OOIR: Observatory of International Research

Papers

(The median citation count of SIAM Journal on Mathematics of Data Science is 2. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)

Article	Citations
Scalable Semidefinite Programming	50
The Gap between Theory and Practice in Function Approximation with Deep Neural Networks	36
Implicit Deep Learning	35
Greed Works: An Improved Analysis of Sampling Kaczmarz--Motzkin	30
Persistent Laplacians: Properties, Algorithms and Implications	24
Nonbacktracking Eigenvalues under Node Removal: X-Centrality and Targeted Immunization	22
Autodifferentiable Ensemble Kalman Filters	18
On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case	18
Mean-Field Controls with Q-Learning for Cooperative MARL: Convergence and Complexity Analysis	16
What Kinds of Functions Do Deep Neural Networks Learn? Insights from Variational Spline Theory	15
Finite-Time Performance of Distributed Temporal-Difference Learning with Linear Function Approximation	15
Multi-Reference Alignment in High Dimensions: Sample Complexity and Phase Transition	14
An AO-ADMM Approach to Constraining PARAFAC2 on All Modes	13
Core-Periphery Detection in Hypergraphs	12
Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs	12
The Signature Kernel Is the Solution of a Goursat PDE	11
Simplex-Structured Matrix Factorization: Sparsity-Based Identifiability and Provably Correct Algorithms	11
Benefit of Interpolation in Nearest Neighbor Algorithms	11
Variational Representations and Neural Network Estimation of Rényi Divergences	10
An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs	10
Global Minima of Overparameterized Neural Networks	10
Matrix Denoising for Weighted Loss Functions and Heterogeneous Signals	10
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis	9
Two Steps at a Time---Taking GAN Training in Stride with Tseng's Method	9
Tensor Methods for Nonlinear Matrix Completion	9

Satisficing Paths and Independent Multiagent Reinforcement Learning in Stochastic Games	9
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection	9
A Generalized CUR Decomposition for Matrix Pairs	9
Wasserstein Barycenters Are NP-Hard to Compute	9
Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise	8
Interpretable Approximation of High-Dimensional Data	8
Multikernel Regression with Sparsity Constraint	8
Diversity Sampling is an Implicit Regularization for Kernel Methods	8
The Trimmed Lasso: Sparse Recovery Guarantees and Practical Optimization by the Generalized Soft-Min Penalty	8
A Generative Variational Model for Inverse Problems in Imaging	8
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination	8
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization	8
Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry	7
Randomized Wasserstein Barycenter Computation: Resampling with Statistical Guarantees	7
A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations	7
Post-training Quantization for Neural Networks with Provable Guarantees	7
Wasserstein-Based Projections with Applications to Inverse Problems	7
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition	7
Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture Model	6
Balancing Geometry and Density: Path Distances on High-Dimensional Data	6
Approximation of Lipschitz Functions Using Deep Spline Neural Networks	6
Semi-supervised Learning for Aggregated Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix-Vector Products	6
Rank $2r$ Iterative Least Squares: Efficient Recovery of Ill-Conditioned Low Rank Matrices from Few Entries	6
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization	5
Binary Component Decomposition Part I: The Positive-Semidefinite Case	5
Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data	5
An Optimal Algorithm for Strict Circular Seriation	5
Error Bounds for Dynamical Spectral Estimation	5
Biwhitening Reveals the Rank of a Count Matrix	5
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning	5
A Metric on Directed Graphs and Markov Chains Based on Hitting Probabilities	5
Approximate Spectral Gaps for Markov Chain Mixing Times in High Dimensions	5
A Variational Formulation of Accelerated Optimization on Riemannian Manifolds	5
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks	4
Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve	4
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning	4
Block Bregman Majorization Minimization with Extrapolation	4
On the Bias, Risk, and Consistency of Sample Means in Multi-armed Bandits	4
A Performance Guarantee for Spectral Clustering	4
Optimality Conditions for Nonsmooth Nonconvex-Nonconcave Min-Max Problems and Generative Adversarial Networks	4
GNMR: A Provable One-Line Algorithm for Low Rank Matrix Recovery	4
Private Sampling: A Noiseless Approach for Generating Differentially Private Synthetic Data	4
Accelerated Bregman Primal-Dual Methods Applied to Optimal Transport and Wasserstein Barycenter Problems	4
The Convex Mixture Distribution: Granger Causality for Categorical Time Series	4
Measuring Complexity of Learning Schemes Using Hessian-Schatten Total Variation	4
Fast Cluster Detection in Networks by First Order Optimization	4
Exponential-Wrapped Distributions on Symmetric Spaces	3
Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks	3
Time-Inhomogeneous Diffusion Geometry and Topology	3
Communication-Efficient Distributed Eigenspace Estimation	3

Stochastic Geometry to Generalize the Mondrian Process	3
Normal-Bundle Bootstrap	3
Sharp Estimates on Random Hyperplane Tessellations	3
Algorithmic Regularization in Model-Free Overparametrized Asymmetric Matrix Factorization	3
Convergence of Recursive Stochastic Algorithms Using Wasserstein Divergence	3
Deterministic Tensor Completion with Hypergraph Expanders	3
Consistency of Archetypal Analysis	3
Efficient Global Optimization of Two-Layer ReLU Networks: Quadratic-Time Algorithms and Adversarial Training	3
Approximation Properties of Ridge Functions and Extreme Learning Machines	3
Numerical Considerations and a new implementation for invariant coordinate selection	3
On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions	2
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization	2
Statistical Methods for Minimax Estimation in Linear Models with Unknown Design Over Finite Alphabets	2
Convergence of a Piggyback-Style Method for the Differentiation of Solutions of Standard Saddle-Point Problems	2
Joint Community Detection and Rotational Synchronization via Semidefinite Programming	2
Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms	2
Quantitative Approximation Results for Complex-Valued Neural Networks	2
On the Effectiveness of Richardson Extrapolation in Data Science	2
Tukey Depths and Hamilton--Jacobi Differential Equations	2
Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms	2
The GenCol Algorithm for High-Dimensional Optimal Transport: General Formulation and Application to Barycenters and Wasserstein Splines	2
Approximate Q Learning for Controlled Diffusion Processes and Its Near Optimality	2
Spectral Discovery of Jointly Smooth Features for Multimodal Data	2
Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling	2
Generalization Error of Minimum Weighted Norm and Kernel Interpolation	2
Adversarial Robustness of Sparse Local Lipschitz Predictors	2
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data	2
MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data	2
Accelerated and Instance-Optimal Policy Evaluation with Linear Function Approximation	2
Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints	2
LASSO Reloaded: A Variational Analysis Perspective with Applications to Compressed Sensing	2
A Simple and Optimal Algorithm for Strict Circular Seriation	2