Saved in:
| Main Author: | Yun, Juyoung |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.21564 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Stochastic Gradient Sampling for Enhancing Neural Networks Training
by: Yun, Juyoung
Published: (2023)
by: Yun, Juyoung
Published: (2023)
Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks
by: Yun, Juyoung
Published: (2023)
by: Yun, Juyoung
Published: (2023)
Extreme Solar Flare Prediction Using Residual Networks with HMI Magnetograms and Intensitygrams
by: Yun, Juyoung, et al.
Published: (2024)
by: Yun, Juyoung, et al.
Published: (2024)
ZNorm: Z-Score Gradient Normalization Accelerating Skip-Connected Network Training without Architectural Modification
by: Yun, Juyoung
Published: (2024)
by: Yun, Juyoung
Published: (2024)
AlphaGrad: Non-Linear Gradient Normalization Optimizer
by: Sane, Soham
Published: (2025)
by: Sane, Soham
Published: (2025)
Gradient Residual Connections
by: Pan, Yangchen, et al.
Published: (2026)
by: Pan, Yangchen, et al.
Published: (2026)
Insights from Gradient Dynamics: Gradient Autoscaled Normalization
by: Yun, Vincent-Daniel
Published: (2025)
by: Yun, Vincent-Daniel
Published: (2025)
Federated Smoothing Proximal Gradient for Quantile Regression with Non-Convex Penalties
by: Mirzaeifard, Reza, et al.
Published: (2024)
by: Mirzaeifard, Reza, et al.
Published: (2024)
Beyond Gradient Averaging in Parallel Optimization: Improved Robustness through Gradient Agreement Filtering
by: Chaubard, Francois, et al.
Published: (2024)
by: Chaubard, Francois, et al.
Published: (2024)
The Hidden Power of Pure 16-bit Floating-Point Neural Networks
by: Yun, Juyoung, et al.
Published: (2023)
by: Yun, Juyoung, et al.
Published: (2023)
Reconstructing Deep Neural Networks: Unleashing the Optimization Potential of Natural Gradient Descent
by: Liu, Weihua, et al.
Published: (2024)
by: Liu, Weihua, et al.
Published: (2024)
Cross-Entropy Optimization for Hyperparameter Optimization in Stochastic Gradient-based Approaches to Train Deep Neural Networks
by: Li, Kevin, et al.
Published: (2024)
by: Li, Kevin, et al.
Published: (2024)
Gradient Multi-Normalization for Stateless and Scalable LLM Training
by: Scetbon, Meyer, et al.
Published: (2025)
by: Scetbon, Meyer, et al.
Published: (2025)
Enhancing Deep Learning with Optimized Gradient Descent: Bridging Numerical Methods and Neural Network Training
by: Ma, Yuhan, et al.
Published: (2024)
by: Ma, Yuhan, et al.
Published: (2024)
Analysis and Predictive Modeling of Solar Coronal Holes Using Computer Vision and ARIMA-LSTM Networks
by: Yun, Juyoung, et al.
Published: (2024)
by: Yun, Juyoung, et al.
Published: (2024)
FlowPG: Action-constrained Policy Gradient with Normalizing Flows
by: Brahmanage, Janaka Chathuranga, et al.
Published: (2024)
by: Brahmanage, Janaka Chathuranga, et al.
Published: (2024)
Gradient Routing: Masking Gradients to Localize Computation in Neural Networks
by: Cloud, Alex, et al.
Published: (2024)
by: Cloud, Alex, et al.
Published: (2024)
Randomness and Interpolation Improve Gradient Descent
by: Li, Jiawen, et al.
Published: (2025)
by: Li, Jiawen, et al.
Published: (2025)
Influence Functions for Edge Edits in Non-Convex Graph Neural Networks
by: Heo, Jaeseung, et al.
Published: (2025)
by: Heo, Jaeseung, et al.
Published: (2025)
MANGO: Meta-Adaptive Network Gradient Optimization for Online Continual Learning
by: Awasthi, Ankita, et al.
Published: (2026)
by: Awasthi, Ankita, et al.
Published: (2026)
Gradient Extrapolation-Based Policy Optimization
by: Swapnil, Ismam Nur, et al.
Published: (2026)
by: Swapnil, Ismam Nur, et al.
Published: (2026)
Gradient Regularized Natural Gradients
by: Dash, Satya Prakash, et al.
Published: (2026)
by: Dash, Satya Prakash, et al.
Published: (2026)
Deep Reinforcement Learning with Gradient Eligibility Traces
by: Elelimy, Esraa, et al.
Published: (2025)
by: Elelimy, Esraa, et al.
Published: (2025)
Improving Spatio-Temporal Residual Error Propagation by Mitigating Over-Squashing
by: Moghadas, Seyed Mohamad, et al.
Published: (2026)
by: Moghadas, Seyed Mohamad, et al.
Published: (2026)
Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems
by: Ozaslan, Ibrahim K., et al.
Published: (2024)
by: Ozaslan, Ibrahim K., et al.
Published: (2024)
Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks
by: Wang, Puyu, et al.
Published: (2026)
by: Wang, Puyu, et al.
Published: (2026)
GradientStabilizer:Fix the Norm, Not the Gradient
by: Huang, Tianjin, et al.
Published: (2025)
by: Huang, Tianjin, et al.
Published: (2025)
Axiomatization of Gradient Smoothing in Neural Networks
by: Zhou, Linjiang, et al.
Published: (2024)
by: Zhou, Linjiang, et al.
Published: (2024)
Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functions
by: Jain, Ayush, et al.
Published: (2024)
by: Jain, Ayush, et al.
Published: (2024)
Sequential Policy Gradient for Adaptive Hyperparameter Optimization
by: Li, Zheng, et al.
Published: (2025)
by: Li, Zheng, et al.
Published: (2025)
DeepDefense: Layer-Wise Gradient-Feature Alignment for Building Robust Neural Networks
by: Lin, Ci, et al.
Published: (2025)
by: Lin, Ci, et al.
Published: (2025)
Policy Gradient Methods for Non-Markovian Reinforcement Learning
by: Kar, Avik, et al.
Published: (2026)
by: Kar, Avik, et al.
Published: (2026)
AttriReBoost: A Gradient-Free Propagation Optimization Method for Cold Start Mitigation in Attribute Missing Graphs
by: Li, Mengran, et al.
Published: (2025)
by: Li, Mengran, et al.
Published: (2025)
Vertical Symbolic Regression via Deep Policy Gradient
by: Jiang, Nan, et al.
Published: (2024)
by: Jiang, Nan, et al.
Published: (2024)
Deep MMD Gradient Flow without adversarial training
by: Galashov, Alexandre, et al.
Published: (2024)
by: Galashov, Alexandre, et al.
Published: (2024)
Gradient Free Deep Reinforcement Learning With TabPFN
by: Schiff, David, et al.
Published: (2025)
by: Schiff, David, et al.
Published: (2025)
EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification
by: Zhang, Lin, et al.
Published: (2025)
by: Zhang, Lin, et al.
Published: (2025)
Signal-Adaptive Trust Regions for Gradient-Free Optimization of Recurrent Spiking Neural Networks
by: Li, Jinhao, et al.
Published: (2026)
by: Li, Jinhao, et al.
Published: (2026)
A Qualitative Test-Risk Mechanism for Scaling Behavior in Normalized Residual Networks
by: Cheng, Daning, et al.
Published: (2026)
by: Cheng, Daning, et al.
Published: (2026)
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis
by: Chen, Lesi, et al.
Published: (2023)
by: Chen, Lesi, et al.
Published: (2023)
Similar Items
-
Stochastic Gradient Sampling for Enhancing Neural Networks Training
by: Yun, Juyoung
Published: (2023) -
Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks
by: Yun, Juyoung
Published: (2023) -
Extreme Solar Flare Prediction Using Residual Networks with HMI Magnetograms and Intensitygrams
by: Yun, Juyoung, et al.
Published: (2024) -
ZNorm: Z-Score Gradient Normalization Accelerating Skip-Connected Network Training without Architectural Modification
by: Yun, Juyoung
Published: (2024) -
AlphaGrad: Non-Linear Gradient Normalization Optimizer
by: Sane, Soham
Published: (2025)