Saved in:
| Main Authors: | Holland, Matthew J., Nakatani, Kosuke |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.10006 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An accelerated first-order regularized momentum descent ascent algorithm for stochastic nonconvex-concave minimax problems
by: Zhang, Huiling, et al.
Published: (2023)
by: Zhang, Huiling, et al.
Published: (2023)
Convergence of two-timescale gradient descent ascent dynamics: finite-dimensional and mean-field perspectives
by: An, Jing, et al.
Published: (2025)
by: An, Jing, et al.
Published: (2025)
Robust variance-regularized risk minimization with concomitant scaling
by: Holland, Matthew J.
Published: (2023)
by: Holland, Matthew J.
Published: (2023)
Criterion Collapse and Loss Distribution Control
by: Holland, Matthew J.
Published: (2024)
by: Holland, Matthew J.
Published: (2024)
Making Robust Generalizers Less Rigid with Loss Concentration
by: Holland, Matthew J., et al.
Published: (2024)
by: Holland, Matthew J., et al.
Published: (2024)
Coordinate ascent neural Kalman-MLE for state estimation
by: Hanlon, Bettina, et al.
Published: (2025)
by: Hanlon, Bettina, et al.
Published: (2025)
Robust off-policy Reinforcement Learning via Soft Constrained Adversary
by: Nakanishi, Kosuke, et al.
Published: (2024)
by: Nakanishi, Kosuke, et al.
Published: (2024)
Evaluating GFlowNet from partial episodes for stable and flexible policy-based training
by: Niu, Puhua, et al.
Published: (2026)
by: Niu, Puhua, et al.
Published: (2026)
Pi theorem formulation of flood mapping
by: Bartlett, Mark S., et al.
Published: (2022)
by: Bartlett, Mark S., et al.
Published: (2022)
Manifold constrained steepest descent
by: Yang, Kaiwei, et al.
Published: (2026)
by: Yang, Kaiwei, et al.
Published: (2026)
Enhancing E-commerce Product Title Translation with Retrieval-Augmented Generation and Large Language Models
by: Zhang, Bryan, et al.
Published: (2024)
by: Zhang, Bryan, et al.
Published: (2024)
Double descent in quantum kernel methods
by: Kempkes, Marie, et al.
Published: (2025)
by: Kempkes, Marie, et al.
Published: (2025)
Training thermodynamic computers by gradient descent
by: Whitelam, Stephen
Published: (2025)
by: Whitelam, Stephen
Published: (2025)
Langevin Monte Carlo: random coordinate descent and variance reduction
by: Ding, Zhiyan, et al.
Published: (2020)
by: Ding, Zhiyan, et al.
Published: (2020)
Generalisation under gradient descent via deterministic PAC-Bayes
by: Clerico, Eugenio, et al.
Published: (2022)
by: Clerico, Eugenio, et al.
Published: (2022)
Learning mirror maps in policy mirror descent
by: Alfano, Carlo, et al.
Published: (2024)
by: Alfano, Carlo, et al.
Published: (2024)
Riemannian coordinate descent algorithms on matrix manifolds
by: Han, Andi, et al.
Published: (2024)
by: Han, Andi, et al.
Published: (2024)
Singular-limit analysis of gradient descent with noise injection
by: Shalova, Anna, et al.
Published: (2024)
by: Shalova, Anna, et al.
Published: (2024)
A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
by: Kim, Youngseok, et al.
Published: (2022)
by: Kim, Youngseok, et al.
Published: (2022)
Gradient descent in matrix factorization: Understanding large initialization
by: Chen, Hengchao, et al.
Published: (2023)
by: Chen, Hengchao, et al.
Published: (2023)
Gradient descent for deep equilibrium single-index models
by: Dandapanthula, Sanjit, et al.
Published: (2025)
by: Dandapanthula, Sanjit, et al.
Published: (2025)
New logarithmic step size for stochastic gradient descent
by: Shamaee, M. Soheil, et al.
Published: (2024)
by: Shamaee, M. Soheil, et al.
Published: (2024)
The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints
by: Wang, Po-Wei, et al.
Published: (2017)
by: Wang, Po-Wei, et al.
Published: (2017)
Double descent for least-squares interpolation on contaminated data: A simulation study
by: Werner, Tino
Published: (2026)
by: Werner, Tino
Published: (2026)
eGAD! double descent is explained by Generalized Aliasing Decomposition
by: Transtrum, Mark K., et al.
Published: (2024)
by: Transtrum, Mark K., et al.
Published: (2024)
Spectral alignment of stochastic gradient descent for high-dimensional classification tasks
by: Arous, Gerard Ben, et al.
Published: (2023)
by: Arous, Gerard Ben, et al.
Published: (2023)
Guided parallelized stochastic gradient descent for delay compensation
by: Sharma, Anuraganand
Published: (2021)
by: Sharma, Anuraganand
Published: (2021)
Linear convergence of proximal descent schemes on the Wasserstein space
by: Lascu, Razvan-Andrei, et al.
Published: (2024)
by: Lascu, Razvan-Andrei, et al.
Published: (2024)
Convergence of coordinate ascent variational inference for log-concave measures via optimal transport
by: Arnese, Manuel, et al.
Published: (2024)
by: Arnese, Manuel, et al.
Published: (2024)
Iterative regularization in classification via hinge loss diagonal descent
by: Apidopoulos, Vassilis, et al.
Published: (2022)
by: Apidopoulos, Vassilis, et al.
Published: (2022)
Spike-timing-dependent Hebbian learning as noisy gradient descent
by: Dexheimer, Niklas, et al.
Published: (2025)
by: Dexheimer, Niklas, et al.
Published: (2025)
Training-free retrieval-augmented generation with reinforced reasoning for flood damage nowcasting
by: Huang, Lipai, et al.
Published: (2026)
by: Huang, Lipai, et al.
Published: (2026)
Gradient descent with generalized Newton's method
by: Bu, Zhiqi, et al.
Published: (2024)
by: Bu, Zhiqi, et al.
Published: (2024)
Adaptive Discovery of Interpretable Audio Attributes with Multimodal LLMs for Low-Resource Classification
by: Yoshimura, Kosuke, et al.
Published: (2026)
by: Yoshimura, Kosuke, et al.
Published: (2026)
AaSP: Aliasing-aware Self-Supervised Pre-Training for Audio Spectrogram Transformers
by: Yamamoto, Kohei, et al.
Published: (2025)
by: Yamamoto, Kohei, et al.
Published: (2025)
GenAI-Powered Inference
by: Imai, Kosuke, et al.
Published: (2025)
by: Imai, Kosuke, et al.
Published: (2025)
Acceleration of stochastic gradient descent with momentum by averaging: finite-sample rates and asymptotic normality
by: Tang, Kejie, et al.
Published: (2023)
by: Tang, Kejie, et al.
Published: (2023)
Softmax $\geq$ Linear: Transformers may learn to classify in-context by kernel gradient descent
by: Dragutinović, Sara, et al.
Published: (2025)
by: Dragutinović, Sara, et al.
Published: (2025)
Towards Understanding Epoch-wise Double descent in Two-layer Linear Neural Networks
by: Olmin, Amanda, et al.
Published: (2024)
by: Olmin, Amanda, et al.
Published: (2024)
Data-driven low-dimensional model of a sedimenting flexible fiber
by: Fox, Andrew J, et al.
Published: (2024)
by: Fox, Andrew J, et al.
Published: (2024)
Similar Items
-
An accelerated first-order regularized momentum descent ascent algorithm for stochastic nonconvex-concave minimax problems
by: Zhang, Huiling, et al.
Published: (2023) -
Convergence of two-timescale gradient descent ascent dynamics: finite-dimensional and mean-field perspectives
by: An, Jing, et al.
Published: (2025) -
Robust variance-regularized risk minimization with concomitant scaling
by: Holland, Matthew J.
Published: (2023) -
Criterion Collapse and Loss Distribution Control
by: Holland, Matthew J.
Published: (2024) -
Making Robust Generalizers Less Rigid with Loss Concentration
by: Holland, Matthew J., et al.
Published: (2024)