Saved in:
| Main Authors: | Xie, Tian, Zhu, Ding, Liu, Jia, Khalili, Mahdi, Zhang, Xueru |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.17304 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Demographic-Agnostic Fairness without Harm
by: Cai, Zhongteng, et al.
Published: (2025)
by: Cai, Zhongteng, et al.
Published: (2025)
Lookahead Counterfactual Fairness
by: Zuo, Zhiqun, et al.
Published: (2024)
by: Zuo, Zhiqun, et al.
Published: (2024)
Addressing Polarization and Unfairness in Performative Prediction
by: Jin, Kun, et al.
Published: (2024)
by: Jin, Kun, et al.
Published: (2024)
Federated Learning with Reduced Information Leakage and Computation
by: Yin, Tongxin, et al.
Published: (2023)
by: Yin, Tongxin, et al.
Published: (2023)
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
by: Xie, Tian, et al.
Published: (2024)
by: Xie, Tian, et al.
Published: (2024)
Non-linear Welfare-Aware Strategic Learning
by: Xie, Tian, et al.
Published: (2024)
by: Xie, Tian, et al.
Published: (2024)
Post-processing for Fair Regression via Explainable SVD
by: Zuo, Zhiqun, et al.
Published: (2025)
by: Zuo, Zhiqun, et al.
Published: (2025)
An Efficient Training Algorithm for Models with Block-wise Sparsity
by: Zhu, Ding, et al.
Published: (2025)
by: Zhu, Ding, et al.
Published: (2025)
Improving Tree Probability Estimation with Stochastic Optimization and Variance Reduction
by: Xie, Tianyu, et al.
Published: (2024)
by: Xie, Tianyu, et al.
Published: (2024)
Neuroplasticity and Corruption in Model Mechanisms: A Case Study Of Indirect Object Identification
by: Chhabra, Vishnu Kabir, et al.
Published: (2025)
by: Chhabra, Vishnu Kabir, et al.
Published: (2025)
ECG Signal Denoising Using Multi-scale Patch Embedding and Transformers
by: Zhu, Ding, et al.
Published: (2024)
by: Zhu, Ding, et al.
Published: (2024)
How Strategic Agents Respond: Comparing Analytical Models with LLM-Generated Responses in Strategic Classification
by: Xie, Tian, et al.
Published: (2025)
by: Xie, Tian, et al.
Published: (2025)
ProFL: Performative Robust Optimal Federated Learning
by: Zheng, Xue, et al.
Published: (2024)
by: Zheng, Xue, et al.
Published: (2024)
Stochastic Gradient Langevin Dynamics with Variance Reduction
by: Huang, Zhishen, et al.
Published: (2021)
by: Huang, Zhishen, et al.
Published: (2021)
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions
by: Jiang, Wei, et al.
Published: (2024)
by: Jiang, Wei, et al.
Published: (2024)
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods
by: Chayti, El Mahdi, et al.
Published: (2023)
by: Chayti, El Mahdi, et al.
Published: (2023)
AbsTopK: Rethinking Sparse Autoencoders For Bidirectional Features
by: Zhu, Xudong, et al.
Published: (2025)
by: Zhu, Xudong, et al.
Published: (2025)
Individual Fairness In Strategic Classification
by: Zuo, Zhiqun, et al.
Published: (2026)
by: Zuo, Zhiqun, et al.
Published: (2026)
TRSVR: An Adaptive Stochastic Trust-Region Method with Variance Reduction
by: Fang, Yuchen, et al.
Published: (2026)
by: Fang, Yuchen, et al.
Published: (2026)
Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
by: Keane, Ronan
Published: (2024)
by: Keane, Ronan
Published: (2024)
Learning under Imitative Strategic Behavior with Unforeseeable Outcomes
by: Xie, Tian, et al.
Published: (2024)
by: Xie, Tian, et al.
Published: (2024)
Variance Reduction via Resampling and Experience Replay
by: Han, Jiale, et al.
Published: (2025)
by: Han, Jiale, et al.
Published: (2025)
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning
by: Sun, Jingruo, et al.
Published: (2025)
by: Sun, Jingruo, et al.
Published: (2025)
Variance Reduction Based Experience Replay for Policy Optimization
by: Zheng, Hua, et al.
Published: (2026)
by: Zheng, Hua, et al.
Published: (2026)
From Emergence to Control: Probing and Modulating Self-Reflection in Language Models
by: Zhu, Xudong, et al.
Published: (2025)
by: Zhu, Xudong, 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)
Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints
by: Ablin, Pierre, et al.
Published: (2023)
by: Ablin, Pierre, et al.
Published: (2023)
Self-Consuming Generative Models with Adversarially Curated Data
by: Wei, Xiukun, et al.
Published: (2025)
by: Wei, Xiukun, et al.
Published: (2025)
PRISM: Gauge-Invariant Tangent-Space Differentially Private LoRA
by: Wang, Shihao, et al.
Published: (2026)
by: Wang, Shihao, et al.
Published: (2026)
Variance Reduction for the Independent Metropolis Sampler
by: Liu, Siran, et al.
Published: (2024)
by: Liu, Siran, et al.
Published: (2024)
SPRINT: Efficient Spectral Priors for Humanoid Athletic Sprints
by: Wei, Yantong, et al.
Published: (2026)
by: Wei, Yantong, et al.
Published: (2026)
Variance Reduction and Low Sample Complexity in Stochastic Optimization via Proximal Point Method
by: Liang, Jiaming
Published: (2024)
by: Liang, Jiaming
Published: (2024)
Conformal Risk Minimization with Variance Reduction
by: Noorani, Sima, et al.
Published: (2024)
by: Noorani, Sima, et al.
Published: (2024)
SPRINT: Scalable Policy Pre-Training via Language Instruction Relabeling
by: Zhang, Jesse, et al.
Published: (2023)
by: Zhang, Jesse, et al.
Published: (2023)
On the transferability of Sparse Autoencoders for interpreting compressed models
by: Gupte, Suchit, et al.
Published: (2025)
by: Gupte, Suchit, et al.
Published: (2025)
Scaling Structure Aware Virtual Screening to Billions of Molecules with SPRINT
by: McNutt, Andrew T., et al.
Published: (2024)
by: McNutt, Andrew T., et al.
Published: (2024)
PPI-SVRG: Unifying Prediction-Powered Inference and Variance Reduction for Semi-Supervised Optimization
by: Ao, Ruicheng, et al.
Published: (2026)
by: Ao, Ruicheng, et al.
Published: (2026)
MARS-M: When Variance Reduction Meets Matrices
by: Liu, Yifeng, et al.
Published: (2025)
by: Liu, Yifeng, et al.
Published: (2025)
On the Reduction of Variance and Overestimation of Deep Q-Learning
by: Sabry, Mohammed, et al.
Published: (2019)
by: Sabry, Mohammed, et al.
Published: (2019)
The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL
by: Li, Yingru, et al.
Published: (2026)
by: Li, Yingru, et al.
Published: (2026)
Similar Items
-
Demographic-Agnostic Fairness without Harm
by: Cai, Zhongteng, et al.
Published: (2025) -
Lookahead Counterfactual Fairness
by: Zuo, Zhiqun, et al.
Published: (2024) -
Addressing Polarization and Unfairness in Performative Prediction
by: Jin, Kun, et al.
Published: (2024) -
Federated Learning with Reduced Information Leakage and Computation
by: Yin, Tongxin, et al.
Published: (2023) -
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
by: Xie, Tian, et al.
Published: (2024)