Table of Contents

• Multi-Scale Algorithms for Optimal TransportBernhard Schmitzer. 1-5 [doi]
• Causality from a Distributional Robustness Point of ViewNicolai Meinshausen. 6-10 [doi]
• SAVE - Space Alternating Variational Estimation for Sparse Bayesian LearningChristo Kurisummoottil Thomas, Dirk T. M. Slock. 11-15 [doi]
• Subspace Data Visualization with Dissimilarity Based on Principal AngleXinyue Shen, Yuchen Jiao, Yuantao Gu. 16-20 [doi]
• BYRDIE: A Byzantine-Resilient Distributed Learning AlgorithmZhiXiong Yang, Waheed U. Bajwa. 21-25 [doi]
• Spectral Statistics of Directed Networks with Random Link Model Transpose-AsymmetryStephen Kruzick, José M. F. Moura. 26-30 [doi]
• A Novel Backbone Network Anomaly Detector via Clustering in Sketch SpaceYating Liu, Yuantao Gu. 31-35 [doi]
• Uncertainty Quantification in Sunspot CountsSophie Mathieu, Rainer von Sachs, Véronique Delouille, Laure Lefevre. 36-40 [doi]
• Optimizing Thermal Comfort and Energy Consumption in a Large Building without Renovation WorkSylvain Le Corff, Alain Champagne, Maurice Charbit, Gilles Noziere, Eric Moulines. 41-45 [doi]
• Robust and Consistent Clustering Recovery via SDP ApproachesChenxi Sun, Tongxin Li, Victor O. K. Li. 46-50 [doi]
• Learning from Signals Defined over Simplicial ComplexesSergio Barbarossa, Stefania Sardellitti, Elena Ceci. 51-55 [doi]
• Distributed Nonparametric Inference Using a One-Sample Bootstrapped Anderson-Darling Test and P-Value FusionTopi Halme, Visa Koivunen. 56-60 [doi]
• Learning Flexible Representations of Stochastic Processes on GraphsAddison W. Bohannon, Brian M. Sadler, Radu V. Balan. 61-65 [doi]
• Predictive Maintenance of Photovoltaic Panels via Deep LearningTimo Huuhtanen, Alexander Jung. 66-70 [doi]
• Endmember Extraction on the GrassmannianElin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson. 71-75 [doi]
• False Discovery Rate Control with Concave Penalties Using Stability SelectionBhanukiran Vinzamuri, Kush R. Varshney. 76-80 [doi]
• Nearly Optimal Robust Subspace Tracking: A Unified ApproachPraneeth Narayanamurthy, Namrata Vaswani. 81-85 [doi]
• Restricted Isometry Property for Low-Dimensional Subspaces and its Application in Compressed Subspace ClusteringGen Li, Qinghua Liu, Yuantao Gu. 86-90 [doi]
• Subsampling Least Squares and Elemental EstimationKeith Knight. 91-94 [doi]
• Deep CNN Sparse Coding Analysis: Towards Average CaseMichael Murray, Jared Tanner. 95-99 [doi]
• Non-Negative Super-Resolution is StableArmin Eftekhari, Jared Tanner, Andrew Thompson 0001, Bogdan Toader, Hemant Tyagi. 100-104 [doi]
• Subgradient Projection Over Directed Graphs Using Surplus ConsensusRan Xin, Chenguang Xi, Usman A. Khan. 105-109 [doi]
• Vector Compression for Similarity Search Using Multi-Layer Sparse Ternary CodesSohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov. 110-114 [doi]
• Subspace Principal Angle Preserving Property of Gaussian Random ProjectionYuchen Jiao, Xinyue Shen, Gen Li, Yuantao Gu. 115-119 [doi]
• The Michigan Data Science Team: A Data Science Education Program with Significant Social ImpactArya Farahi, Jonathan C. Stroud. 120-124 [doi]
• Profit Maximizing Logistic Regression Modeling for Credit ScoringArnout Devos, Jakob Dhondt, Eugen Stripling, Bart Baesens, Seppe Vanden Broucke, Gaurav Sukhatme. 125-129 [doi]
• Alternating Autoencoders for Matrix CompletionKiwon Lee, Yong-Hoon Lee, Changho Suh. 130-134 [doi]
• An Efficient Recommender System by Integrating Non-Negative Matrix Factorization with Trust and Distrust RelationshipsHashem Parvin, Parham Moradi, Shahrokh Esmaeili, Mahdi Jalili. 135-139 [doi]
• Sparse Anomaly Representations in Very High-Dimensional Brain SignalsCatherine Stamoulis. 140-144 [doi]
• Predicting Electricity Outages Caused By Convective StormsRoope Tervo, Joonas Karjalainen, Alexander Jung. 145-149 [doi]
• AIM: An Abstraction for Improving Machine Learning PredictionVictoria Stodden, Xiaomian Wu, Vanessa Sochat. 150-154 [doi]
• Network Inference from Complex Systems Steady States Observations: Theory and MethodsHoi-To Wai, Anna Scaglione, Baruch Barzel, Amir Leshem. 155-159 [doi]
• Semi-Supervised Transfer Learning Using Marginal PredictorsAniket Anand Deshmukh, Emil Laftchiev. 160-164 [doi]
• Semi-Blind Inference of Topologies and Signals over GraphsVassilis N. Ioannidis, Yanning Shen, Georgios B. Giannakis. 165-169 [doi]
• Divide-and-Conquer Tomography for Large-Scale NetworksAugusto Santos, Vincenzo Matta, Ali H. Sayed. 170-174 [doi]
• Computational Strategies for Statistical Inference Based on Empirical Optimal TransportCarla Tameling, Axel Munk. 175-179 [doi]
• Sparse Subspace Clustering with Missing and Corrupted DataZachary Charles, Amin Jalali 0004, Rebecca Willett. 180-184 [doi]
• An Exponentially Convergent Algorithm for Learning Under Distributed FeaturesBicheng Ying, Kun Yuan, Ali H. Sayed. 185-189 [doi]
• Online Graph Learning from Sequential DataStefan Vlaski, Hermina Petric Maretic, Roula Nassif, Pascal Frossard, Ali H. Sayed. 190-194 [doi]
• Online Identification of Directional Graph Topologies Capturing Dynamic and Nonlinear DependenciesYanning Shen, Georgios B. Giannakis. 195-199 [doi]
• Sparsest Network Support Estimation: A Submodular ApproachMario Coutino, Sundeep Prabhakar Chepuri, Geert Leus. 200-204 [doi]
• On Learning Laplacians of Tree Structured GraphsKeng-Shih Lu, Eduardo Pavez, Antonio Ortega. 205-209 [doi]
• Directed Network Topology Inference via Graph Filter IdentificationRasoul Shafipour, Santiago Segarra, Antonio G. Marques, Gonzalo Mateos. 210-214 [doi]
• Learning to Infer Power Grid Topologies: Performance and ScalabilityYue Zhao, Jianshu Chen, H. Vincent Poor. 215-219 [doi]
• Convolutional Neural Networks via Node-Varying Graph FiltersFernando Gama, Geert Leus, Antonio G. Marques, Alejandro Ribeiro. 220-224 [doi]
• MOTIFNET: A Motif-Based Graph Convolutional Network for Directed GraphsFederico Monti, Karl Otness, Michael M. Bronstein. 225-228 [doi]
• Revised Note on Learning Quadratic Assignment with Graph Neural NetworksAlex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna. 229-233 [doi]
• Matching Convolutional Neural Networks without Priors about DataCarlos Eduardo Rosar Kós Lassance, Jean-Charles Vialatte, Vincent Gripon. 234-238 [doi]
• On Graph Convolution for Graph CNNsJian Du, John Shi, Soummya Kar, José M. F. Moura. 239-243 [doi]
• Towards a Spectrum of Graph Convolutional NetworksMathias Niepert, Alberto García-Durán. 244-248 [doi]