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SIAM Journal on Mathematics of Data Science, Volume 6
Volume 6, Number 1, March 2024
- Hwanwoo Kim
, Daniel Sanz-Alonso, Ruiyi Yang
Optimization on Manifolds via Graph Gaussian Processes. 1-25 - Francis Bach:
High-Dimensional Analysis of Double Descent for Linear Regression with Random Projections. 26-50 - Alec Koppel, Joe Eappen, Sujay Bhatt, Cole Hawkins, Sumitra Ganesh:
Online MCMC Thinning with Kernelized Stein Discrepancy. 51-75 - Anatoli B. Juditsky
On Design of Polyhedral Estimates in Linear Inverse Problems. 76-96 - Elisa Negrini
Applications of No-Collision Transportation Maps in Manifold Learning. 97-126 - Michal Derezinski, Elizaveta Rebrova:
Sharp Analysis of Sketch-and-Project Methods via a Connection to Randomized Singular Value Decomposition. 127-153 - Haoyu Zhao, Konstantin Burlachenko, Zhize Li, Peter Richtárik
Faster Rates for Compressed Federated Learning with Client-Variance Reduction. 154-175 - Yi Yu, Oscar Hernan Madrid Padilla, Daren Wang, Alessandro Rinaldo:
Network Online Change Point Localization. 176-198 - Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk, Ryan J. Tibshirani:
Asymptotics of the Sketched Pseudoinverse. 199-225
Volume 6, Number 2, 2024
- Chiwei Yan
Efficiency of ETA Prediction. 227-253 - Tamir Bendory
The Sample Complexity of Sparse Multireference Alignment and Single-Particle Cryo-Electron Microscopy. 254-282 - YoonHaeng Hur
Reversible Gromov-Monge Sampler for Simulation-Based Inference. 283-310 - Adrien Vacher, Boris Muzellec, Francis R. Bach, François-Xavier Vialard, Alessandro Rudi:
Optimal Estimation of Smooth Transport Maps with Kernel SoS. 311-342 - Hao Liu
Learning Functions Varying along a Central Subspace. 343-371 - Yu Tian
Structural Balance and Random Walks on Complex Networks with Complex Weights. 372-399 - Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco
Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods. 400-427 - Stanislav Minsker
Robust and Tuning-Free Sparse Linear Regression via Square-Root Slope. 428-453 - Yehuda Dar, Daniel LeJeune, Richard G. Baraniuk:
The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression. 454-480 - Sinan G. Aksoy, Ilya Amburg
Scalable Tensor Methods for Nonuniform Hypergraphs. 481-503 - Stanislav Minsker
The Geometric Median and Applications to Robust Mean Estimation. 504-533 - Seonho Kim
Max-Affine Regression via First-Order Methods. 534-552 - Wenlong Mou, Nhat Ho, Martin J. Wainwright
A Diffusion Process Perspective on Posterior Contraction Rates for Parameters. 553-577
Volume 6, Number 3, 2024
- Matthias Beckmann, Nick Heilenkötter:
Equivariant Neural Networks for Indirect Measurements. 579-601
Volume 6, Number 4, 2024
- Changyu Liu, Yuling Jiao, Junhui Wang, Jian Huang
Nonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models. 847-868 - Semih Cayci
Finite-Time Analysis of Natural Actor-Critic for POMDPs. 869-896 - Andreas Habring, Martin Holler
Subgradient Langevin Methods for Sampling from Nonsmooth Potentials. 897-925 - Duy-Nhat Phan, Sedi Bartz, Nilabja Guha, Hung M. Phan:
Stochastic Variance-Reduced Majorization-Minimization Algorithms. 926-952 - Daniela Angela Parletta, Andrea Paudice
High Probability Bounds for Stochastic Subgradient Schemes with Heavy Tailed Noise]. 953-977 - Yifei Wang
Optimal Neural Network Approximation of Wasserstein Gradient Direction via Convex Optimization. 978-999 - Daniel W. Mimouni
Computing Wasserstein Barycenters via Operator Splitting: The Method of Averaged Marginals. 1000-1026 - Nelvin Tan, Pablo Pascual Cobo, Jonathan Scarlett, Ramji Venkataramanan
Approximate Message Passing with Rigorous Guarantees for Pooled Data and Quantitative Group Testing. 1027-1054
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