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Publication search results
found 95 matches
- 2022
- Ziyu Chen, Yingzhou Li, Xiuyuan Cheng:
SpecNet2: Orthogonalization-free Spectral Embedding by Neural Networks. MSML 2022: 33-48 - Zhijun Chen, Hayden Schaeffer, Rachel A. Ward:
Concentration of Random Feature Matrices in High-Dimensions. MSML 2022: 287-302 - Laurent Condat, Peter Richtárik:
MURANA: A Generic Framework for Stochastic Variance-Reduced Optimization. MSML 2022: 81-96 - Samuel Horváth, Chen-Yu Ho, Ludovit Horvath, Atal Narayan Sahu, Marco Canini, Peter Richtárik:
Natural Compression for Distributed Deep Learning. MSML 2022: 129-141 - Arthur Jacot, Franck Gabriel, François Ged, Clément Hongler:
Freeze and Chaos: NTK views on DNN Normalization, Checkerboard and Boundary Artifacts. MSML 2022: 257-270 - Didem Kochan, Zheng Zhang, Xiu Yang:
A Quantum-Inspired Hamiltonian Monte Carlo Method for Missing Data Imputation. MSML 2022: 17-32 - Kookjin Lee, Nathaniel Trask, Panos Stinis:
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling. MSML 2022: 65-80 - Fei Lu, Quanjun Lang, Qingci An:
Data adaptive RKHS Tikhonov regularization for learning kernels in operators. MSML 2022: 158-172 - Tao Luo, Zheng Ma, Zhiwei Wang, Zhiqin John Xu, Yaoyu Zhang:
An Upper Limit of Decaying Rate with Respect to Frequency in Linear Frequency Principle Model. MSML 2022: 205-214 - Tyler Maunu, Chenyu Yu, Gilad Lerman:
Stochastic and Private Nonconvex Outlier-Robust PCAs. MSML 2022: 173-188 - Daniel A. Messenger, Emiliano Dall'Anese, David M. Bortz:
Online Weak-form Sparse Identification of Partial Differential Equations. MSML 2022: 241-256 - Johannes Müller, Marius Zeinhofer:
Error Estimates for the Deep Ritz Method with Boundary Penalty. MSML 2022: 215-230 - Johannes Müller, Marius Zeinhofer:
Notes on Exact Boundary Values in Residual Minimisation. MSML 2022: 231-240 - Tan Minh Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang:
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. MSML 2022: 189-204 - Ravi G. Patel, Indu Manickam, Myoungkyu Lee, Mamikon A. Gulian:
Error-in-variables modelling for operator learning. MSML 2022: 142-157 - Yuankai Teng, Xiaoping Zhang, Zhu Wang, Lili Ju:
Learning Green’s Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver. MSML 2022: 1-16 - Nathaniel Trask, Amelia Henriksen, Carianne Martinez, Eric C. Cyr:
Hierarchical partition of unity networks: fast multilevel training. MSML 2022: 271-286 - Emanuele Troiani, Vittorio Erba, Florent Krzakala, Antoine Maillard, Lenka Zdeborová:
Optimal denoising of rotationally invariant rectangular matrices. MSML 2022: 97-112 - Yuege Xie, Robert Shi, Hayden Schaeffer, Rachel A. Ward:
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning. MSML 2022: 303-318 - Jiahao Yao, Haoya Li, Marin Bukov, Lin Lin, Lexing Ying:
Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits. MSML 2022: 49-64 - Yaohua Zang, Jihao Long, Xuanxi Zhang, Wei Hu, Weinan E, Jiequn Han:
A Machine Learning Enhanced Algorithm for the Optimal Landing Problem. MSML 2022: 319-334 - Sixin Zhang:
On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes. MSML 2022: 113-128 - Zichen Zhao, Qianxiao Li:
Adaptive sampling methods for learning dynamical systems. MSML 2022: 335-350 - Bin Dong, Qianxiao Li, Lei Wang, Zhi-Qin John Xu:
Mathematical and Scientific Machine Learning, 15-17 August 2022, Peking University, Beijing, China. Proceedings of Machine Learning Research 190, PMLR 2022 [contents] - 2021
- Chao Ma, Lei Wu, Weinan E:
A Qualitative Study of the Dynamic Behavior for Adaptive Gradient Algorithms. MSML 2021: 671-692 - Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga:
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data. MSML 2021: 1-36 - Andrea Agazzi, Jianfeng Lu:
Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes. MSML 2021: 37-74 - Amirali Aghazadeh, Vipul Gupta, Alex DeWeese, Onur Ozan Koyluoglu, Kannan Ramchandran:
BEAR: Sketching BFGS Algorithm for Ultra-High Dimensional Feature Selection in Sublinear Memory. MSML 2021: 75-92 - Terrence Alsup, Luca Venturi, Benjamin Peherstorfer:
Multilevel Stein variational gradient descent with applications to Bayesian inverse problems. MSML 2021: 93-117 - Randall Balestriero, Hervé Glotin, Richard G. Baraniuk:
Interpretable and Learnable Super-Resolution Time-Frequency Representation. MSML 2021: 118-152
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