Cover Image

Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhu, Jin, Li, Jingyi, Zhou, Hongyi, Lin, Yinan, Lin, Zhenhua, Shi, Chengchun
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Detecting LLM-Generated Text with Performance Guarantees
by: Zhou, Hongyi, et al.
Published: (2026)

Causal Deepsets for Off-policy Evaluation under Spatial or Spatio-temporal Interferences
by: Dai, Runpeng, et al.
Published: (2024)

Learn-to-Distance: Distance Learning for Detecting LLM-Generated Text
by: Zhou, Hongyi, et al.
Published: (2026)

Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning
by: Ye, Kai, et al.
Published: (2025)

Counterfactually Safe Reinforcement Learning
by: Li, Jingyi, et al.
Published: (2026)

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning
by: Gong, Shijin, et al.
Published: (2026)

Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
by: Zhou, Hongyi, et al.
Published: (2025)

Robust Sequential Experimental Design for A/B Testing
by: Wen, Qianglin, et al.
Published: (2026)

Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
by: Wu, Xiangkun, et al.
Published: (2026)

Demystifying Group Relative Policy Optimization: Its Policy Gradient is a U-Statistic
by: Zhou, Hongyi, et al.
Published: (2026)

Statistical Inference in Reinforcement Learning: A Selective Survey
by: Shi, Chengchun
Published: (2025)

AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees
by: Zhou, Hongyi, et al.
Published: (2025)

Integrating Active Learning in Causal Inference with Interference: A Novel Approach in Online Experiments
by: Zhu, Hongtao, et al.
Published: (2024)

Doubly Robust Alignment for Large Language Models
by: Xu, Erhan, et al.
Published: (2025)

Fighting Spurious Correlations in Text Classification via a Causal Learning Perspective
by: Zhou, Yuqing, et al.
Published: (2024)

Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
by: Wen, Qianglin, et al.
Published: (2024)

Spatial Deconfounder: Interference-Aware Deconfounding for Spatial Causal Inference
by: Khot, Ayush, et al.
Published: (2025)

Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning
by: Yu, Shuguang, et al.
Published: (2024)

Pessimistic Causal Reinforcement Learning with Mediators for Confounded Offline Data
by: Wang, Danyang, et al.
Published: (2024)

Perturbation is All You Need for Extrapolating Language Models
by: Cen, Zetai, et al.
Published: (2026)

Balancing the Reasoning Load: Difficulty-Differentiated Policy Optimization with Length Redistribution for Efficient and Robust Reinforcement Learning
by: Xia, Yinan, et al.
Published: (2026)

Combining Experimental and Historical Data for Policy Evaluation
by: Li, Ting, et al.
Published: (2024)

Fast Rerandomization for Balancing Covariates in Randomized Experiments: A Metropolis-Hastings Framework
by: Lu, Jiuyao, et al.
Published: (2026)

A Benchmark on Directed Graph Representation Learning in Hardware Designs
by: Wang, Haoyu, et al.
Published: (2024)

A Difference-in-Difference Approach to Detecting AI-Generated Images
by: Qi, Xinyi, et al.
Published: (2026)

From Authors to Reviewers: Leveraging Rankings to Improve Peer Review
by: Wang, Weichen, et al.
Published: (2025)

Reinforcement Learning from Human Feedback: A Statistical Perspective
by: Liu, Pangpang, et al.
Published: (2026)

Higher-Order Causal Message Passing for Experimentation with Complex Interference
by: Bayati, Mohsen, et al.
Published: (2024)

Causal Message Passing for Experiments with Unknown and General Network Interference
by: Shirani, Sadegh, et al.
Published: (2023)

Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness
by: Sun, Ke, et al.
Published: (2021)

Robust Offline Reinforcement learning with Heavy-Tailed Rewards
by: Zhu, Jin, et al.
Published: (2023)

Branch-Tuning: Balancing Stability and Plasticity for Continual Self-Supervised Learning
by: Liu, Wenzhuo, et al.
Published: (2024)

Dual Active Learning for Reinforcement Learning from Human Feedback
by: Liu, Pangpang, et al.
Published: (2024)

Learning Perturbations to Extrapolate Your LLM
by: Cen, Zetai, et al.
Published: (2026)

Hinge Regression Tree: A Newton Method for Oblique Regression Tree Splitting
by: Li, Hongyi, et al.
Published: (2026)

Observationally Informed Adaptive Causal Experimental Design
by: Gao, Erdun, et al.
Published: (2026)

D3HRL: A Distributed Hierarchical Reinforcement Learning Approach Based on Causal Discovery and Spurious Correlation Detection
by: Zhao, Chenran, et al.
Published: (2025)

Testing Stationarity and Change Point Detection in Reinforcement Learning
by: Li, Mengbing, et al.
Published: (2022)

Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding
by: Wang, Zhe, et al.
Published: (2024)

Stochastic Path Planning in Correlated Obstacle Fields
by: Zhou, Li, et al.
Published: (2025)