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2019

IEEE Data Science Workshop, DSW 2019, Minneapolis, MN, USA, June 2-5, 2019IEEE, 2019. [doi]

Sparse and Functional Principal Components AnalysisGenevera I. Allen, Michael Weylandt. dsw 2019: 11-16 [doi]

Comprehensive Personalized Ranking Using One-Bit Comparison DataAria Ameri, Arindam Bose, Mojtaba Soltanalian. dsw 2019: 338-342 [doi]

Statistical Learning Using Hierarchical Modeling of Probability TensorsMagda Amiridi, Nikos Kargas, Nicholas D. Sidiropoulos. dsw 2019: 290-294 [doi]

Multispectral Snapshot Demosaicing Via Non-Convex Matrix CompletionGiancarlo A. Antonucci, Simon Vary, David Humphreys, Robert A. Lamb, Jonathan Piper, Jared Tanner. dsw 2019: 227-231 [doi]

Long-Range Dependence Parameter Estimation For Mixed Spectra Gaussian ProcessesLenin Arango-Castillo, Glen Takahara. dsw 2019: 120-124 [doi]

Training Generative Networks Using Random DiscriminatorsBabak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi. dsw 2019: 327-332 [doi]

Data-Driven Mean-Field Game Approximation for a Population of Electric VehiclesDario Bauso, Toru Namerikawa. dsw 2019: 285-289 [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. dsw 2019: 160-164 [doi]

Vertex-Frequency ClusteringDaniel B. Burkhardt, Jay S. Stanley III, Guy Wolf, Smita Krishnaswamy. dsw 2019: 145-149 [doi]

Graphical Models and Dynamic Latent Factors for Modeling Functional Brain ConnectivityAndersen Chang, Tianyi Yao, Genevera I. Allen. dsw 2019: 57-63 [doi]

Non-Negative Matrix Factorization of Clustered Data with Missing ValuesRebecca Chen, Lav R. Varshney. dsw 2019: 180-184 [doi]

Asynchronous Distributed Edge-Variant Graph FiltersMario Coutino, Geert Leus. dsw 2019: 115-119 [doi]

Rumour Detection Via News Propagation Dynamics and User Representation LearningTien Huu Do, Xiao Luo, Duc-Minh Nguyen, Nikos Deligiannis. dsw 2019: 196-200 [doi]

Randomized Algorithms for Data-Driven Stabilization of Stochastic Linear SystemsMohamad Kazem Shirani Faradonbeh, Ambuj Tewari, George Michailidis. dsw 2019: 170-174 [doi]

Recovery of Missing Data in Correlated Smart Grid DatasetsCristian Genes, Iñaki Esnaola, Samir Medina Perlaza, Daniel Coca. dsw 2019: 263-269 [doi]

Learning to Regularize Using Neumann NetworksDavis Gilton, Greg Ongie, Rebecca Willett. dsw 2019: 201-207 [doi]

Optimal Sampling Sets in CographsDominique Guillot, Alejandro Parada-Mayorga, Sebastian Cioaba, Gonzalo R. Arce. dsw 2019: 165-169 [doi]

Bayesian Multiple Hypothesis Testing For Distributed Detection In Sensor NetworksTopi Halme, Martin Golz, Visa Koivunen. dsw 2019: 105-109 [doi]

A Convolutional Neural Network Approach to Automated Lung Bounding Box Estimation from Computed Tomography ScansCharles R. Hatt, Sundaresh Ram, Craig J. Galbán. dsw 2019: 213-216 [doi]

Byzantine-Robust Stochastic Gradient Descent for Distributed Low-Rank Matrix CompletionXuechao He, Qing Ling, Tianyi Chen. dsw 2019: 322-326 [doi]

Dynamic Functional Connectivity Using Heat KernelShih-Gu Huang, Moo K. Chung, Ian C. Carroll, H. Hill Goldsmith. dsw 2019: 222-226 [doi]

Learning Partially Observable Markov Decision Processes Using Coupled Canonical Polyadic DecompositionKejun Huang, Zhuoran Yang, Zhaoran Wang, Mingyi Hong. dsw 2019: 295-299 [doi]

Stochastic Optimization for Coupled Tensor Decomposition with Applications in Statistical LearningShahana Ibrahim, Xiao Fu. dsw 2019: 300-304 [doi]

Kernel-Based Efficient Lifelong Learning AlgorithmSeung-Jun Kim, Rami Mowakeaa. dsw 2019: 175-179 [doi]

Canonical Polyadic (CP) Decomposition of Structured Semi-Symmetric Fourth-Order TensorsAli Koochakzadeh, Piya Pal. dsw 2019: 305-309 [doi]

Lfinite Sample Bounds on the Performance of Weighted Linear Least Squares in Sub-Gaussian Correlated NoiseMichael Krikheli, Amir Leshem. dsw 2019: 110-114 [doi]

Structural Robustness for Deep Learning ArchitecturesCarlos Eduardo Rosar Kós Lassance, Vincent Gripon, Jian Tang, Antonio Ortega. dsw 2019: 125-129 [doi]

Learning to Infer Voltage Stability Margin Using Transfer LearningJiaming Li, Yue Zhao, Young Hwan Lee, Seung-Jun Kim. dsw 2019: 270-274 [doi]

GNSD: a Gradient-Tracking Based Nonconvex Stochastic Algorithm for Decentralized OptimizationSongtao Lu, Xinwei Zhang, Haoran Sun, Mingyi Hong. dsw 2019: 315-321 [doi]

Semi-Supervised Tracking of Dynamic Processes Over Switching GraphsQin Lu, Vassilis N. Ioannidis, Georgios B. Giannakis. dsw 2019: 64-68 [doi]

Online Sparse Subspace ClusteringLiam Madden, Stephen Becker, Emiliano Dall'Anese. dsw 2019: 248-252 [doi]

Graph Topology Learning and Signal Recovery Via Bayesian InferenceMahmoud Ramezani Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Rick S. Blum, H. Vincent Poor. dsw 2019: 52-56 [doi]

Estimation of State-Space Models with Gaussian Mixture Process NoiseSina Miran, Jonathan Z. Simon, Michael C. Fu, Steven I. Marcus, Behtash Babadi. dsw 2019: 185-189 [doi]

Classification of Hyperspectral Colon Cancer Images Using Convolutional Neural NetworksSean Mobilia, Birsen Sirkeci Mergen, Joshua Deal, Thomas C. Rich, Silas J. Leavesley. dsw 2019: 232-236 [doi]

Online selective training for faster neural network learningSara Mourad, Haris Vikalo, Ahmed H. Tewfik. dsw 2019: 135-139 [doi]

A Hierarchical Approach for Timely Cyberbullying DetectionImara Nazar, Daphney-Stavroula Zois, Mengfan Yao. dsw 2019: 190-195 [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. dsw 2019: 280-284 [doi]

Time-Varying Interaction Estimation Using Ensemble MethodsBrandon Oselio, Alfred Hero, Amir Sadeghian, Silvio Savarese. dsw 2019: 69-75 [doi]

Gradient Coding with Clustering and Multi-Message CommunicationEmre Ozfatura, Deniz Gündüz, Sennur Ulukus. dsw 2019: 42-46 [doi]

Sampling of Graph Signals with Blue Noise DitheringAlejandro Parada-Mayorga, Daniel L. Lau, Jhony H. Giraldo, Gonzalo R. Arce. dsw 2019: 150-154 [doi]

Simultaneous Multivariate Outlier and Trend DetectionKarl Pazdernik, Bryan Stanfill, Lisa Bramer, Kellie J. MacPhee. dsw 2019: 93-99 [doi]

Learning to Detect an Anomalous Target with Observations from an Exponential FamilyGayathri R. Prabhu, Srikrishna Bhashyam, Aditya Gopalan, Rajesh Sundaresan. dsw 2019: 88-92 [doi]

Data Driven Measurement Matrix Learning for Sparse ReconstructionRobiul Hossain Md. Rafi, Ali Cafer Gürbüz. dsw 2019: 253-257 [doi]

On Modeling Voltage Phasor Measurements as Graph SignalsRaksha Ramakrishna, Anna Scaglione. dsw 2019: 275-279 [doi]

Supervised Principal Component Analysis Via Manifold OptimizationAlexander Ritchie, Clayton D. Scott, Laura Balzano, Daniel Kessler, Chandra Sekhar Sripada. dsw 2019: 6-10 [doi]

Multitaper Analysis of Evolutionary Spectral Density Matrix From Multivariate Spiking ObservationsAnuththara Rupasinghe, Behtash Babadi. dsw 2019: 47-51 [doi]

Distributed Training with Mobile Agents: Optimization Over Dynamic Directed GraphsFakhteh Saadatniaki, Ran Xin, Usman A. Khan. dsw 2019: 37-41 [doi]

Deep One-Class Classification Using Intra-Class SplittingPatrick Schlachter, Yiwen Liao, Bin Yang. dsw 2019: 100-104 [doi]

Online Topology Inference from Streaming Stationary Graph SignalsRasoul Shafipour, Abolfazl Hashemi, Gonzalo Mateos, Haris Vikalo. dsw 2019: 140-144 [doi]

Localization of Data Injection Attacks on Distributed M-EstimationOr Shalom, Amir Leshem, Anna Scaglione. dsw 2019: 22-26 [doi]

Scalable Learning with Privacy Over GraphsYanning Shen, Geert Leus. dsw 2019: 83-87 [doi]

Online Distributed Estimation of Principal EigenspacesDavoud Ataee Tarzanagh, Mohamad Kazem Shirani Faradonbeh, George Michailidis. dsw 2019: 27-31 [doi]

Blind Ensemble Classification of Sequential DataPanagiotis A. Traganitis. dsw 2019: 130-134 [doi]

The Core Consistency of a Compressed TensorGeorgios Tsitsikas, Evangelos E. Papalexakis. dsw 2019: 1-5 [doi]

Deep Mimo Detection Using ADMM UnfoldingMan-Wai Un, Mingjie Shao, Wing-Kin Ma, P. C. Ching. dsw 2019: 333-337 [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. dsw 2019: 310-314 [doi]

Distance-Penalized Active Learning via Markov Decision ProcessesDingyu Wang, John Lipor, Gautam Dasarathy. dsw 2019: 155-159 [doi]

Enhancing Medical Imaging Semantic Segmentation Using the Digital AnnealerJiankun Wang, Shahrokh Valaee. dsw 2019: 217-221 [doi]

Splitting Methods For Convex Bi-Clustering And Co-ClusteringMichael Weylandt. dsw 2019: 237-242 [doi]

Coke: Communication-Censored Kernel Learning Via Random FeaturesPing Xu, Zhi Tian, Zhe Zhang, Yue Wang. dsw 2019: 32-36 [doi]

Clustered Gaussian Graphical Model Via Symmetric Convex ClusteringTianyi Yao, Genevera I. Allen. dsw 2019: 76-82 [doi]

A Stochastic LBFGS Algorithm for Radio Interferometric CalibrationSarod Yatawatta, Lukas De Clercq, Hanno Spreeuw, Faruk Diblen. dsw 2019: 208-212 [doi]

Online Tensor Decomposition and Imputation for Count DataChang Ye, Gonzalo Mateos. dsw 2019: 17-21 [doi]

Distribution System State Estimation Via Data-Driven and Physics-Aware Deep Neural NetworksLiang Zhang, Gang Wang 0014, Georgios B. Giannakis. dsw 2019: 258-262 [doi]

Generalized Jordan Center: A Source Localization Heuristic For Noisy And Incomplete ObservationsHuozhi Zhou, Ashish Jagmohan, Lav R. Varshney. dsw 2019: 243-247 [doi]

2018

2018 IEEE Data Science Workshop, DSW 2018, Lausanne, Switzerland, June 4-6, 2018IEEE, 2018. [doi]

Learning Flexible Representations of Stochastic Processes on GraphsAddison W. Bohannon, Brian M. Sadler, Radu V. Balan. dsw 2018: 61-65 [doi]

Sparse Subspace Clustering with Missing and Corrupted DataZachary Charles, Amin Jalali 0004, Rebecca Willett. dsw 2018: 180-184 [doi]

Semi-Supervised Transfer Learning Using Marginal PredictorsAniket Anand Deshmukh, Emil Laftchiev. dsw 2018: 160-164 [doi]

Profit Maximizing Logistic Regression Modeling for Credit ScoringArnout Devos, Jakob Dhondt, Eugen Stripling, Bart Baesens, Seppe Vanden Broucke, Gaurav Sukhatme. dsw 2018: 125-129 [doi]

Non-Negative Super-Resolution is StableArmin Eftekhari, Jared Tanner, Andrew Thompson 0001, Bogdan Toader, Hemant Tyagi. dsw 2018: 100-104 [doi]

The Michigan Data Science Team: A Data Science Education Program with Significant Social ImpactArya Farahi, Jonathan C. Stroud. dsw 2018: 120-124 [doi]

Endmember Extraction on the GrassmannianElin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson. dsw 2018: 71-75 [doi]

Vector Compression for Similarity Search Using Multi-Layer Sparse Ternary CodesSohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov. dsw 2018: 110-114 [doi]

Distributed Nonparametric Inference Using a One-Sample Bootstrapped Anderson-Darling Test and P-Value FusionTopi Halme, Visa Koivunen. dsw 2018: 56-60 [doi]

Predictive Maintenance of Photovoltaic Panels via Deep LearningTimo Huuhtanen, Alexander Jung. dsw 2018: 66-70 [doi]

Subsampling Least Squares and Elemental EstimationKeith Knight. dsw 2018: 91-94 [doi]

Matching Convolutional Neural Networks without Priors about DataCarlos Eduardo Rosar Kós Lassance, Jean-Charles Vialatte, Vincent Gripon. dsw 2018: 234-238 [doi]

Alternating Autoencoders for Matrix CompletionKiwon Lee, Yong-Hoon Lee, Changho Suh. dsw 2018: 130-134 [doi]

On Learning Laplacians of Tree Structured GraphsKeng-Shih Lu, Eduardo Pavez, Antonio Ortega. dsw 2018: 205-209 [doi]

Uncertainty Quantification in Sunspot CountsSophie Mathieu, Rainer von Sachs, Véronique Delouille, Laure Lefevre. dsw 2018: 36-40 [doi]

Causality from a Distributional Robustness Point of ViewNicolai Meinshausen. dsw 2018: 6-10 [doi]

MOTIFNET: A Motif-Based Graph Convolutional Network for Directed GraphsFederico Monti, Karl Otness, Michael M. Bronstein. dsw 2018: 225-228 [doi]

Deep CNN Sparse Coding Analysis: Towards Average CaseMichael Murray, Jared Tanner. dsw 2018: 95-99 [doi]

Nearly Optimal Robust Subspace Tracking: A Unified ApproachPraneeth Narayanamurthy, Namrata Vaswani. dsw 2018: 81-85 [doi]

Towards a Spectrum of Graph Convolutional NetworksMathias Niepert, Alberto García-Durán. dsw 2018: 244-248 [doi]

Revised Note on Learning Quadratic Assignment with Graph Neural NetworksAlex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna. dsw 2018: 229-233 [doi]

An Efficient Recommender System by Integrating Non-Negative Matrix Factorization with Trust and Distrust RelationshipsHashem Parvin, Parham Moradi, Shahrokh Esmaeili, Mahdi Jalili. dsw 2018: 135-139 [doi]

Divide-and-Conquer Tomography for Large-Scale NetworksAugusto Santos, Vincenzo Matta, Ali H. Sayed. dsw 2018: 170-174 [doi]

Multi-Scale Algorithms for Optimal TransportBernhard Schmitzer. dsw 2018: 1-5 [doi]

Sparse Anomaly Representations in Very High-Dimensional Brain SignalsCatherine Stamoulis. dsw 2018: 140-144 [doi]

AIM: An Abstraction for Improving Machine Learning PredictionVictoria Stodden, Xiaomian Wu, Vanessa Sochat. dsw 2018: 150-154 [doi]

Robust and Consistent Clustering Recovery via SDP ApproachesChenxi Sun, Tongxin Li, Victor O. K. Li. dsw 2018: 46-50 [doi]

Computational Strategies for Statistical Inference Based on Empirical Optimal TransportCarla Tameling, Axel Munk. dsw 2018: 175-179 [doi]

Predicting Electricity Outages Caused By Convective StormsRoope Tervo, Joonas Karjalainen, Alexander Jung. dsw 2018: 145-149 [doi]

False Discovery Rate Control with Concave Penalties Using Stability SelectionBhanukiran Vinzamuri, Kush R. Varshney. dsw 2018: 76-80 [doi]

Network Inference from Complex Systems Steady States Observations: Theory and MethodsHoi-To Wai, Anna Scaglione, Baruch Barzel, Amir Leshem. dsw 2018: 155-159 [doi]

Subgradient Projection Over Directed Graphs Using Surplus ConsensusRan Xin, Chenguang Xi, Usman A. Khan. dsw 2018: 105-109 [doi]

BYRDIE: A Byzantine-Resilient Distributed Learning AlgorithmZhiXiong Yang, Waheed U. Bajwa. dsw 2018: 21-25 [doi]

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