Table of Contents

• The Core Consistency of a Compressed TensorGeorgios Tsitsikas, Evangelos E. Papalexakis. 1-5 [doi]
• Supervised Principal Component Analysis Via Manifold OptimizationAlexander Ritchie, Clayton D. Scott, Laura Balzano, Daniel Kessler, Chandra Sekhar Sripada. 6-10 [doi]
• Sparse and Functional Principal Components AnalysisGenevera I. Allen, Michael Weylandt. 11-16 [doi]
• Online Tensor Decomposition and Imputation for Count DataChang Ye, Gonzalo Mateos. 17-21 [doi]
• Localization of Data Injection Attacks on Distributed M-EstimationOr Shalom, Amir Leshem, Anna Scaglione. 22-26 [doi]
• Online Distributed Estimation of Principal EigenspacesDavoud Ataee Tarzanagh, Mohamad Kazem Shirani Faradonbeh, George Michailidis. 27-31 [doi]
• Coke: Communication-Censored Kernel Learning Via Random FeaturesPing Xu, Zhi Tian, Zhe Zhang, Yue Wang. 32-36 [doi]
• Distributed Training with Mobile Agents: Optimization Over Dynamic Directed GraphsFakhteh Saadatniaki, Ran Xin, Usman A. Khan. 37-41 [doi]
• Gradient Coding with Clustering and Multi-Message CommunicationEmre Ozfatura, Deniz Gündüz, Sennur Ulukus. 42-46 [doi]
• Multitaper Analysis of Evolutionary Spectral Density Matrix From Multivariate Spiking ObservationsAnuththara Rupasinghe, Behtash Babadi. 47-51 [doi]
• Graph Topology Learning and Signal Recovery Via Bayesian InferenceMahmoud Ramezani Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Rick S. Blum, H. Vincent Poor. 52-56 [doi]
• Graphical Models and Dynamic Latent Factors for Modeling Functional Brain ConnectivityAndersen Chang, Tianyi Yao, Genevera I. Allen. 57-63 [doi]
• Semi-Supervised Tracking of Dynamic Processes Over Switching GraphsQin Lu, Vassilis N. Ioannidis, Georgios B. Giannakis. 64-68 [doi]
• Time-Varying Interaction Estimation Using Ensemble MethodsBrandon Oselio, Alfred Hero, Amir Sadeghian, Silvio Savarese. 69-75 [doi]
• Clustered Gaussian Graphical Model Via Symmetric Convex ClusteringTianyi Yao, Genevera I. Allen. 76-82 [doi]
• Scalable Learning with Privacy Over GraphsYanning Shen, Geert Leus. 83-87 [doi]
• Learning to Detect an Anomalous Target with Observations from an Exponential FamilyGayathri R. Prabhu, Srikrishna Bhashyam, Aditya Gopalan, Rajesh Sundaresan. 88-92 [doi]
• Simultaneous Multivariate Outlier and Trend DetectionKarl Pazdernik, Bryan Stanfill, Lisa Bramer, Kellie J. MacPhee. 93-99 [doi]
• Deep One-Class Classification Using Intra-Class SplittingPatrick Schlachter, Yiwen Liao, Bin Yang. 100-104 [doi]
• Bayesian Multiple Hypothesis Testing For Distributed Detection In Sensor NetworksTopi Halme, Martin Golz, Visa Koivunen. 105-109 [doi]
• Lfinite Sample Bounds on the Performance of Weighted Linear Least Squares in Sub-Gaussian Correlated NoiseMichael Krikheli, Amir Leshem. 110-114 [doi]
• Asynchronous Distributed Edge-Variant Graph FiltersMario Coutino, Geert Leus. 115-119 [doi]
• Long-Range Dependence Parameter Estimation For Mixed Spectra Gaussian ProcessesLenin Arango-Castillo, Glen Takahara. 120-124 [doi]
• Structural Robustness for Deep Learning ArchitecturesCarlos Eduardo Rosar Kós Lassance, Vincent Gripon, Jian Tang, Antonio Ortega. 125-129 [doi]
• Blind Ensemble Classification of Sequential DataPanagiotis A. Traganitis. 130-134 [doi]
• Online selective training for faster neural network learningSara Mourad, Haris Vikalo, Ahmed H. Tewfik. 135-139 [doi]
• Online Topology Inference from Streaming Stationary Graph SignalsRasoul Shafipour, Abolfazl Hashemi, Gonzalo Mateos, Haris Vikalo. 140-144 [doi]
• Vertex-Frequency ClusteringDaniel B. Burkhardt, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy. 145-149 [doi]
• Sampling of Graph Signals with Blue Noise DitheringAlejandro Parada-Mayorga, Daniel L. Lau, Jhony H. Giraldo, Gonzalo R. Arce. 150-154 [doi]
• Distance-Penalized Active Learning via Markov Decision ProcessesDingyu Wang, John Lipor, Gautam Dasarathy. 155-159 [doi]
• Introducing Graph Smoothness Loss for Training Deep Learning ArchitecturesMyriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega. 160-164 [doi]
• Optimal Sampling Sets in CographsDominique Guillot, Alejandro Parada-Mayorga, Sebastian Cioaba, Gonzalo R. Arce. 165-169 [doi]
• Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear SystemsMohamad Kazem Shirani Faradonbeh, Ambuj Tewari, George Michailidis. 170-174 [doi]
• Kernel-Based Efficient Lifelong Learning AlgorithmSeung-Jun Kim, Rami Mowakeaa. 175-179 [doi]
• Non-Negative Matrix Factorization of Clustered Data with Missing ValuesRebecca Chen, Lav R. Varshney. 180-184 [doi]
• Estimation of State-Space Models with Gaussian Mixture Process NoiseSina Miran, Jonathan Z. Simon, Michael C. Fu, Steven I. Marcus, Behtash Babadi. 185-189 [doi]
• A Hierarchical Approach for Timely Cyberbullying DetectionImara Nazar, Daphney-Stavroula Zois, Mengfan Yao. 190-195 [doi]
• Rumour Detection Via News Propagation Dynamics and User Representation LearningTien Huu Do, Xiao Luo, Duc-Minh Nguyen, Nikos Deligiannis. 196-200 [doi]
• Learning to Regularize Using Neumann NetworksDavis Gilton, Greg Ongie, Rebecca Willett. 201-207 [doi]
• A Stochastic LBFGS Algorithm for Radio Interferometric CalibrationSarod Yatawatta, Lukas De Clercq, Hanno Spreeuw, Faruk Diblen. 208-212 [doi]
• A Convolutional Neural Network Approach to Automated Lung Bounding Box Estimation from Computed Tomography ScansCharles R. Hatt, Sundaresh Ram, Craig J. Galbán. 213-216 [doi]
• Enhancing Medical Imaging Semantic Segmentation Using the Digital AnnealerJiankun Wang, Shahrokh Valaee. 217-221 [doi]
• Dynamic Functional Connectivity Using Heat KernelShih-Gu Huang, Moo K. Chung, Ian C. Carroll, H. Hill Goldsmith. 222-226 [doi]
• Multispectral Snapshot Demosaicing Via Non-Convex Matrix CompletionGiancarlo A. Antonucci, Simon Vary, David Humphreys, Robert A. Lamb, Jonathan Piper, Jared Tanner. 227-231 [doi]
• Classification of Hyperspectral Colon Cancer Images Using Convolutional Neural NetworksSean Mobilia, Birsen Sirkeci Mergen, Joshua Deal, Thomas C. Rich, Silas J. Leavesley. 232-236 [doi]
• Splitting Methods For Convex Bi-Clustering And Co-ClusteringMichael Weylandt. 237-242 [doi]
• Generalized Jordan Center: A Source Localization Heuristic For Noisy And Incomplete ObservationsHuozhi Zhou, Ashish Jagmohan, Lav R. Varshney. 243-247 [doi]
• Online Sparse Subspace ClusteringLiam Madden, Stephen Becker, Emiliano Dall'Anese. 248-252 [doi]
• Data Driven Measurement Matrix Learning for Sparse ReconstructionRobiul Hossain Md. Rafi, Ali Cafer Gürbüz. 253-257 [doi]
• Distribution System State Estimation Via Data-Driven and Physics-Aware Deep Neural NetworksLiang Zhang, Gang Wang 0014, Georgios B. Giannakis. 258-262 [doi]
• Recovery of Missing Data in Correlated Smart Grid DatasetsCristian Genes, Iñaki Esnaola, Samir Medina Perlaza, Daniel Coca. 263-269 [doi]
• Learning to Infer Voltage Stability Margin Using Transfer LearningJiaming Li, Yue Zhao, Young Hwan Lee, Seung-Jun Kim. 270-274 [doi]
• On Modeling Voltage Phasor Measurements as Graph SignalsRaksha Ramakrishna, Anna Scaglione. 275-279 [doi]
• Assessing the Resilience of the Texas Power Grid NetworkDorcas Ofori-Boateng, Asim Kumer Dey, Yulia R. Gel, Binghui Li, Jie Zhang, H. Vincent Poor. 280-284 [doi]
• Data-Driven Mean-Field Game Approximation for a Population of Electric VehiclesDario Bauso, Toru Namerikawa. 285-289 [doi]
• Statistical Learning Using Hierarchical Modeling of Probability TensorsMagda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos. 290-294 [doi]
• Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic DecompositionKejun Huang, Zhuoran Yang, Zhaoran Wang, Mingyi Hong. 295-299 [doi]
• Stochastic Optimization for Coupled Tensor Decomposition with Applications in Statistical LearningShahana Ibrahim, Xiao Fu. 300-304 [doi]
• Canonical Polyadic (CP) Decomposition of Structured Semi-Symmetric Fourth-Order TensorsAli Koochakzadeh, Piya Pal. 305-309 [doi]
• Recent Numerical and Conceptual Advances for Tensor Decompositions - A Preview of Tensorlab 4.0Nico Vervliet, Michiel Vandecappelle, Martijn Boussé, Rob Zink, Lieven De Lathauwer. 310-314 [doi]
• GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized OptimizationSongtao Lu, Xinwei Zhang, Haoran Sun, Mingyi Hong. 315-321 [doi]
• Byzantine-Robust Stochastic Gradient Descent for Distributed Low-Rank Matrix CompletionXuechao He, Qing Ling, Tianyi Chen. 322-326 [doi]
• Training Generative Networks Using Random DiscriminatorsBabak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi. 327-332 [doi]
• Deep Mimo Detection Using ADMM UnfoldingMan-Wai Un, Mingjie Shao, Wing-Kin Ma, P. C. Ching. 333-337 [doi]
• Comprehensive Personalized Ranking Using One-Bit Comparison DataAria Ameri, Arindam Bose, Mojtaba Soltanalian. 338-342 [doi]