List of Accepted Papers

Following is the list of accepted DSW 2019 papers, sorted by paper title. You can use the search feature of your web browser to find your paper number. Notifications to all authors have also been sent by email. If you have not received your notification of the results by email, please contact us at dsw2019@cmsworkshops.com.

1098A Convolutional Neural Network Approach to Automated Lung Bounding Box Estimation from Computed Tomography Scans
1020A HIERARCHICAL APPROACH FOR TIMELY CYBERBULLYING DETECTION
1019A Stochastic LBFGS Algorithm for Radio Interferometric Calibration
1105ASSESSING THE RESILIENCE OF TEXAS POWER GRID NETWORK
1090Asynchronous Distributed Edge-Variant Graph Filters
1085BAYESIAN MULTIPLE HYPOTHESIS TESTING FOR DISTRIBUTED DETECTION IN SENSOR NETWORKS
1121BLIND ENSEMBLE CLASSIFICATION OF SEQUENTIAL DATA
1122BYZANTINE-ROBUST STOCHASTIC GRADIENT DECENT FOR DISTRIBUTED LOW-RANK MATRIX COMPLETION
1093Canonical Polyadic (CP) Decomposition of Structured Semi-Symmetric Fourth-Order Tensors
1044CENSORING-BASED DISTRIBUTED KERNEL LEARNING VIA RANDOM FEATURES
1077Classification of Hyperspectral Colon Cancer Images Using Convolutional Neural Networks
1036CLUSTERED GAUSSIAN GRAPHICAL MODEL VIA SYMMETRIC CONVEX CLUSTERING
1112Data Driven Measurement Matrix Learning for Sparse Reconstruction
1111Data-Driven Mean-Field Game Approximation for a Population of Electric Vehicles
1054DEEP ONE-CLASS CLASSIFICATION USING INTRA-CLASS SPLITTING
1061DISTANCE-PENALIZED ACTIVE LEARNING VIA MARKOV DECISION PROCESSES
1005DISTRIBUTED TRAINING WITH MOBILE AGENTS: OPTIMIZATION OVER DYNAMIC DIRECTED GRAPHS
1007DISTRIBUTION SYSTEM STATE ESTIMATION VIA DATA-DRIVEN AND PHYSICS-AWARE DEEP NEURAL NETWORKS
1017DYNAMIC FUNCTIONAL CONNECTIVITY USING HEAT KERNEL
1014ENHANCING MEDICAL IMAGING SEMANTIC SEGMENTATION USING THE DIGITAL ANNEALER
1063ESTIMATION OF STATE-SPACE MODELS WITH GAUSSIAN MIXTURE PROCESS NOISE
1043FINITE SAMPLE BOUNDS ON THE PERFORMANCE OF WEIGHTED LINEAR LEAST SQUARES IN SUB-GAUSSIAN CORRELATED NOISE
1022GENERALIZED JORDAN CENTER: A SOURCE LOCALIZATION HEURISTIC FOR NOISY AND INCOMPLETE OBSERVATIONS
1073GNSD: A Gradient-Tracking based Nonconvex Stochastic Algorithm for Decentralized Optimization
1081GRADIENT CODING WITH CLUSTERING AND MULTI-MESSAGE COMMUNICATION
1003Graph Topology Learning and Signal Recovery via Bayesian Inference
1099GRAPHICAL MODELS AND DYNAMIC LATENT FACTORS FOR MODELING FUNCTIONAL BRAIN CONNECTIVITY
1092INTRODUCING GRAPH SMOOTHNESS LOSS FOR TRAINING DEEP LEARNING ARCHITECTURES
1117KERNEL-BASED EFFICIENT LIFELONG LEARNING ALGORITHM
1028LEARNING PARTIALLY OBSERVABLE MARKOV DECISION PROCESSES USING COUPLED CANONICAL POLYADIC DECOMPOSITION
1011LEARNING TO DETECT AN ANOMALOUS TARGET WITH OBSERVATIONS FROM AN EXPONENTIAL FAMILY
1103LEARNING TO INFER VOLTAGE STABILITY MARGIN USING TRANSFER LEARNING
1071LEARNING TO REGULARIZE USING NEUMANN NETWORKS
1033LOCALIZATION OF DATA INJECTION ATTACKS ON DISTRIBUTED M-ESTIMATION
1100LONG-RANGE DEPENDENCE PARAMETER ESTIMATION FOR MIXED SPECTRA GAUSSIAN PROCESSES
1076MULTISPECTRAL SNAPSHOT DEMOSAICING VIA NON-CONVEX MATRIX COMPLETION
1059MULTITAPER ANALYSIS OF EVOLUTIONARY SPECTRAL DENSITY MATRIX FROM MULTIVARIATE SPIKING OBSERVATIONS
1057NON-NEGATIVE MATRIX FACTORIZATION OF CLUSTERED DATA WITH MISSING VALUES
1113NUMERICAL ANALYSIS OF RANDOMIZED ALGORITHMS FOR DATA-DRIVEN STABILIZATION
1047ON MODELING VOLTAGE PHASOR MEASUREMENTS AS GRAPH SIGNALS
1086Online Distributed Estimation of Principal Eigenspaces
1106ONLINE SELECTIVE TRAINING FOR FASTER NEURAL NETWORK LEARNING
1060ONLINE SPARSE SUBSPACE CLUSTERING
1080ONLINE TENSOR DECOMPOSITION AND IMPUTATION FOR COUNT DATA
1109Online Topology Inference from Streaming Stationary Graph Signals
1034OPTIMAL SAMPLING SETS IN COGRAPHS
1037RECENT NUMERICAL AND CONCEPTUAL ADVANCES FOR TENSOR DECOMPOSITIONS — A PREVIEW OF TENSORLAB 4.0
1091Recovery of Missing Data in Correlated Smart Grid Datasets
1041RUMOUR DETECTION VIA NEWS PROPAGATION DYNAMICS AND USER REPRESENTATION LEARNING
1009SAMPLING OF GRAPH SIGNALS WITH BLUE NOISE DITHERING
1129SCALABLE LEARNING WITH PRIVACY OVER GRAPHS
1123SEMI-SUPERVISED TRACKING OF DYNAMIC PROCESSES OVER SWITCHING GRAPHS
1023SIMULTANEOUS MULTIVARIATE OUTLIER AND TREND DETECTION
1065SPARSE AND FUNCTIONAL PRINCIPAL COMPONENTS ANALYSIS
1064SPLITTING METHODS FOR CONVEX BI-CLUSTERING AND CO-CLUSTERING
1025STATISTICAL LEARNING USING HIERARCHICAL MODELING OF PROBABILITY TENSORS
1055Stochastic Optimization for Coupled Tensor Decomposition with Applications in Statistical Learning
1094Structural Robustness for Deep Learning Architectures
1024SUPERVISED PRINCIPAL COMPONENT ANALYSIS VIA MANIFOLD OPTIMIZATION
1026THE CORE CONSISTENCY OF A COMPRESSED TENSOR
1102TIME-VARYING INTERACTION ESTIMATION USING ENSEMBLE METHODS
1126TRAINING GENERATIVE NETWORKS USING RANDOM DISCRIMINATORS
1110VERTEX-FREQUENCY CLUSTERING