Online Importance Sampling for Stochastic Gradient Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Salaün, Corentin, Huang, Xingchang, Georgiev, Iliyan, Mitra, Niloy J., Singh, Gurprit |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multiple Importance Sampling for Stochastic Gradient Estimation
by: Salaün, Corentin, et al.
Published: (2024)
by: Salaün, Corentin, et al.
Published: (2024)
Blue noise for diffusion models
by: Huang, Xingchang, et al.
Published: (2024)
by: Huang, Xingchang, et al.
Published: (2024)
Edge-preserving noise for diffusion models
by: Vandersanden, Jente, et al.
Published: (2024)
by: Vandersanden, Jente, et al.
Published: (2024)
MCMC: Bridging Rendering, Optimization and Generative AI
by: Singh, Gurprit, et al.
Published: (2025)
by: Singh, Gurprit, et al.
Published: (2025)
Stochastic Optimization with Optimal Importance Sampling
by: Aolaritei, Liviu, et al.
Published: (2025)
by: Aolaritei, Liviu, et al.
Published: (2025)
Policy Gradient with Active Importance Sampling
by: Papini, Matteo, et al.
Published: (2024)
by: Papini, Matteo, et al.
Published: (2024)
Edge‐preserving noise for diffusion models
by: Jente Vandersanden, et al.
Published: (2026)
by: Jente Vandersanden, et al.
Published: (2026)
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
by: Livni, Roi
Published: (2024)
by: Livni, Roi
Published: (2024)
Faster Sampling via Stochastic Gradient Proximal Sampler
by: Huang, Xunpeng, et al.
Published: (2024)
by: Huang, Xunpeng, et al.
Published: (2024)
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling
by: Xu, Jian, et al.
Published: (2024)
by: Xu, Jian, et al.
Published: (2024)
ESPO: Entropy Importance Sampling Policy Optimization
by: Sheng, Yuepeng, et al.
Published: (2025)
by: Sheng, Yuepeng, et al.
Published: (2025)
Preference as Reward, Maximum Preference Optimization with Importance Sampling
by: Jiang, Zaifan, et al.
Published: (2023)
by: Jiang, Zaifan, et al.
Published: (2023)
Neural Product Importance Sampling via Warp Composition
by: Litalien, Joey, et al.
Published: (2024)
by: Litalien, Joey, et al.
Published: (2024)
Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization
by: Yang, Yufeng, et al.
Published: (2024)
by: Yang, Yufeng, et al.
Published: (2024)
Learning to Solve PDEs on Neural Shape Representations
by: Welschinger, Lilian, et al.
Published: (2025)
by: Welschinger, Lilian, et al.
Published: (2025)
Disagreement-Regularized Importance Sampling for Adversarial Label Corruption
by: Horváth, Csongor, et al.
Published: (2026)
by: Horváth, Csongor, et al.
Published: (2026)
Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation
by: Mensch, Zier, et al.
Published: (2026)
by: Mensch, Zier, et al.
Published: (2026)
Mean-Shift Distillation for Diffusion Mode Seeking
by: Thamizharasan, Vikas, et al.
Published: (2025)
by: Thamizharasan, Vikas, et al.
Published: (2025)
GIPO: Gaussian Importance Sampling Policy Optimization
by: Lu, Chengxuan, et al.
Published: (2026)
by: Lu, Chengxuan, et al.
Published: (2026)
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics
by: Mauri, Lorenzo, et al.
Published: (2024)
by: Mauri, Lorenzo, et al.
Published: (2024)
Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent
by: Chang, Xiangyu, et al.
Published: (2022)
by: Chang, Xiangyu, et al.
Published: (2022)
MonetGPT: Solving Puzzles Enhances MLLMs' Image Retouching Skills
by: Dutt, Niladri Shekhar, et al.
Published: (2025)
by: Dutt, Niladri Shekhar, et al.
Published: (2025)
Regret and Sample Complexity of Online Q-Learning via Concentration of Stochastic Approximation with Time-Inhomogeneous Markov Chains
by: Singh, Rahul, et al.
Published: (2026)
by: Singh, Rahul, et al.
Published: (2026)
Beyond Importance Sampling: Rejection-Gated Policy Optimization
by: Sun, Ziwu, et al.
Published: (2026)
by: Sun, Ziwu, et al.
Published: (2026)
The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization
by: Schliserman, Matan, et al.
Published: (2024)
by: Schliserman, Matan, et al.
Published: (2024)
Distributed Online Optimization with Stochastic Agent Availability
by: Achddou, Juliette, et al.
Published: (2024)
by: Achddou, Juliette, et al.
Published: (2024)
Robust Stochastic Optimization via Gradient Quantile Clipping
by: Merad, Ibrahim, et al.
Published: (2023)
by: Merad, Ibrahim, et al.
Published: (2023)
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
by: Lin, Jihao Andreas, et al.
Published: (2023)
by: Lin, Jihao Andreas, et al.
Published: (2023)
Breaking the Frozen Subspace: Importance Sampling for Low-Rank Optimization in LLM Pretraining
by: Zhang, Haochen, et al.
Published: (2025)
by: Zhang, Haochen, et al.
Published: (2025)
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
by: Chen, Sijia, et al.
Published: (2023)
by: Chen, Sijia, et al.
Published: (2023)
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo
by: Wang, Ziyi, et al.
Published: (2023)
by: Wang, Ziyi, et al.
Published: (2023)
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
by: Shen, Wei, et al.
Published: (2023)
by: Shen, Wei, et al.
Published: (2023)
Gradient-based Sample Selection for Faster Bayesian Optimization
by: Wei, Qiyu, et al.
Published: (2025)
by: Wei, Qiyu, et al.
Published: (2025)
Learning to Importance Sample in Primary Sample Space
by: Zheng, Quan, et al.
Published: (2018)
by: Zheng, Quan, et al.
Published: (2018)
Implicit Diffusion: Efficient Optimization through Stochastic Sampling
by: Marion, Pierre, et al.
Published: (2024)
by: Marion, Pierre, et al.
Published: (2024)
Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate
by: Lin, Yifan, et al.
Published: (2024)
by: Lin, Yifan, et al.
Published: (2024)
Annealed Importance Sampling with q-Paths
by: Brekelmans, Rob, et al.
Published: (2020)
by: Brekelmans, Rob, et al.
Published: (2020)
Actor-Critic with Active Importance Sampling
by: Molaei, Majid, et al.
Published: (2026)
by: Molaei, Majid, et al.
Published: (2026)
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
by: Song, Yuda, et al.
Published: (2024)
by: Song, Yuda, et al.
Published: (2024)
Sample Selection Bias in Machine Learning for Healthcare
by: Chauhan, Vinod Kumar, et al.
Published: (2024)
by: Chauhan, Vinod Kumar, et al.
Published: (2024)
Similar Items
-
Multiple Importance Sampling for Stochastic Gradient Estimation
by: Salaün, Corentin, et al.
Published: (2024) -
Blue noise for diffusion models
by: Huang, Xingchang, et al.
Published: (2024) -
Edge-preserving noise for diffusion models
by: Vandersanden, Jente, et al.
Published: (2024) -
MCMC: Bridging Rendering, Optimization and Generative AI
by: Singh, Gurprit, et al.
Published: (2025) -
Stochastic Optimization with Optimal Importance Sampling
by: Aolaritei, Liviu, et al.
Published: (2025)