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 2022-05-01 to 2026-05-01.)

Article	Citations
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization	45
Spectral Barron Space for Deep Neural Network Approximation	35
A Simple and Optimal Algorithm for Strict Circular Seriation	34
Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms	33
A Note on the Regularity of Images Generated by Convolutional Neural Networks	28
New Equivalences between Interpolation and SVMs: Kernels and Structured Features	22
Quantitative Approximation Results for Complex-Valued Neural Networks	20
Learning Functions Varying along a Central Subspace	19
Block Majorization Minimization with Extrapolation and Application to \({\beta }\)-NMF	17
Deep Block Proximal Linearized Minimization Algorithm for Nonconvex Inverse Problems	17
Efficient Algorithms for Regularized Nonnegative Scale-Invariant Low-Rank Approximation Models	14
Randomized Nyström Approximation of Non-negative Self-Adjoint Operators	14
Poisson Reweighted Laplacian Uncertainty Sampling for Graph-Based Active Learning	14
On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions	14
Resolving the Mixing Time of the Langevin Algorithm to Its Stationary Distribution for Log-Concave Sampling	13
Nonlinear Tomographic Reconstruction via Nonsmooth Optimization	12
Online Machine Teaching under Learner Uncertainty: Gradient Descent Learners of a Quadratic Loss	12
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning	11
Safe Rules for the Identification of Zeros in the Solutions of the SLOPE Problem	11
Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs	11
Persistent Laplacians: Properties, Algorithms and Implications	11
Scalable Tensor Methods for Nonuniform Hypergraphs	10
Convergence of a Piggyback-Style Method for the Differentiation of Solutions of Standard Saddle-Point Problems	10
Covariance Alignment: From Maximum Likelihood Estimation to Gromov–Wasserstein	9
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities	9

Stochastic Variance-Reduced Majorization-Minimization Algorithms	9
A Notion of Uniqueness for the Adversarial Bayes Classifier	9
Nonlinear Meta-learning Can Guarantee Faster Rates	9
Asymptotics of the Sketched Pseudoinverse	9
Learning Memory Kernels in Generalized Langevin Equations	9
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature	9
The Sample Complexity of Sparse Multireference Alignment and Single-Particle Cryo-Electron Microscopy	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	8
Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation	8
Bi-Invariant Dissimilarity Measures for Sample Distributions in Lie Groups	8
A Variational Formulation of Accelerated Optimization on Riemannian Manifolds	8
Group-Invariant Tensor Train Networks for Supervised Learning	8
The GenCol Algorithm for High-Dimensional Optimal Transport: General Formulation and Application to Barycenters and Wasserstein Splines	8
Efficient Identification of Butterfly Sparse Matrix Factorizations	7
Benefit of Interpolation in Nearest Neighbor Algorithms	7
Supervised Gromov–Wasserstein Optimal Transport with Metric-Preserving Constraints	7
The Geometric Median and Applications to Robust Mean Estimation	7
Numerical Considerations and a new implementation for invariant coordinate selection	7
ABBA Neural Networks: Coping with Positivity, Expressivity, and Robustness	7
Finite-Time Analysis of Natural Actor-Critic for POMDPs	7
Optimal Dorfman Group Testing for Symmetric Distributions	7
Post-training Quantization for Neural Networks with Provable Guarantees	6
LASSO Reloaded: A Variational Analysis Perspective with Applications to Compressed Sensing	6
Operator Shifting for General Noisy Matrix Systems	6
Computing Wasserstein Barycenters via Operator Splitting: The Method of Averaged Marginals	6
KL Convergence Guarantees for Score Diffusion Models under Minimal Data Assumptions	5
Sequential Construction and Dimension Reduction of Gaussian Processes Under Inequality Constraints	5
Phase Retrieval with Semialgebraic and ReLU Neural Network Priors	5
HADES: Fast Singularity Detection with Local Measure Comparison	5
Complete and Continuous Invariants of 1-Periodic Sequences in Polynomial Time	5
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning	5
Adaptive Joint Distribution Learning	5
Memory Capacity of Two Layer Neural Networks with Smooth Activations	5