Paper Title

Authors

SEMI-BLIND INFERENCE OF TOPOLOGIES AND SIGNALS OVER GRAPHS Vassilis N. Ioannidis, Yanning Shen, Georgios B. Giannakis, University of Minnesota, United States
THE MICHIGAN DATA SCIENCE TEAM: A DATA SCIENCE EDUCATION PROGRAM WITH SIGNIFICANT SOCIAL IMPACT Arya Farahi, Jonathan Stroud, University of Michigan – Ann Arbor, United States
A NOVEL ANOMALY DETECTOR IN BACKBONE NETWORK WITH SKETCH SPACE AND CLUSTERING Yating Liu, Yuantao Gu, Tsinghua University, China
AN EXPONENTIALLY CONVERGENT ALGORITHM FOR LEARNING UNDER DISTRIBUTED FEATURES Bicheng Ying, Yuan Kun, University of California, Los Angeles, Switzerland; Ali H. Sayed, Ecole Polytechique Federale de Lausanne, Switzerland
COMPUTATIONAL STRATEGIES FOR STATISTICAL INFERENCE BASED ON EMPIRICAL OPTIMAL TRANSPORT Carla Tameling, Axel Munk, University Goettingen, Germany
MOTIFNET: A MOTIF-BASED GRAPH CONVOLUTIONAL NETWORK FOR DIRECTED GRAPHS Federico Monti, Università della Svizzera italiana, Italy; Karl Otness, Harvard University, United States; Michael Bronstein, Università della Svizzera italiana, Switzerland
PROFIT MAXIMIZING LOGISTIC REGRESSION MODELING FOR CREDIT SCORING Arnout Devos, University of Southern California, United States; Jakob Dhondt, Switch, Switzerland; Eugen Stripling, Bart Baesens, Seppe vanden Broucke, KU Leuven, Belgium; Gaurav Sukhatme, University of Southern California, United States
ALTERNATING AUTOENCODERS FOR MATRIX COMPLETION Kiwon Lee, Yong H. Lee, Changho Suh, Korea Advanced Institute of Science and Technology (KAIST), Korea (South)
DISTRIBUTIONAL ROBUSTNESS FROM A CAUSAL POINT OF VIEW Nicolai Meinshausen, Seminar für Statistik, ETH Zurich, Switzerland
DIVIDE AND CONQUER TOMOGRAPHY FOR LARGE-SCALE NETWORKS Augusto Santos, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland; Vincenzo Matta, University of Salerno, Italy; Ali H. Sayed, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland
UNCERTAINTY QUANTIFICATION IN SUNSPOT COUNTS Sophie Mathieu, Rainer von Sachs, Université Catholique de Louvain, Belgium; Véronique Delouille, Laure Lefèvre, Royal Observatory of Belgium, Belgium
MATCHING CONVOLUTIONAL NEURAL NETWORKS WITHOUT PRIORS ABOUT DATA Carlos Eduardo Rosar Kos Lassance, IMT Atlantique, France; Jean-Charles Vialatte, IMT Atlantique / Cityzen Data, France; Vincent Gripon, IMT Atlantique, France
BYRDIE: A BYZANTINE-RESILIENT DISTRIBUTED LEARNING ALGORITHM Zhixiong Yang, Waheed Bajwa, Rutgers University, United States
SUBSAMPLING LEAST SQUARES AND ELEMENTAL ESTIMATION Keith Knight, University of Toronto, Canada
SUBGRADIENT PROJECTION OVER DIRECTED GRAPHS USING SURPLUS CONSENSUS Ran Xin, Chenguang Xi, Usman Khan, Tufts University, United States
AN EFFICIENT RECOMMENDER SYSTEM BY INTEGRATING NON-NEGATIVE MATRIX FACTORIZATION WITH TRUST AND DISTRUST RELATIONSHIPS Hashem Parvin, Parham Moradi, Shahrokh Esmaeili, University of Kurdistan, Iran; Nafiseh Imanian, Amirkabir University of Technology, Iran
ONLINE IDENTIFICATION OF DIRECTIONAL GRAPH TOPOLOGIES CAPTURING DYNAMIC AND NONLINEAR DEPENDENCIES Yanning Shen, Georgios B. Giannakis, University of Minnesota, United States
SPARSE ANOMALY REPRESENTATIONS IN VERY HIGH-DIMENSIONAL BRAIN SIGNAL Catherine Stamoulis, Harvard Medical School, United States
ON LEARNING LAPLACIANS OF TREE STRUCTURED GRAPHS Keng-Shih Lu, Eduardo Pavez, Antonio Ortega, University of Southern California, United States
ONLINE GRAPH LEARNING FROM SEQUENTIAL DATA Stefan Vlaski, Hermina Maretic, Roula Nassif, Pascal Frossard, Ali Sayed, EPFL, Switzerland
OPTIMIZING THERMAL COMFORT AND ENERGY CONSUMPTION IN A LARGE BUILDING WITHOUT RENOVATION WORK Sylvain Le Corff, CNRS, Université Paris-Sud, Université Paris Saclay, France; Alain Champagne, Maurice Charbit, Gilles Nozière, Oze-Energies, France; Eric Moulines, Centre de Mathématiques Appliquées, France
ROBUST AND CONSISTENT CLUSTERING RECOVERY VIA SDP APPROACHES Chenxi Sun, The University of Hong Kong, China; Tongxin Li, California Institute of Technology, United States; Victor O.K. Li, The University of Hong Kong, China
SPARSEST NETWORK SUPPORT ESTIMATION: A SUBMODULAR APPROACH Mario Coutino, Sundeep Prabhakar Chepuri, Geert Leus, TU Delft, Netherlands
SAVE – SPACE ALTERNATING VARIATIONAL ESTIMATION FOR SPARSE BAYESIAN LEARNING Christo Kurisummoottil Thomas, Dirk Slock, Eurecom, France
SUBSPACE DATA VISUALIZATION WITH DISSIMILARITY BASED ON PRINCIPAL ANGLE Xinyue Shen, Yuchen Jiao, Yuantao Gu, Tsinghua Univereity, China
SPECTRAL STATISTICS OF DIRECTED NETWORKS WITH RANDOM LINK MODEL TRANSPOSE-ASYMMETRY Stephen Kruzick, Jose M. F. Moura, Carnegie Mellon University, United States
PREDICTING ELECTRICITY OUTAGES CAUSED BY CONVECTIVE STORMS Roope Tervo, Joonas Karjalainen, Finnish Meteorological Institute, Finland; Alexander Jung, Aalto University, Finland
DIRECTED NETWORK TOPOLOGY INFERENCE VIA GRAPH FILTER IDENTIFICATION Rasoul Shafipour, University of Rochester, United States; Santiago Segarra, Massachusetts Institute of Technology, United States; Antonio Garcia Marques, King Juan Carlos University, Spain; Gonzalo Mateos, University of Rochester, United States
SEMI-SUPERVISED TRANSFER LEARNING USING MARGINAL PREDICTORS Aniket Deshmukh, University of Michigan, United States; Emil Laftchiev, Mitsubishi Electric Research Labs, United States
CONVOLUTIONAL NEURAL NETWORKS VIA NODE-VARYING GRAPH FILTERS Fernando Gama, University of Pennsylvania, United States; Geert Leus, Delft University of Technology, Netherlands; Antonio Marques, King Juan Carlos University, Spain; Alejandro Ribeiro, University of Pennsylvania, United States
ON GRAPH CONVOLUTION FOR GRAPH CNNS Jian Du, John Shi, Soummya Kar, Jose Moura, Carnegie Mellon University, United States
TOWARDS A SPECTRUM OF GRAPH CONVOLUTIONAL NETWORKS Mathias Niepert, Alberto Garcia-Duran, NEC Labs Europe, Germany
LEARNING FROM SIGNALS DEFINED OVER SIMPLICIAL COMPLEXES Sergio Barbarossa, Stefania Sardellitti, Elena Ceci, University of Rome, Italy
DISTRIBUTED NONPARAMETRIC DETECTION USING ONE-SAMPLE ANDERSON-DARLING TEST AND P-VALUE FUSION Topi Halme, Visa Koivunen, Aalto University, Finland
SPARSE SUBSPACE CLUSTERING WITH MISSING AND CORRUPTED DATA Zachary Charles, Amin Jalali, Rebecca Willett, University of Wisconsin-Madison, United States
LEARNING FLEXIBLE REPRESENTATIONS OF STOCHASTIC PROCESSES ON GRAPHS Addison Bohannon, Brian Sadler, US Army Research Laboratory, United States; Radu Balan, University of Maryland, United States
PREDICTIVE MAINTENANCE OF PHOTOVOLTAIC PANELS VIA DEEP LEARNING Timo Huuhtanen, Alexander Jung, Aalto University, Espoo, Finland, Finland
VECTOR COMPRESSION FOR SIMILARITY SEARCH USING MULTI-LAYER SPARSE TERNARY CODES Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov, University of Geneva, Switzerland
LEARNING TO INFER POWER GRID TOPOLOGIES: PERFORMANCE AND SCALABILITY Yue Zhao, Stony Brook University, United States; Jianshu Chen, Microsoft Research, United States; H. Vincent Poor, Princeton University, United States
SUBSPACE PRINCIPAL ANGLE PRESERVING PROPERTY OF GAUSSIAN RANDOM PROJECTION Yuchen Jiao, Xinyue Shen, Gen Li, Yuantao Gu, Tsinghua University, China
ENDMEMBER EXTRACTION ON THE GRASSMANNIAN Elin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson, Colorado State University, United States
AIM: AN ABSTRACTION FOR IMPROVING MACHINE LEARNING PREDICTION Victoria Stodden, Xiaomian Wu, University of Illinois Urbana-Champaign, United States; Vanessa Sochat, Stanford University, United States
MULTI-SCALE ALGORITHMS FOR OPTIMAL TRANSPORT Bernhard Schmitzer, WWU Münster, Germany
FALSE POSITIVE CONTROL WITH CONCAVE PENALTIES USING STABILITY SELECTION Bhanukiran Vinzamuri, Kush R. Varshney, IBM Research, United States
NEARLY OPTIMAL ROBUST SUBSPACE TRACKING: A UNIFIED APPROACH Praneeth Narayanamurthy, Namrata Vaswani, Iowa State University, United States
NETWORK INFERENCE FROM COMPLEX SYSTEMS STEADY STATES OBSERVATIONS : THEORY AND METHODS Hoi-To Wai, Anna Scaglione, Arizona State University, United States; Baruch Barzel, Amir Leshem, Bar-Ilan University, Israel
NON-NEGATIVE SUPER-RESOLUTION IS STABLE Armin Eftekhari, Alan Turing Institute, United Kingdom; Jared Tanner, Andrew Thompson, Bogdan Toader, Hemant Tyagi, University of Oxford, United Kingdom
DEEP CNN SPARSE CODING ANALYSIS: TOWARDS AVERAGE CASE Michael Murray, Jared Tanner, The Alan Turing Institute and The University of Oxford, United Kingdom
REVISED NOTE ON LEARNING QUADRATIC ASSIGNMENT WITH GRAPH NEURAL NETWORKS Alex Nowak, INRIA, Ecole Normale Superieure, France; Soledad Villar, Afonso Bandeira, Joan Bruna, New York University, United States
RESTRICTED ISOMETRY PROPERTY FOR LOW-DIMENSIONAL SUBSPACES AND ITS APPLICATION IN COMPRESSED SUBSPACE CLUSTERING Gen Li, Qinghua Liu, Yuantao Gu, Tsinghua University, China