OOIR: Observatory of International Research

Papers

(The TQCC of SIAM Journal on Mathematics of Data Science is 5. 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 2021-09-01 to 2025-09-01.)

Article	Citations
Spectral Barron Space for Deep Neural Network Approximation	35
A Simple and Optimal Algorithm for Strict Circular Seriation	26
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization	26
Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms	24
On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions	22
Efficient Algorithms for Regularized Nonnegative Scale-Invariant Low-Rank Approximation Models	21
Learning Functions Varying along a Central Subspace	19
Resolving the Mixing Time of the Langevin Algorithm to Its Stationary Distribution for Log-Concave Sampling	19
Block Majorization Minimization with Extrapolation and Application to ${\beta }$-NMF	15
Randomized Nyström Approximation of Non-negative Self-Adjoint Operators	15
A Note on the Regularity of Images Generated by Convolutional Neural Networks	14
New Equivalences between Interpolation and SVMs: Kernels and Structured Features	13
Poisson Reweighted Laplacian Uncertainty Sampling for Graph-Based Active Learning	12
Safe Rules for the Identification of Zeros in the Solutions of the SLOPE Problem	11
Persistent Laplacians: Properties, Algorithms and Implications	11
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning	11
Online Machine Teaching under Learner Uncertainty: Gradient Descent Learners of a Quadratic Loss	11
Quantitative Approximation Results for Complex-Valued Neural Networks	11
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature	10
Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs	10
Scalable Tensor Methods for Nonuniform Hypergraphs	10
Nonlinear Tomographic Reconstruction via Nonsmooth Optimization	10
Asymptotics of the Sketched Pseudoinverse	9
Convergence of a Piggyback-Style Method for the Differentiation of Solutions of Standard Saddle-Point Problems	9
Stochastic Variance-Reduced Majorization-Minimization Algorithms	9

Random Multitype Spanning Forests for Synchronization on Sparse Graphs	8
A Variational Formulation of Accelerated Optimization on Riemannian Manifolds	8
Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation	8
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities	8
The Sample Complexity of Sparse Multireference Alignment and Single-Particle Cryo-Electron Microscopy	8
The GenCol Algorithm for High-Dimensional Optimal Transport: General Formulation and Application to Barycenters and Wasserstein Splines	8
Bi-Invariant Dissimilarity Measures for Sample Distributions in Lie Groups	7
Group-Invariant Tensor Train Networks for Supervised Learning	7
Finite-Time Analysis of Natural Actor-Critic for POMDPs	7
A Nonlinear Matrix Decomposition for Mining the Zeros of Sparse Data	7
Benefit of Interpolation in Nearest Neighbor Algorithms	7
Supervised Gromov–Wasserstein Optimal Transport with Metric-Preserving Constraints	7
Optimal Dorfman Group Testing for Symmetric Distributions	6
Numerical Considerations and a new implementation for invariant coordinate selection	6
LASSO Reloaded: A Variational Analysis Perspective with Applications to Compressed Sensing	6
Efficient Identification of Butterfly Sparse Matrix Factorizations	6
Convergence of Gradient Descent for Recurrent Neural Networks: A Nonasymptotic Analysis	6
Computing Wasserstein Barycenters via Operator Splitting: The Method of Averaged Marginals	6
Post-training Quantization for Neural Networks with Provable Guarantees	6
The Geometric Median and Applications to Robust Mean Estimation	6
ABBA Neural Networks: Coping with Positivity, Expressivity, and Robustness	6
Adaptive Joint Distribution Learning	6
Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints	5
KL Convergence Guarantees for Score Diffusion Models under Minimal Data Assumptions	5
Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture Model	5
Optimality Conditions for Nonsmooth Nonconvex-Nonconcave Min-Max Problems and Generative Adversarial Networks	5
Randomized Wasserstein Barycenter Computation: Resampling with Statistical Guarantees	5
Operator Shifting for General Noisy Matrix Systems	5
Memory Capacity of Two Layer Neural Networks with Smooth Activations	5