OOIR: Observatory of International Research

Papers

(The TQCC of SIAM Journal on Mathematics of Data Science is 6. 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 2022-01-01 to 2026-01-01.)

Article	Citations
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization	43
A Simple and Optimal Algorithm for Strict Circular Seriation	31
Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms	30
Spectral Barron Space for Deep Neural Network Approximation	28
On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions	25
A Note on the Regularity of Images Generated by Convolutional Neural Networks	23
Randomized Nyström Approximation of Non-negative Self-Adjoint Operators	23
New Equivalences between Interpolation and SVMs: Kernels and Structured Features	22
Poisson Reweighted Laplacian Uncertainty Sampling for Graph-Based Active Learning	18
Block Majorization Minimization with Extrapolation and Application to ${\beta }$-NMF	17
Resolving the Mixing Time of the Langevin Algorithm to Its Stationary Distribution for Log-Concave Sampling	17
Learning Functions Varying along a Central Subspace	14
Efficient Algorithms for Regularized Nonnegative Scale-Invariant Low-Rank Approximation Models	14
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning	13
Deep Block Proximal Linearized Minimization Algorithm for Nonconvex Inverse Problems	13
Online Machine Teaching under Learner Uncertainty: Gradient Descent Learners of a Quadratic Loss	13
Nonlinear Tomographic Reconstruction via Nonsmooth Optimization	13
Quantitative Approximation Results for Complex-Valued Neural Networks	13
Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs	12
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature	11
Safe Rules for the Identification of Zeros in the Solutions of the SLOPE Problem	11
Nonlinear Meta-learning Can Guarantee Faster Rates	11
Persistent Laplacians: Properties, Algorithms and Implications	11
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities	10
Convergence of a Piggyback-Style Method for the Differentiation of Solutions of Standard Saddle-Point Problems	10

Stochastic Variance-Reduced Majorization-Minimization Algorithms	10
Scalable Tensor Methods for Nonuniform Hypergraphs	10
The GenCol Algorithm for High-Dimensional Optimal Transport: General Formulation and Application to Barycenters and Wasserstein Splines	9
Asymptotics of the Sketched Pseudoinverse	9
The Sample Complexity of Sparse Multireference Alignment and Single-Particle Cryo-Electron Microscopy	9
Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation	9
Covariance Alignment: From Maximum Likelihood Estimation to Gromov–Wasserstein	9
A Variational Formulation of Accelerated Optimization on Riemannian Manifolds	9
Group-Invariant Tensor Train Networks for Supervised Learning	9
Bi-Invariant Dissimilarity Measures for Sample Distributions in Lie Groups	8
Finite-Time Analysis of Natural Actor-Critic for POMDPs	8
The Geometric Median and Applications to Robust Mean Estimation	8
On Neural Network Approximation of Ideal Adversarial Attack and Convergence of Adversarial Training	8
Random Multitype Spanning Forests for Synchronization on Sparse Graphs	8
Convergence of Gradient Descent for Recurrent Neural Networks: A Nonasymptotic Analysis	7
Supervised Gromov–Wasserstein Optimal Transport with Metric-Preserving Constraints	7
ABBA Neural Networks: Coping with Positivity, Expressivity, and Robustness	7
Optimal Dorfman Group Testing for Symmetric Distributions	7
Benefit of Interpolation in Nearest Neighbor Algorithms	7
LASSO Reloaded: A Variational Analysis Perspective with Applications to Compressed Sensing	7
Post-training Quantization for Neural Networks with Provable Guarantees	7
A Nonlinear Matrix Decomposition for Mining the Zeros of Sparse Data	7
Numerical Considerations and a new implementation for invariant coordinate selection	7
Computing Wasserstein Barycenters via Operator Splitting: The Method of Averaged Marginals	7
Efficient Identification of Butterfly Sparse Matrix Factorizations	7
Operator Shifting for General Noisy Matrix Systems	6
Adaptive Joint Distribution Learning	6
Complete and Continuous Invariants of 1-Periodic Sequences in Polynomial Time	6
Robust Classification Under $\ell_0$ Attack for the Gaussian Mixture Model	6
Phase Retrieval with Semialgebraic and ReLU Neural Network Priors	6
Randomized Wasserstein Barycenter Computation: Resampling with Statistical Guarantees	6
Memory Capacity of Two Layer Neural Networks with Smooth Activations	6