Saved in:
| Main Authors: | Zhu, Wanrong, Lou, Zhipeng, Wei, Ziyang, Wu, Wei Biao |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.09346 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality
by: Wei, Ziyang, et al.
Published: (2023)
by: Wei, Ziyang, et al.
Published: (2023)
Refining Covariance Matrix Estimation in Stochastic Gradient Descent Through Bias Reduction
by: Wei, Ziyang, et al.
Published: (2026)
by: Wei, Ziyang, et al.
Published: (2026)
Online Statistical Inference of Constrained Stochastic Optimization via Random Scaling
by: Du, Xinchen, et al.
Published: (2025)
by: Du, Xinchen, et al.
Published: (2025)
Statistical Guarantees for High-Dimensional Stochastic Gradient Descent
by: Li, Jiaqi, et al.
Published: (2025)
by: Li, Jiaqi, et al.
Published: (2025)
Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization
by: Bonnerjee, Soham, et al.
Published: (2026)
by: Bonnerjee, Soham, et al.
Published: (2026)
Central Limit Theorems for Stochastic Gradient Descent Quantile Estimators
by: Wei, Ziyang, et al.
Published: (2025)
by: Wei, Ziyang, et al.
Published: (2025)
Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
by: Jiang, Wei, et al.
Published: (2024)
by: Jiang, Wei, et al.
Published: (2024)
Communication-Efficient Distributed Estimation and Inference for Cox's Model
by: Bayle, Pierre, et al.
Published: (2023)
by: Bayle, Pierre, et al.
Published: (2023)
Membership Inference Attacks and Privacy in Topic Modeling
by: Manzonelli, Nico, et al.
Published: (2024)
by: Manzonelli, Nico, et al.
Published: (2024)
Confidence Optimization for Probabilistic Encoding
by: Xia, Pengjiu, et al.
Published: (2025)
by: Xia, Pengjiu, et al.
Published: (2025)
Conformalized Percentile Interval: Finite Sample Validity and Improved Conditional Performance
by: Zou, Ran, et al.
Published: (2026)
by: Zou, Ran, et al.
Published: (2026)
Deterministic Inference across Tensor Parallel Sizes That Eliminates Training-Inference Mismatch
by: Zhang, Ziyang, et al.
Published: (2025)
by: Zhang, Ziyang, et al.
Published: (2025)
Enhancing Parallelism in Decentralized Stochastic Convex Optimization
by: Eisen, Ofri, et al.
Published: (2025)
by: Eisen, Ofri, et al.
Published: (2025)
TokenShapley: Token Level Context Attribution with Shapley Value
by: Xiao, Yingtai, et al.
Published: (2025)
by: Xiao, Yingtai, et al.
Published: (2025)
Spectral Ranking Inferences based on General Multiway Comparisons
by: Fan, Jianqing, et al.
Published: (2023)
by: Fan, Jianqing, et al.
Published: (2023)
Confidence Freeze: Early Success Induces a Metastable Decoupling of Metacognition and Behaviour
by: Zhang, Zhipeng, et al.
Published: (2026)
by: Zhang, Zhipeng, et al.
Published: (2026)
A Flexible Empirical Bayes Approach to Generalized Linear Models, with Applications to Sparse Logistic Regression
by: Xie, Dongyue, et al.
Published: (2026)
by: Xie, Dongyue, et al.
Published: (2026)
Mixture-Model Preference Learning for Many-Objective Bayesian Optimization
by: Dubey, Manisha, et al.
Published: (2026)
by: Dubey, Manisha, et al.
Published: (2026)
Efficiency of Parallel and Restart Exploration Strategies in Model Free Stochastic Simulations
by: Garcia, Ernesto, et al.
Published: (2025)
by: Garcia, Ernesto, et al.
Published: (2025)
Tuning-Free Stochastic Optimization
by: Khaled, Ahmed, et al.
Published: (2024)
by: Khaled, Ahmed, et al.
Published: (2024)
How Free is Parameter-Free Stochastic Optimization?
by: Attia, Amit, et al.
Published: (2024)
by: Attia, Amit, et al.
Published: (2024)
Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models
by: Li, Jiaqi, et al.
Published: (2024)
by: Li, Jiaqi, et al.
Published: (2024)
Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
by: Luo, Yuhong, et al.
Published: (2025)
by: Luo, Yuhong, et al.
Published: (2025)
Randomized Confidence Bounds for Stochastic Partial Monitoring
by: Heuillet, Maxime, et al.
Published: (2024)
by: Heuillet, Maxime, et al.
Published: (2024)
Jointly Modeling and Clustering Tensors in High Dimensions
by: Cai, Biao, et al.
Published: (2021)
by: Cai, Biao, et al.
Published: (2021)
Semi-Supervised Mixture Models under the Concept of Missing at Radom with Margin Confidence and Aranda Ordaz Function
by: Liao, Jinyang, et al.
Published: (2026)
by: Liao, Jinyang, et al.
Published: (2026)
Robust, Accurate Stochastic Optimization for Variational Inference
by: Dhaka, Akash Kumar, et al.
Published: (2020)
by: Dhaka, Akash Kumar, et al.
Published: (2020)
Stable but Wrong: An Inference Limit in Galactic Archaeology
by: Zhang, Zhipeng
Published: (2026)
by: Zhang, Zhipeng
Published: (2026)
Neural Stochastic Flows: Solver-Free Modelling and Inference for SDE Solutions
by: Kiyohara, Naoki, et al.
Published: (2025)
by: Kiyohara, Naoki, et al.
Published: (2025)
Accelerated Parameter-Free Stochastic Optimization
by: Kreisler, Itai, et al.
Published: (2024)
by: Kreisler, Itai, et al.
Published: (2024)
Linear Noise Approximation Assisted Bayesian Inference on Mechanistic Model of Partially Observed Stochastic Reaction Network
by: Xu, Wandi, et al.
Published: (2024)
by: Xu, Wandi, et al.
Published: (2024)
SparseDVFS: Sparse-Aware DVFS for Energy-Efficient Edge Inference
by: Zhang, Ziyang, et al.
Published: (2026)
by: Zhang, Ziyang, et al.
Published: (2026)
Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator
by: Kou, Wei-Bin, et al.
Published: (2025)
by: Kou, Wei-Bin, et al.
Published: (2025)
CAdam: Confidence-Based Optimization for Online Learning
by: Wang, Shaowen, et al.
Published: (2024)
by: Wang, Shaowen, et al.
Published: (2024)
Understanding Stochastic Natural Gradient Variational Inference
by: Wu, Kaiwen, et al.
Published: (2024)
by: Wu, Kaiwen, et al.
Published: (2024)
Session-Level Dynamic Ad Load Optimization using Offline Robust Reinforcement Learning
by: Liu, Tao, et al.
Published: (2025)
by: Liu, Tao, et al.
Published: (2025)
Efficient Stochastic Approximation of Minimax Excess Risk Optimization
by: Zhang, Lijun, et al.
Published: (2023)
by: Zhang, Lijun, et al.
Published: (2023)
A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning
by: Kim, Minyoung, et al.
Published: (2024)
by: Kim, Minyoung, et al.
Published: (2024)
Make Some Noise: Unlocking Language Model Parallel Inference Capability through Noisy Training
by: Wang, Yixuan, et al.
Published: (2024)
by: Wang, Yixuan, et al.
Published: (2024)
Almost Bayesian: The Fractal Dynamics of Stochastic Gradient Descent
by: Hennick, Max, et al.
Published: (2025)
by: Hennick, Max, et al.
Published: (2025)
Similar Items
-
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality
by: Wei, Ziyang, et al.
Published: (2023) -
Refining Covariance Matrix Estimation in Stochastic Gradient Descent Through Bias Reduction
by: Wei, Ziyang, et al.
Published: (2026) -
Online Statistical Inference of Constrained Stochastic Optimization via Random Scaling
by: Du, Xinchen, et al.
Published: (2025) -
Statistical Guarantees for High-Dimensional Stochastic Gradient Descent
by: Li, Jiaqi, et al.
Published: (2025) -
Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization
by: Bonnerjee, Soham, et al.
Published: (2026)