter*, University of Osnabrück, Gerlind Plonka, Robert Schaback, University of Goettingen</td> </tr> </tbody> </table>
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---++ <a name="poster2a"></a>Poster Session 2 - Wednesday, July 8, 14:30-16:30 <br />Structured Sparsity and Adaptive Methods

<table border="0" cellpadding="0" cellspacing="0"> <tbody> <tr> <td height="21" width="44"> *Code* </td> <td width="273"> *Topic* </td> </tr> <tr> <td height="21">G</td> <td>Least squares</td> </tr> <tr> <td height="21">H</td> <td>Structured sparsity</td> </tr> <tr> <td height="21">I</td> <td>L1 vs Lp norms & reweighting</td> </tr> <tr> <td height="21">J</td> <td>Sparse classifiers & machine learning</td> </tr> <tr> <td height="21">L</td> <td>Adaptive sensing</td> </tr> <tr> <td height="21">M</td> <td>Dictionary learning</td> </tr> </tbody> </table>

<table border="0" cellpadding="0" cellspacing="0"><col width="50"></col> <col width="45"></col> <col width="292"></col> <col width="474"></col> <tbody> <tr> <td height="19" width="50"> *Paper#* </td> <td width="45"> *Topic* </td> <td width="292"> *Title* </td> <td width="474"> *Authors* </td> </tr> <tr> <td height="19">1018</td> <td>G</td> <td>Robust Principal Component Analysis in high dimension</td> <td>Ilaria Giulini*, Ecole Normale Superieure</td> </tr> <tr> <td height="19">1034</td> <td>G</td> <td>Non-Negative Orthogonal Least Square: an Efficient Implementation</td> <td>Mehrdad Yaghoobi*, Mike Davies, University of Edinburgh</td> </tr> <tr> <td height="19">1067</td> <td>H</td> <td>Distributed algorithms for in-network recovery of jointly sparse signals</td> <td>Sophie Fosson*, Javier Matamoros, Carles Anton-Haro, Enrico Magli, Politecnico di Torino</td> </tr> <tr> <td height="19">1074</td> <td>H</td> <td>Structural Norm Minimization based on Neighborhoods</td> <td>Roozbeh Manshaei*, Ryerson University; <a href="foswiki.bin.edit.SPARS2015.SayedMasoud?topicparent=SPARS2015.PosterSession2" rel="nofollow" title="Create this topic">SayedMasoud</a> Hashemi, U<font>niversity of Toronto</font><font>; Matthew Kyan, Ryerson University</font></td> </tr> <tr> <td height="19">1084</td> <td>H</td> <td>Structure Aware ADMM Splitting for Discrete Tomography</td> <td>Andreea Denitiu*, Stefania Petra, Heidelberg University; Claudius Schnoerr, Hochschule Munchen; Christoph Schnoerr, University of Heidelberg</td> </tr> <tr> <td height="19">1095</td> <td>H</td> <td>Fast Solving of the Group-Lasso via Dynamic Screening.</td> <td>Antoine Bonnefoy*, Valentin Emiya, liva Ralaivola, Aix-Marseille Université - LIF; Remi Gribonval, Centre de Recherche INRIA Rennes</td> </tr> <tr> <td height="19">1096</td> <td>H</td> <td>Sparsistency of \ell_1-Regularized M-Estimators</td> <td>Yen-Huan Li*, Jonathan Scarlett, Pradeep Ravikumar, Volkan Cevher, EPFL, Lausanne</td> </tr> <tr> <td height="19">1108</td> <td>H</td> <td>Sparse Clustering of Noisy Signals in the Wavelet Domain</td> <td>Tom Hope*, Avishai Wagner, Or Zuk, Hebrew University of Jerusalem</td> </tr> <tr> <td height="19">1109</td> <td>H</td> <td>Structured sparsity: towards a "deep" understanding</td> <td>Angélique Drémeau*, Florent Krzakala, ENSTA Bretagne</td> </tr> <tr> <td height="19">1141</td> <td>H</td> <td>Learning network structure via Hawkes processes</td> <td>Michael Moore*, Mark Davenport, Georgia Institute of Technology</td> </tr> <tr> <td height="19">1142</td> <td>H</td> <td>Anomaly Detection Using Convolutional Sparse Models</td> <td>Diego Carrera*, Giacomo Boracchi, Alessandro Foi, Brendt Wohlberg, Politecnico Di Milano</td> </tr> <tr> <td height="19">1051</td> <td>I</td> <td>Efficient Algorithms for l_infty-Norm Minimization</td> <td>Christoph Studer*, Cornell University; Tom Goldstein, University of Maryland; Wotao Yin, UCLA; Rich Baraniuk, Rice Univ.</td> </tr> <tr> <td height="19">1052</td> <td>I</td> <td>Forward-Backward Splitting Made FASTA</td> <td>Tom Goldstein*, University of Maryland; Christoph Studer, Cornell University; Rich Baraniuk, Rice University</td> </tr> <tr> <td height="19">5</td> <td>J</td> <td>A Semiquantitative Group Testing Approach for Learning Interpretable Clinical Prediction Rules</td> <td>Amin Emad, Kush Varshney*, Dmitry Malioutov, IBM Research;</td> </tr> <tr> <td height="19">1037</td> <td>J</td> <td>On Sufficient Conditions for Affine Sparse Subspace Clustering</td> <td>Chun-Guang Li*, Beijing Univ.of Posts&Telecomm; Chong You, Rene Vidal, The Johns Hopkins University</td> </tr> <tr> <td height="19">1044</td> <td>J</td> <td>Compressed Sensing with Deep Neural Network</td> <td>David Boublil*, Michael Elad, Michael Zibulevsky, Technion;</td> </tr> <tr> <td height="19">1053</td> <td>J</td> <td>Self-Expressive Clustering of Binary Data via Group Sparsity</td> <td>Andrew Lan, Rice University; Christoph Studer*, Cornell University; Rich Baraniuk, Rice University</td> </tr> <tr> <td height="19">1090</td> <td>J</td> <td>Sparse Modeling of Neural Network Posterior Probabilities for Exemplar-Based Speech Recognition</td> <td>Pranay Dighe, Afsaneh Asaei*, Hervé Bourlard, Idiap Research Institute, EPFL</td> </tr> <tr> <td height="19">1148</td> <td>J</td> <td>A Primal-Dual Algorithmic Framework for Constrained Convex Optimization</td> <td>Volkan Cevher*, Quoc Tran Dinh, EPFL, Lausanne</td> </tr> <tr> <td height="19">1021</td> <td>L</td> <td>Sub-Nyquist Volumetric Ultrasound Imaging</td> <td>Tanya Chernyakova*, Yonina Eldar, The Technion, IIT</td> </tr> <tr> <td height="19">1063</td> <td>L</td> <td>Xampling and Frequency Domain Beamforming Application in a Wireless Ultrasound Imaging System</td> <td>Alon Eilam*, Tanya Chernyakova, Samuel Londer, Armand Chocron, Technion; Arcady Kempinski, GE Healthcare; Yonina Eldar, Technion</td> </tr> <tr> <td height="19">1126</td> <td>L</td> <td>Minimum-Time Sampling Using Quantile Search</td> <td>Laura Balzano*, John Lipor, University of Michigan</td> </tr> <tr> <td height="19">1149</td> <td>L</td> <td>Adaptive Dynamical Systems in Compressive Domains as a Manifold Learning Framework</td> <td>Herbert Buchner*, Simon Godsill, University of Cambridge</td> </tr> <tr> <td height="19">7</td> <td>M</td> <td>A Tensor-based Dictionary Approach to Tomographic Image Reconstruction</td> <td>Sara Soltani*, Danmarks Tekniske Universitet; Misha Kilmer, Tufts University</td> </tr> <tr> <td height="19">9</td> <td>M</td> <td>Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment</td> <td>Liansheng Zhuang, Univ. Sci. & Tech. China; Tsung-Han Chan, Adv. Digital Sci. Center Singapore; Allen Yang*, Univ. of California, Berkeley; Yi Ma, !ShanghaiTech University</td> </tr> <tr> <td height="19">13</td> <td>M</td> <td>Learning Dictionaries of Orthonormal Bases for Scalable Coding: Application to Biological Images</td> <td>Jonathan Taquet*, Canon Research Centre France; Claude Labit, Centre INRIA Rennes Bretagne Atlantique</td> </tr> <tr> <td height="19">1026</td> <td>M</td> <td>Learning Sparsity Inducing Analysis Operators for Discriminative Similarity Metrics</td> <td>Cagdas Bilen*, Joaquin Zepeda, Patrick Perez, Technicolor</td> </tr> <tr> <td height="19">1040</td> <td>M</td> <td>Regularized Dictionary Learning for Graph Signals</td> <td>Yael Yankelevsky*, Michael Elad, Technion</td> </tr> <tr> <td height="19">1045</td> <td>M</td> <td>On the Sample Complexity of Analysis Operator Learning</td> <td>Matthias Seibert*, Martin Kleinsteuber, Technische Universität München</td> </tr> <tr> <td height="19">1050</td> <td>M</td> <td>Learning a Dynamics Dictionary for Time-Varying Sparse Signals</td> <td>Adam Charles*, Christopher Rozell, Georgia Institute of Technology</td> </tr> <tr> <td height="19">1057</td> <td>M</td> <td>Sparse Regression in Time-Frequency Dictionaries with Non-White Gaussian Noise</td> <td>Matthieu Kowalski*, Univ Paris-Sud; Alexandre Gramfort, Telecom !ParisTech</td> </tr> <tr> <td height="19">1060</td> <td>M</td> <td>Reconstruction of Dynamic MRI using a Sparsity Prior on 1D Temporal Snippets</td> <td>Esben Plenge*, Michael Elad, Technion; Mitchell Cooper, Martin Prince, Yi Wang, Pascal Spincemaille, Cornell</td> </tr> <tr> <td height="19">1086</td> <td>M</td> <td>Convolutional Trees for Fast Transform Learning</td> <td>Olivier Chabiron*, Jean-Yves Tourneret, Herwig Wendt, IRIT; François Malgouyres, IMT</td> </tr> <tr> <td height="19">1093</td> <td>M</td> <td>Dictionary Learning for Sparse Representation of Neural Network Exemplars in Speech Recognition</td> <td>Pranay Dighe, Afsaneh Asaei*, Hervé Bourlard, Idiap Research Institute, EPFL</td> </tr> <tr> <td height="19">1100</td> <td>M</td> <td>New Analysis of Multiband Modulated DPSS Dictionaries</td> <td>Zhihui Zhu*, Michael Wakin, Colorado School of Mines</td> </tr> <tr> <td height="19">1114</td> <td>M</td> <td>Cropped Signal Dictionary Without Border Effects</td> <td>Boaz Ophir*, Jeremias Sulam, Michael Zibulevsky, Michael Elad, Technion</td> </tr> </tbody> </table>
---++ 
---++ <a name="poster3a"></a>Poster Session 3 - Thursday, July 9, 14:50-16:50<br />Applications of Sparsity

<table border="0" cellpadding="0" cellspacing="0"> <tbody> <tr> <td height="21" width="44"> *Code* </td> <td width="273"> *Topic* </td> </tr> <tr> <td height="21">E</td> <td>Applications - denoising / deconvolution etc</td> </tr> </tbody> </table>

<table border="0" cellpadding="0" cellspacing="0"><col width="50"></col> <col width="45"></col> <col width="292"></col> <col width="474"></col> <tbody> <tr> <td height="19" width="50"> *Paper#* </td> <td width="45"> *Topic* </td> <td width="292"> *Title* </td> <td width="474"> *Authors* </td> </tr> <tr> <td height="19">11</td> <td>E</td> <td>Sparse BSS in the presence of outliers</td> <td>Cecile Chenot*, Jerome Bobin, Jeremy Rapin, CEA</td> </tr> <tr> <td height="19">1017</td> <td>E</td> <td>Disease Classification via Sparse Proteomics Analysis</td> <td>Irena Bojarovska, Technical University of Berlin; Tim Conrad, Nada Cvetkovic, Free University of Berlin; Martin Genzel*, Gitta Kutyniok, TU Berlin; Christof Schütte, Free University of Berlin; Jan Vybiral, Charles University Prague</td> </tr> <tr> <td height="19">1019</td> <td>E</td> <td>Sub-Nyquist Cognitive Radio</td> <td>Shahar Tsiper*, Deborah Cohen, Yonina Eldar, Technion</td> </tr> <tr> <td height="19">1030</td> <td>E</td> <td>Postprocessing of Compressed Images via Sequential Image Denoising</td> <td>Yehuda Dar*, Alfred Bruckstein, Michael Elad, Technion; Raja Giryes, Duke University</td> </tr> <tr> <td height="19">1035</td> <td>E</td> <td>Super-Resolution of SEM Images by Dictionary Learning</td> <td>Shahar Tsiper*, Yonina C. Eldar, Moti Segev, Technion</td> </tr> <tr> <td height="19">1038</td> <td>E</td> <td>A Robust Nonlinear Kalman Smoothing Approach for Dynamic Matrix Factorization</td> <td>Aleksandr Aravkin, Kush Varshney*, Dmitry Malioutov, IBM Research</td> </tr> <tr> <td height="19">1049</td> <td>E</td> <td>Phase-transition behavior in X-ray CT matches that of Gaussian sensing matrices</td> <td>Jakob Joergensen*, Technical University of Denmark; Stefania Petra, Heidelberg University; Emil Sidky, University of Chicago</td> </tr> <tr> <td height="19">1064</td> <td>E</td> <td>An Unified Approach for Over and Under-determined Blind Source Separation Based on Both Sparsity and Decorrelation</td> <td>Fangchen Feng*, Matthieu Kowalski, Univ Paris-Sud</td> </tr> <tr> <td height="19">1078</td> <td>E</td> <td>ALOHA : a link between compressed sensing and parallel MRI</td> <td>Kyong Hwan Jin, Dongwook Lee, Jong Chul Ye*, Dept. of Bio and Brain Engineering, KAIST</td> </tr> <tr> <td height="19">1082</td> <td>E</td> <td>A Fast and Sparsity-Aware Generalization of SMART for Tomographic Particle Image Velocimetry</td> <td>Ioana BARBU, Cédric Herzet*, INRIA</td> </tr> <tr> <td height="19">1089</td> <td>E</td> <td>Image reconstruction from dense binary pixels</td> <td>Or Litany*, Tal Remez, Alex Bronstein, Tel Aviv University</td> </tr> <tr> <td height="19">1098</td> <td>E</td> <td>On compressed sensing in photoacoustic tomography</td> <td>Michael Sandbichler*, Felix Krahmer, Thomas Berer, Peter Burgholzer, Markus Haltmeier, University of Innsbruck</td> </tr> <tr> <td height="19">1107</td> <td>E</td> <td>Compressive Computed Tomography Image Reconstruction with Denoising Message Passing Algorithms</td> <td>Alessandro Perelli*, Mike Davies, University of Edinburgh</td> </tr> <tr> <td height="19">1116</td> <td>E</td> <td>OMP with Unknown Filters for Multipath Channel Estimation</td> <td>Ivan Dokmanic*, Martin Vetterli, EPFL</td> </tr> <tr> <td height="19">1118</td> <td>E</td> <td>A scalable algorithm for radio-interferometric imaging</td> <td>Rafael Carrillo*, Vijay Kartik, Jean-Philippe Thiran, EPFL; Yves Wiaux, Heriot-Watt University</td> </tr> <tr> <td height="19">1122</td> <td>E</td> <td>Discrete solutions to underdetermined linear systems via sparse-based transform</td> <td>Dominique Pastor*, Abdeldjalil Aissa-El-Bey, Telecom Bretagne</td> </tr> <tr> <td height="19">1123</td> <td>E</td> <td>On Compressed Motion Sensing for Tomographical Particle Image Velocimetry</td> <td>Robert Dalitz*, Ecaterina Budnariuc, Stefania Petra, Christoph Schnoerr, University of Heidelberg</td> </tr> <tr> <td height="19">1127</td> <td>E</td> <td>Stable Camera Location Estimation by Convex Programming</td> <td>Onur Ozyesil*, Amit Singer, Princeton University; Ronen Basri, Weizmann Institute of Science</td> </tr> <tr> <td height="19">1132</td> <td>E</td> <td>Single Pixel Fabry Perot Camera: Photoacoustic Image Reconstruction using Data Sparsity</td> <td>Marta Betcke*, Ben Cox, Nam Huynh, Paul Beard, Edward Zhang, Simon Arridge, University College London</td> </tr> <tr> <td height="19">1133</td> <td>E</td> <td>Sparse NMF methods applied to Music Transcription</td> <td>Ken O'Hanlon*, Queen Mary University Of London; Mark Plumbley, CVSSP, U Surrey</td> </tr> <tr> <td height="19">1135</td> <td>E</td> <td>Towards 4D Photoacoustic Tomography</td> <td>Felix Lucka*, Marta Betcke, Simon Arridge, Ben Cox, Nam Huynh, Edward Zhang, Paul Beard, University College London</td> </tr> <tr> <td height="19">1137</td> <td>E</td> <td>Reversible Data Hiding on Compressively Sensed Measurements</td> <td>Mehmet Yamaç*, Bo&#x11F;aziçi University; Ça&#x11F;atay Dikici, Imagination Technologies; Bülent Sankur, Bo&#x11F;aziçi University</td> </tr> </tbody> </table>
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