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ORCIDSIAM Journal on Mathematics of Data Science, Volume 4
Volume 4, Number 1, March 2022
- Le Thi Khanh Hien
, Duy Nhat Phan, Nicolas Gillis, Masoud Ahookhosh, Panagiotis Patrinos:
Block Bregman Majorization Minimization with Extrapolation. 1-25 - Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus:
Sensitivity-Informed Provable Pruning of Neural Networks. 26-45 - Cole Hawkins, Xing Liu, Zheng Zhang:
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination. 46-71 - Anna V. Little, Daniel McKenzie, James M. Murphy:
Balancing Geometry and Density: Path Distances on High-Dimensional Data. 72-99 - Junteng Jia, Austin R. Benson:
A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations. 100-125 - Ningyuan Teresa Huang, David W. Hogg, Soledad Villar:
Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions. 126-152 - Michaël Fanuel, Antoine Aspeel, Jean-Charles Delvenne, Johan A. K. Suykens:
Positive Semi-definite Embedding for Dimensionality Reduction and Out-of-Sample Extensions. 153-178 - Jason M. Altschuler, Enric Boix-Adserà:
Wasserstein Barycenters Are NP-Hard to Compute. 179-203 - Anastasiya Belyaeva, Kaie Kubjas, Lawrence J. Sun, Caroline Uhler:
Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry. 204-228 - Florian Heinemann, Axel Munk, Yoav Zemel:
Randomized Wasserstein Barycenter Computation: Resampling with Statistical Guarantees. 229-259 - Ke Wang, Christos Thrampoulidis:
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization. 260-284 - Immanuel M. Bomze, Francesco Rinaldi, Damiano Zeffiro:
Fast Cluster Detection in Networks by First Order Optimization. 285-305 - Andreas Habring, Martin Holler:
A Generative Variational Model for Inverse Problems in Imaging. 306-335 - Haolin Chen, Luis Rademacher:
Overcomplete Order-3 Tensor Decomposition, Blind Deconvolution, and Gaussian Mixture Models. 336-361 - Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture Model. 362-385 - Perfect Y. Gidisu, Michiel E. Hochstenbach:
A Generalized CUR Decomposition for Matrix Pairs. 386-409 - Felix Dietrich, Or Yair, Rotem Mulayoff, Ronen Talmon, Ioannis G. Kevrekidis:
Spectral Discovery of Jointly Smooth Features for Multimodal Data. 410-430
Volume 4, Number 2, June 2022
- Lawrence K. Saul:
A Nonlinear Matrix Decomposition for Mining the Zeros of Sparse Data. 431-463 - Rahul Parhi, Robert D. Nowak:
What Kinds of Functions Do Deep Neural Networks Learn? Insights from Variational Spline Theory. 464-489 - Merle Behr, Axel Munk:
Statistical Methods for Minimax Estimation in Linear Models with Unknown Design Over Finite Alphabets. 490-513 - Armin Askari, Alexandre d'Aspremont, Laurent El Ghaoui:
Approximation Bounds for Sparse Programs. 514-530 - Eliza O'Reilly, Ngoc Mai Tran:
Stochastic Geometry to Generalize the Mondrian Process. 531-552 - Andrei Caragea, Dae Gwan Lee, Johannes Maly, Götz E. Pfander, Felix Voigtländer:
Quantitative Approximation Results for Complex-Valued Neural Networks. 553-580 - Howard Heaton, Samy Wu Fung, Alex Tong Lin, Stanley J. Osher, Wotao Yin:
Wasserstein-Based Projections with Applications to Inverse Problems. 581-603 - Martin Molina-Fructuoso, Ryan W. Murray:
Tukey Depths and Hamilton-Jacobi Differential Equations. 604-633 - Samuel Horváth, Lihua Lei, Peter Richtárik, Michael I. Jordan:
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization. 634-648 - Valentin Duruisseaux, Melvin Leok:
A Variational Formulation of Accelerated Optimization on Riemannian Manifolds. 649-674 - Markus Böck, Clemens Heitzinger:
Speedy Categorical Distributional Reinforcement Learning and Complexity Analysis. 675-693 - Yuqing Li, Tao Luo, Chao Ma:
Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for Neural Networks. 694-720 - Thomas Hamm, Ingo Steinwart:
Intrinsic Dimension Adaptive Partitioning for Kernel Methods. 721-749 - Axel Böhm, Michael Sedlmayer, Ernö Robert Csetnek, Radu Ioan Bot:
Two Steps at a Time - Taking GAN Training in Stride with Tseng's Method. 750-771 - François Bachoc, Andrés F. López-Lopera, Olivier Roustant:
Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints. 772-800 - Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett:
Autodifferentiable Ensemble Kalman Filters. 801-833 - Tong Zhang:
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning. 834-857 - Facundo Mémoli, Zhengchao Wan, Yusu Wang:
Persistent Laplacians: Properties, Algorithms and Implications. 858-884 - Yuege Xie, Hung-Hsu Chou, Holger Rauhut, Rachel A. Ward:
Overparameterization and Generalization Error: Weighted Trigonometric Interpolation. 885-908 - Pini Zilber, Boaz Nadler:
GNMR: A Provable One-Line Algorithm for Low Rank Matrix Recovery. 909-934 - Yue Xing, Qifan Song, Guang Cheng:
Benefit of Interpolation in Nearest Neighbor Algorithms. 935-956
Volume 4, Number 3, September 2022
- Justin Solomon, Kristjan H. Greenewald, Haikady N. Nagaraja:
$k$-Variance: A Clustered Notion of Variance. 957-978 - Mathieu Barré, Adrien B. Taylor, Alexandre d'Aspremont:
Convergence of a Constrained Vector Extrapolation Scheme. 979-1002 - Lea Bogensperger, Antonin Chambolle, Thomas Pock:
Convergence of a Piggyback-Style Method for the Differentiation of Solutions of Standard Saddle-Point Problems. 1003-1030 - Boyue Li, Zhize Li, Yuejie Chi:
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization. 1031-1051 - Yifeng Fan, Yuehaw Khoo, Zhizhen Zhao:
Joint Community Detection and Rotational Synchronization via Semidefinite Programming. 1052-1081 - March Boedihardjo, Thomas Strohmer, Roman Vershynin:
Private Sampling: A Noiseless Approach for Generating Differentially Private Synthetic Data. 1082-1115 - Abigail Hickok, Deanna Needell, Mason A. Porter:
Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data. 1116-1144 - Bastian Bohn, Michael Griebel, Dinesh Kannan:
Deep Neural Networks and PIDE Discretizations. 1145-1170 - Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens:
Determinantal Point Processes Implicitly Regularize Semiparametric Regression Problems. 1171-1190 - Marie Roald, Carla Schenker, Vince D. Calhoun, Tülay Adali, Rasmus Bro, Jeremy E. Cohen, Evrim Acar:
An AO-ADMM Approach to Constraining PARAFAC2 on All Modes. 1191-1222
Volume 4, Number 4, December 2022
- Martin Hanik, Hans-Christian Hege, Christoph von Tycowicz:
Bi-Invariant Dissimilarity Measures for Sample Distributions in Lie Groups. 1223-1249 - Alexander Dunlap, Jean-Christophe Mourrat:
Local Versions of Sum-of-Norms Clustering. 1250-1271 - Tao Luo, Zheng Ma, Zhi-Qin John Xu, Yaoyu Zhang:
On the Exact Computation of Linear Frequency Principle Dynamics and Its Generalization. 1272-1292 - Florian Maire, Pierre Vandekerkhove:
Markov Kernels Local Aggregation for Noise Vanishing Distribution Sampling. 1293-1319 - Philip A. Etter, Lexing Ying:
Operator Shifting for General Noisy Matrix Systems. 1320-1346 - Emmanuel Chevallier, Didong Li, Yulong Lu, David B. Dunson:
Exponential-Wrapped Distributions on Symmetric Spaces. 1347-1368 - Antonin Chambolle, Juan Pablo Contreras:
Accelerated Bregman Primal-Dual Methods Applied to Optimal Transport and Wasserstein Barycenter Problems. 1369-1395 - Sjoerd Dirksen, Shahar Mendelson, Alexander Stollenwerk:
Sharp Estimates on Random Hyperplane Tessellations. 1396-1419 - Boris Landa, Thomas T. C. K. Zhang, Yuval Kluger:
Biwhitening Reveals the Rank of a Count Matrix. 1420-1446 - Yehuda Dar, Richard G. Baraniuk:
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks. 1447-1472
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