Saved in:
| Main Authors: | Shi, Tao, Chen, Liangming, Jin, Long, Zhou, Mengchu |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.07122 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Method for Enhancing Generalization of Adam by Multiple Integrations
by: Jin, Long, et al.
Published: (2024)
by: Jin, Long, et al.
Published: (2024)
CLAIRE: Compressed Latent Autoencoder for Industrial Representation and Evaluation -- A Deep Learning Framework for Smart Manufacturing
by: Ghahramani, Mohammadhossein, et al.
Published: (2026)
by: Ghahramani, Mohammadhossein, et al.
Published: (2026)
Edge-AI-Driven Learning-to-Rank for Decentralized Task Allocation in Circular Smart Manufacturing
by: Ghahramani, Mohammadhossein, et al.
Published: (2026)
by: Ghahramani, Mohammadhossein, et al.
Published: (2026)
Adam-SHANG: A Convergent Adam-Type Method for Stochastic Smooth Convex Optimization
by: Yu, Yaxin, et al.
Published: (2026)
by: Yu, Yaxin, et al.
Published: (2026)
Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate
by: Yu, Yaxin, et al.
Published: (2026)
by: Yu, Yaxin, et al.
Published: (2026)
Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning
by: Guo, Zijian, et al.
Published: (2022)
by: Guo, Zijian, et al.
Published: (2022)
A Heavy-Load-Enhanced and Changeable-Periodicity-Perceived Workload Prediction Network
by: Chen, Feiyi, et al.
Published: (2023)
by: Chen, Feiyi, et al.
Published: (2023)
Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
by: Ahn, Kwangjun, et al.
Published: (2024)
by: Ahn, Kwangjun, et al.
Published: (2024)
HomeAdam: Adam and AdamW Algorithms Sometimes Go Home to Obtain Better Provable Generalization
by: Huang, Feihu, et al.
Published: (2026)
by: Huang, Feihu, et al.
Published: (2026)
AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization
by: Bieringer, Sebastian, et al.
Published: (2023)
by: Bieringer, Sebastian, et al.
Published: (2023)
Do Latent-CoT Models Think Step-by-Step? A Mechanistic Study on Sequential Reasoning Tasks
by: Liang, Jia, et al.
Published: (2026)
by: Liang, Jia, et al.
Published: (2026)
Towards a Mechanistic Understanding of Propositional Logical Reasoning in Large Language Models
by: Chen, Danchun, et al.
Published: (2026)
by: Chen, Danchun, et al.
Published: (2026)
HQViT: Hybrid Quantum Vision Transformer for Image Classification
by: Zhang, Hui, et al.
Published: (2025)
by: Zhang, Hui, et al.
Published: (2025)
Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance
by: Zhang, Qi, et al.
Published: (2024)
by: Zhang, Qi, et al.
Published: (2024)
Federated Transfer Learning with Differential Privacy
by: Li, Mengchu, et al.
Published: (2024)
by: Li, Mengchu, et al.
Published: (2024)
Mechanistic Data Attribution: Tracing the Training Origins of Interpretable LLM Units
by: Chen, Jianhui, et al.
Published: (2026)
by: Chen, Jianhui, et al.
Published: (2026)
Generative Deep Learning Framework for Inverse Design of Fuels
by: Yalamanchi, Kiran K., et al.
Published: (2025)
by: Yalamanchi, Kiran K., et al.
Published: (2025)
Acoustic Structure Inverse Design and Optimization Using Deep Learning
by: Sun, Xuecong, et al.
Published: (2021)
by: Sun, Xuecong, et al.
Published: (2021)
Decentralized Online Learning for Random Inverse Problems Over Graphs
by: Zhang, Xiwei, et al.
Published: (2023)
by: Zhang, Xiwei, et al.
Published: (2023)
FedAdamW: A Communication-Efficient Optimizer with Convergence and Generalization Guarantees for Federated Large Models
by: Liu, Junkang, et al.
Published: (2025)
by: Liu, Junkang, et al.
Published: (2025)
WarpAdam: A new Adam optimizer based on Meta-Learning approach
by: Pan, Chengxi, et al.
Published: (2024)
by: Pan, Chengxi, et al.
Published: (2024)
In-Run Data Shapley for Adam Optimizer
by: Ding, Meng, et al.
Published: (2026)
by: Ding, Meng, et al.
Published: (2026)
Compressed Models are NOT Trust-equivalent to Their Large Counterparts
by: Rai, Rohit Raj, et al.
Published: (2025)
by: Rai, Rohit Raj, et al.
Published: (2025)
Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness Evaluation
by: Wang, Yifei, et al.
Published: (2023)
by: Wang, Yifei, et al.
Published: (2023)
DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models
by: Liu, Jin, et al.
Published: (2026)
by: Liu, Jin, et al.
Published: (2026)
Compositional Generative Inverse Design
by: Wu, Tailin, et al.
Published: (2024)
by: Wu, Tailin, et al.
Published: (2024)
Understanding the Generalization of Stochastic Gradient Adam in Learning Neural Networks
by: Tang, Xuan, et al.
Published: (2025)
by: Tang, Xuan, et al.
Published: (2025)
DP-AdamW: Investigating Decoupled Weight Decay and Bias Correction in Private Deep Learning
by: Chooi, Jay, et al.
Published: (2025)
by: Chooi, Jay, et al.
Published: (2025)
SOPHON: Non-Fine-Tunable Learning to Restrain Task Transferability For Pre-trained Models
by: Deng, Jiangyi, et al.
Published: (2024)
by: Deng, Jiangyi, et al.
Published: (2024)
Scalable Kernel Inverse Optimization
by: Long, Youyuan, et al.
Published: (2024)
by: Long, Youyuan, et al.
Published: (2024)
Recursive Deep Inverse Reinforcement Learning
by: Ghanem, Paul, et al.
Published: (2025)
by: Ghanem, Paul, et al.
Published: (2025)
AdamO: A Collapse-Suppressed Optimizer for Offline RL
by: Qiao, Nan, et al.
Published: (2026)
by: Qiao, Nan, et al.
Published: (2026)
Classifier-guided Gradient Modulation for Enhanced Multimodal Learning
by: Guo, Zirun, et al.
Published: (2024)
by: Guo, Zirun, et al.
Published: (2024)
Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning
by: Waykole, Vedant, et al.
Published: (2026)
by: Waykole, Vedant, et al.
Published: (2026)
Optimizing Search Advertising Strategies: Integrating Reinforcement Learning with Generalized Second-Price Auctions for Enhanced Ad Ranking and Bidding
by: Zhou, Chang, et al.
Published: (2024)
by: Zhou, Chang, et al.
Published: (2024)
Foxtsage vs. Adam: Revolution or Evolution in Optimization?
by: Aula, Sirwan A., et al.
Published: (2024)
by: Aula, Sirwan A., et al.
Published: (2024)
Towards Generalized Inverse Reinforcement Learning
by: Dong, Chaosheng, et al.
Published: (2024)
by: Dong, Chaosheng, et al.
Published: (2024)
Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees
by: Xiao, Nachuan, et al.
Published: (2023)
by: Xiao, Nachuan, et al.
Published: (2023)
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
by: Hong, Yusu, et al.
Published: (2024)
by: Hong, Yusu, et al.
Published: (2024)
Dynamic Regret via Discounted-to-Dynamic Reduction with Applications to Curved Losses and Adam Optimizer
by: Xie, Yan-Feng, et al.
Published: (2026)
by: Xie, Yan-Feng, et al.
Published: (2026)
Similar Items
-
A Method for Enhancing Generalization of Adam by Multiple Integrations
by: Jin, Long, et al.
Published: (2024) -
CLAIRE: Compressed Latent Autoencoder for Industrial Representation and Evaluation -- A Deep Learning Framework for Smart Manufacturing
by: Ghahramani, Mohammadhossein, et al.
Published: (2026) -
Edge-AI-Driven Learning-to-Rank for Decentralized Task Allocation in Circular Smart Manufacturing
by: Ghahramani, Mohammadhossein, et al.
Published: (2026) -
Adam-SHANG: A Convergent Adam-Type Method for Stochastic Smooth Convex Optimization
by: Yu, Yaxin, et al.
Published: (2026) -
Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate
by: Yu, Yaxin, et al.
Published: (2026)