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 2020-04-01 to 2024-04-01.)

Article	Citations
Scalable Semidefinite Programming	44
The Gap between Theory and Practice in Function Approximation with Deep Neural Networks	29
Implicit Deep Learning	26
Greed Works: An Improved Analysis of Sampling Kaczmarz--Motzkin	22
Nonbacktracking Eigenvalues under Node Removal: X-Centrality and Targeted Immunization	19
Persistent Laplacians: Properties, Algorithms and Implications	19
Multi-Reference Alignment in High Dimensions: Sample Complexity and Phase Transition	15
On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case	13
What Kinds of Functions Do Deep Neural Networks Learn? Insights from Variational Spline Theory	13
Finite-Time Performance of Distributed Temporal-Difference Learning with Linear Function Approximation	12
Autodifferentiable Ensemble Kalman Filters	12
Mean-Field Controls with Q-Learning for Cooperative MARL: Convergence and Complexity Analysis	12
Core-Periphery Detection in Hypergraphs	9
Matrix Denoising for Weighted Loss Functions and Heterogeneous Signals	9
Benefit of Interpolation in Nearest Neighbor Algorithms	9
Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs	9
The Signature Kernel Is the Solution of a Goursat PDE	9
Simplex-Structured Matrix Factorization: Sparsity-Based Identifiability and Provably Correct Algorithms	8
Diversity Sampling is an Implicit Regularization for Kernel Methods	8
Multikernel Regression with Sparsity Constraint	8
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis	7
Global Minima of Overparameterized Neural Networks	7
Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise	7
Two Steps at a Time---Taking GAN Training in Stride with Tseng's Method	7
Tensor Methods for Nonlinear Matrix Completion	7

An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs	7
Variational Representations and Neural Network Estimation of Rényi Divergences	7
A Generative Variational Model for Inverse Problems in Imaging	6
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization	6
Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination	6
Semi-supervised Learning for Aggregated Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix-Vector Products	6
An AO-ADMM Approach to Constraining PARAFAC2 on All Modes	6
Wasserstein Barycenters Are NP-Hard to Compute	6
Error Bounds for Dynamical Spectral Estimation	5
A Variational Formulation of Accelerated Optimization on Riemannian Manifolds	5
The Trimmed Lasso: Sparse Recovery Guarantees and Practical Optimization by the Generalized Soft-Min Penalty	5
Approximation of Lipschitz Functions Using Deep Spline Neural Networks	5
A Generalized CUR Decomposition for Matrix Pairs	5
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks	5
Interpretable Approximation of High-Dimensional Data	5
Post-training Quantization for Neural Networks with Provable Guarantees	5
Rank $2r$ Iterative Least Squares: Efficient Recovery of Ill-Conditioned Low Rank Matrices from Few Entries	5
Identifying 3D Genome Organization in Diploid Organisms via Euclidean Distance Geometry	5
Binary Component Decomposition Part I: The Positive-Semidefinite Case	5
An Optimal Algorithm for Strict Circular Seriation	5
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection	5
Balancing Geometry and Density: Path Distances on High-Dimensional Data	4
A Performance Guarantee for Spectral Clustering	4
A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations	4
Randomized Wasserstein Barycenter Computation: Resampling with Statistical Guarantees	4
Satisficing Paths and Independent Multiagent Reinforcement Learning in Stochastic Games	4
Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture Model	4
Block Bregman Majorization Minimization with Extrapolation	4
Wasserstein-Based Projections with Applications to Inverse Problems	4
Biwhitening Reveals the Rank of a Count Matrix	4
The Convex Mixture Distribution: Granger Causality for Categorical Time Series	4
Approximate Spectral Gaps for Markov Chain Mixing Times in High Dimensions	3
Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve	3
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization	3
On the Bias, Risk, and Consistency of Sample Means in Multi-armed Bandits	3
Exponential-Wrapped Distributions on Symmetric Spaces	3
Deterministic Tensor Completion with Hypergraph Expanders	3
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning	3
A Metric on Directed Graphs and Markov Chains Based on Hitting Probabilities	3
Accelerated Bregman Primal-Dual Methods Applied to Optimal Transport and Wasserstein Barycenter Problems	3
Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data	3
Communication-Efficient Distributed Eigenspace Estimation	3
Time-Inhomogeneous Diffusion Geometry and Topology	2
On the Effectiveness of Richardson Extrapolation in Data Science	2
Generalization Error of Minimum Weighted Norm and Kernel Interpolation	2
Measuring Complexity of Learning Schemes Using Hessian-Schatten Total Variation	2
The GenCol Algorithm for High-Dimensional Optimal Transport: General Formulation and Application to Barycenters and Wasserstein Splines	2
Convergence of a Piggyback-Style Method for the Differentiation of Solutions of Standard Saddle-Point Problems	2
Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints	2
Quantitative Approximation Results for Complex-Valued Neural Networks	2

Fast Cluster Detection in Networks by First Order Optimization	2
Private Sampling: A Noiseless Approach for Generating Differentially Private Synthetic Data	2
Stochastic Geometry to Generalize the Mondrian Process	2
Consistency of Archetypal Analysis	2
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning	2
Joint Community Detection and Rotational Synchronization via Semidefinite Programming	2
Algorithmic Regularization in Model-Free Overparametrized Asymmetric Matrix Factorization	2
Convergence of Recursive Stochastic Algorithms Using Wasserstein Divergence	2
A Simple and Optimal Algorithm for Strict Circular Seriation	2
MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data	2
Sharp Estimates on Random Hyperplane Tessellations	2