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ORCIDSIAM Journal on Mathematics of Data Science, Volume 3
Volume 3, Number 1, 2021
- Braxton Osting
, Dong Wang, Yiming Xu, Dominique Zosso:
Consistency of Archetypal Analysis. 1-30 - Amitabh Basu, Tu Nguyen, Ao Sun:
Admissibility of Solution Estimators for Stochastic Optimization. 31-51 - Valentin De Bortoli, Agnès Desolneux, Alain Durmus, Bruno Galerne, Arthur Leclaire:
Maximum Entropy Methods for Texture Synthesis: Theory and Practice. 52-82 - Alex Tank, Xiudi Li, Emily B. Fox, Ali Shojaie:
The Convex Mixture Distribution: Granger Causality for Categorical Time Series. 83-112 - Ariel Jaffe, Noah Amsel, Yariv Aizenbud, Boaz Nadler, Joseph T. Chang, Yuval Kluger:
Spectral Neighbor Joining for Reconstruction of Latent Tree Models. 113-141 - Lenore Cowen, Kapil Devkota, Xiaozhe Hu, James M. Murphy, Kaiyi Wu:
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks. 142-170 - Alp Yurtsever, Joel A. Tropp, Olivier Fercoq, Madeleine Udell, Volkan Cevher:
Scalable Semidefinite Programming. 171-200 - Shayan Aziznejad, Michael Unser:
Multikernel Regression with Sparsity Constraint. 201-224 - Robert J. Webber, Erik H. Thiede, Douglas Dow, Aaron R. Dinner, Jonathan Weare:
Error Bounds for Dynamical Spectral Estimation. 225-252 - Greg Ongie, Daniel L. Pimentel-Alarcón, Laura Balzano, Rebecca Willett, Robert D. Nowak:
Tensor Methods for Nonlinear Matrix Completion. 253-279 - Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens:
Diversity Sampling is an Implicit Regularization for Kernel Methods. 280-297 - Thinh T. Doan, Siva Theja Maguluri, Justin Romberg:
Finite-Time Performance of Distributed Temporal-Difference Learning with Linear Function Approximation. 298-320 - Wojciech Czaja, Dong Dong, Pierre-Emmanuel Jabin, Franck Olivier Ndjakou Njeunje:
Transport Model for Feature Extraction. 321-341 - Jamie Haddock, Anna Ma:
Greed Works: An Improved Analysis of Sampling Kaczmarz-Motzkin. 342-368 - March Boedihardjo, Shaofeng Deng, Thomas Strohmer:
A Performance Guarantee for Spectral Clustering. 369-387 - Boris Landa, Ronald R. Coifman, Yuval Kluger:
Doubly Stochastic Normalization of the Gaussian Kernel Is Robust to Heteroskedastic Noise. 388-413 - Weilin Li:
Generalization Error of Minimum Weighted Norm and Kernel Interpolation. 414-438 - Jonathan Bauch, Boaz Nadler, Pini Zilber:
Rank 2r Iterative Least Squares: Efficient Recovery of Ill-Conditioned Low Rank Matrices from Few Entries. 439-465
Volume 3, Number 2, 2021
- Zachary M. Boyd, Nicolas Fraiman, Jeremy Louis Marzuola, Peter J. Mucha, Braxton Osting, Jonathan Weare:
A Metric on Directed Graphs and Markov Chains Based on Hitting Probabilities. 467-493 - Elad Romanov, Tamir Bendory, Or Ordentlich:
Multi-Reference Alignment in High Dimensions: Sample Complexity and Phase Transition. 494-523 - Ning Zhang, Yangjing Zhang, Defeng Sun, Kim-Chuan Toh:
An Efficient Linearly Convergent Regularized Proximal Point Algorithm for Fused Multiple Graphical Lasso Problems. 524-543 - Richard Kueng, Joel A. Tropp:
Binary Component Decomposition Part I: The Positive-Semidefinite Case. 544-572 - Ruda Zhang, Roger G. Ghanem:
Normal-Bundle Bootstrap. 573-592 - Maryam Abdolali, Nicolas Gillis:
Simplex-Structured Matrix Factorization: Sparsity-Based Identifiability and Provably Correct Algorithms. 593-623 - Ben Adcock, Nick C. Dexter:
The Gap between Theory and Practice in Function Approximation with Deep Neural Networks. 624-655 - Leo Torres, Kevin S. Chan, Hanghang Tong, Tina Eliassi-Rad:
Nonbacktracking Eigenvalues under Node Removal: X-Centrality and Targeted Immunization. 656-675 - Yaim Cooper:
Global Minima of Overparameterized Neural Networks. 676-691 - Alexej Gossmann, Aria Pezeshk, Yu-Ping Wang, Berkman Sahiner:
Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve. 692-714 - Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini:
Distributed Learning with Sparse Communications by Identification. 715-735 - Melissa Marchand, Kyle A. Gallivan, Wen Huang, Paul Van Dooren:
Analysis of the Neighborhood Pattern Similarity Measure for the Role Extraction Problem. 736-757 - Kai Bergermann, Martin Stoll, Toni Volkmer:
Semi-supervised Learning for Aggregated Multilayer Graphs Using Diffuse Interface Methods and Fast Matrix-Vector Products. 758-785
Volume 3, Number 3, 2021
- Nimita Shinde, Vishnu Narayanan, James Saunderson:
Memory-Efficient Structured Convex Optimization via Extreme Point Sampling. 787-814 - Palle E. T. Jorgensen, David E. Stewart:
Approximation Properties of Ridge Functions and Extreme Learning Machines. 815-832 - Armin Askari, Quentin Rebjock, Alexandre d'Aspremont, Laurent El Ghaoui:
FANOK: Knockoffs in Linear Time. 833-853 - Yves F. Atchadé:
Approximate Spectral Gaps for Markov Chain Mixing Times in High Dimensions. 854-872 - Cristopher Salvi, Thomas Cass, James M. Foster, Terry J. Lyons, Weixin Yang:
The Signature Kernel Is the Solution of a Goursat PDE. 873-899 - Tal Amir, Ronen Basri, Boaz Nadler:
The Trimmed Lasso: Sparse Recovery Guarantees and Practical Optimization by the Generalized Soft-Min Penalty. 900-929 - Laurent El Ghaoui, Fangda Gu, Bertrand Travacca, Armin Askari, Alicia Y. Tsai:
Implicit Deep Learning. 930-958 - Ngoc Huy Chau, Éric Moulines, Miklós Rásonyi, Sotirios Sabanis, Ying Zhang:
On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case. 959-986 - William E. Leeb:
Matrix Denoising for Weighted Loss Functions and Heterogeneous Signals. 987-1012
Volume 3, Number 4, 2021
- Koulik Khamaru, Ashwin Pananjady, Feng Ruan, Martin J. Wainwright, Michael I. Jordan:
Is Temporal Difference Learning Optimal? An Instance-Dependent Analysis. 1013-1040 - Elizabeth Newman, Lars Ruthotto, Joseph L. Hart, Bart G. van Bloemen Waanders:
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection. 1041-1066 - Vasileios Charisopoulos, Austin R. Benson, Anil Damle:
Communication-Efficient Distributed Eigenspace Estimation. 1067-1092 - Jeremiah Birrell, Paul Dupuis, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang:
Variational Representations and Neural Network Estimation of Rényi Divergences. 1093-1116 - Kameron Decker Harris, Yizhe Zhu:
Deterministic Tensor Completion with Hypergraph Expanders. 1117-1140 - Abhishek Gupta, William B. Haskell:
Convergence of Recursive Stochastic Algorithms Using Wasserstein Divergence. 1141-1167 - Haotian Gu, Xin Guo, Xiaoli Wei, Renyuan Xu:
Mean-Field Controls with Q-Learning for Cooperative MARL: Convergence and Complexity Analysis. 1168-1196 - Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Jize Zhang, Yi Zhou, Yingbin Liang, Thomas Yong-Jin Han, Pramod K. Varshney:
MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data. 1197-1222 - Santiago Armstrong, Cristóbal Guzmán, Carlos A. Sing-Long:
An Optimal Algorithm for Strict Circular Seriation. 1223-1250 - Francis R. Bach:
On the Effectiveness of Richardson Extrapolation in Data Science. 1251-1277 - Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo:
On the Bias, Risk, and Consistency of Sample Means in Multi-armed Bandits. 1278-1300 - Daniel Potts, Michael Schmischke:
Interpretable Approximation of High-Dimensional Data. 1301-1323
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