Saved in:
| Main Author: | Hedges, C. Evans |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.04487 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Source-Optimal Training is Transfer-Suboptimal
by: Hedges, C. Evans
Published: (2025)
by: Hedges, C. Evans
Published: (2025)
GradINN: Gradient Informed Neural Network
by: Aglietti, Filippo, et al.
Published: (2024)
by: Aglietti, Filippo, et al.
Published: (2024)
GradNetOT: Learning Optimal Transport Maps with GradNets
by: Chaudhari, Shreyas, et al.
Published: (2025)
by: Chaudhari, Shreyas, et al.
Published: (2025)
DiffGrad for Physics-Informed Neural Networks
by: Rahman, Jamshaid Ul, et al.
Published: (2024)
by: Rahman, Jamshaid Ul, et al.
Published: (2024)
OrthoFormer: Instrumental Variable Estimation in Transformer Hidden States via Neural Control Functions
by: Luo, Charles
Published: (2026)
by: Luo, Charles
Published: (2026)
Grad-Instructor: Universal Backpropagation with Explainable Evaluation Neural Networks for Meta-learning and AutoML
by: Ino, Ryohei
Published: (2024)
by: Ino, Ryohei
Published: (2024)
Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed
by: Chezhegov, Savelii, et al.
Published: (2024)
by: Chezhegov, Savelii, et al.
Published: (2024)
Grad2Reward: From Sparse Judgment to Dense Rewards for Improving Open-Ended LLM Reasoning
by: Zhang, Zheng, et al.
Published: (2026)
by: Zhang, Zheng, et al.
Published: (2026)
AdaptGrad: Adaptive Sampling to Reduce Noise
by: Zhou, Linjiang, et al.
Published: (2024)
by: Zhou, Linjiang, et al.
Published: (2024)
AdaGrad under Anisotropic Smoothness
by: Liu, Yuxing, et al.
Published: (2024)
by: Liu, Yuxing, et al.
Published: (2024)
GradAlign for Training-free Model Performance Inference
by: Li, Yuxuan, et al.
Published: (2024)
by: Li, Yuxuan, et al.
Published: (2024)
GLA-Grad++: An Improved Griffin-Lim Guided Diffusion Model for Speech Synthesis
by: Baoueb, Teysir, et al.
Published: (2025)
by: Baoueb, Teysir, et al.
Published: (2025)
Revisiting Convergence of AdaGrad with Relaxed Assumptions
by: Hong, Yusu, et al.
Published: (2024)
by: Hong, Yusu, et al.
Published: (2024)
GradMetaNet: An Equivariant Architecture for Learning on Gradients
by: Gelberg, Yoav, et al.
Published: (2025)
by: Gelberg, Yoav, et al.
Published: (2025)
GradCheck: Analyzing classifier guidance gradients for conditional diffusion sampling
by: Vaeth, Philipp, et al.
Published: (2024)
by: Vaeth, Philipp, et al.
Published: (2024)
Reinforcement Learning in Categorical Cybernetics
by: Hedges, Jules, et al.
Published: (2024)
by: Hedges, Jules, et al.
Published: (2024)
Ortho-Hydra: Orthogonalized Experts for DiT LoRA
by: Ji, Seunghyun
Published: (2026)
by: Ji, Seunghyun
Published: (2026)
PCA- and SVM-Grad-CAM for Convolutional Neural Networks: Closed-form Jacobian Expression
by: Omae, Yuto
Published: (2025)
by: Omae, Yuto
Published: (2025)
TextGrad: Automatic "Differentiation" via Text
by: Yuksekgonul, Mert, et al.
Published: (2024)
by: Yuksekgonul, Mert, et al.
Published: (2024)
Expected Grad-CAM: Towards gradient faithfulness
by: Buono, Vincenzo, et al.
Published: (2024)
by: Buono, Vincenzo, et al.
Published: (2024)
GradCFA: A Hybrid Gradient-Based Counterfactual and Feature Attribution Explanation Algorithm for Local Interpretation of Neural Networks
by: Sanderson, Jacob, et al.
Published: (2026)
by: Sanderson, Jacob, et al.
Published: (2026)
GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through Gradient
by: Zhang, Yuang, et al.
Published: (2024)
by: Zhang, Yuang, et al.
Published: (2024)
AdaGrad Meets Muon: Adaptive Stepsizes for Orthogonal Updates
by: Zhang, Minxin, et al.
Published: (2025)
by: Zhang, Minxin, et al.
Published: (2025)
StableGrad: Backward Scale Control without Batch Normalization
by: Mestre, Jose I., et al.
Published: (2026)
by: Mestre, Jose I., et al.
Published: (2026)
Rethinking Calibration for Early-Exit Neural Networks
by: Kubaty, Piotr, et al.
Published: (2025)
by: Kubaty, Piotr, et al.
Published: (2025)
Probabilistic Calibration by Design for Neural Network Regression
by: Dheur, Victor, et al.
Published: (2024)
by: Dheur, Victor, et al.
Published: (2024)
PeriodGrad: Towards Pitch-Controllable Neural Vocoder Based on a Diffusion Probabilistic Model
by: Hono, Yukiya, et al.
Published: (2024)
by: Hono, Yukiya, et al.
Published: (2024)
GradPower: Powering Gradients for Faster Language Model Pre-Training
by: Wang, Jinbo, et al.
Published: (2025)
by: Wang, Jinbo, et al.
Published: (2025)
AdaGrad-Diff: A New Version of the Adaptive Gradient Algorithm
by: Bojovic, Matia, et al.
Published: (2026)
by: Bojovic, Matia, et al.
Published: (2026)
GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent
by: Marton, Sascha, et al.
Published: (2023)
by: Marton, Sascha, et al.
Published: (2023)
Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration
by: Tang, Yung-Chen, et al.
Published: (2022)
by: Tang, Yung-Chen, et al.
Published: (2022)
Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness
by: Komisarenko, Viacheslav, et al.
Published: (2024)
by: Komisarenko, Viacheslav, et al.
Published: (2024)
AlphaGrad: Non-Linear Gradient Normalization Optimizer
by: Sane, Soham
Published: (2025)
by: Sane, Soham
Published: (2025)
DS FedProxGrad: Asymptotic Stationarity Without Noise Floor in Fair Federated Learning
by: Arif, Huzaifa
Published: (2025)
by: Arif, Huzaifa
Published: (2025)
TreeGrad-Ranker: Feature Ranking via $O(L)$-Time Gradients for Decision Trees
by: Li, Weida, et al.
Published: (2026)
by: Li, Weida, et al.
Published: (2026)
Explanation of Dynamic Physical Field Predictions using WassersteinGrad: Application to Autoregressive Weather Forecasting
by: Essafouri, Younes, et al.
Published: (2026)
by: Essafouri, Younes, et al.
Published: (2026)
Modeling AdaGrad, RMSProp, and Adam with Integro-Differential Equations
by: Heredia, Carlos
Published: (2024)
by: Heredia, Carlos
Published: (2024)
AdAdaGrad: Adaptive Batch Size Schemes for Adaptive Gradient Methods
by: Lau, Tim Tsz-Kit, et al.
Published: (2024)
by: Lau, Tim Tsz-Kit, et al.
Published: (2024)
AdaBatchGrad: Combining Adaptive Batch Size and Adaptive Step Size
by: Ostroukhov, Petr, et al.
Published: (2024)
by: Ostroukhov, Petr, et al.
Published: (2024)
OrthoRank: Token Selection via Sink Token Orthogonality for Efficient LLM inference
by: Shin, Seungjun, et al.
Published: (2025)
by: Shin, Seungjun, et al.
Published: (2025)
Similar Items
-
Source-Optimal Training is Transfer-Suboptimal
by: Hedges, C. Evans
Published: (2025) -
GradINN: Gradient Informed Neural Network
by: Aglietti, Filippo, et al.
Published: (2024) -
GradNetOT: Learning Optimal Transport Maps with GradNets
by: Chaudhari, Shreyas, et al.
Published: (2025) -
DiffGrad for Physics-Informed Neural Networks
by: Rahman, Jamshaid Ul, et al.
Published: (2024) -
OrthoFormer: Instrumental Variable Estimation in Transformer Hidden States via Neural Control Functions
by: Luo, Charles
Published: (2026)