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Low-Rank Contextual Reinforcement Learning from Heterogeneous Human Feedback 基于异质人类反馈的低秩上下文强化学习
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-08-20 DOI: 10.1080/01621459.2026.2674413
Seong Jin Lee, Will Wei Sun, Yufeng Liu
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引用次数: 0
Rejoinder: The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review 答辩：ICML 2023排名实验：检查ML/AI同行评审中的作者自我评估
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-08-20 DOI: 10.1080/01621459.2026.2672763
Buxin Su, Jiayao Zhang, Natalie Collina, Yuling Yan, Didong Li, Kyunghyun Cho, Jianqing Fan, Aaron Roth, Weijie Su
{"title":"Rejoinder: The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review","authors":"Buxin Su, Jiayao Zhang, Natalie Collina, Yuling Yan, Didong Li, Kyunghyun Cho, Jianqing Fan, Aaron Roth, Weijie Su","doi":"10.1080/01621459.2026.2672763","DOIUrl":"https://doi.org/10.1080/01621459.2026.2672763","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"12 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148767382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Discussion of “The ICML 2023 Ranking Experiment” by Su et al. 关于Su等人“ICML 2023排序实验”的讨论
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-08-20 DOI: 10.1080/01621459.2025.2588464
Andreas Haupt, Sanmi Koyejo
{"title":"Discussion of “The ICML 2023 Ranking Experiment” by Su et al.","authors":"Andreas Haupt, Sanmi Koyejo","doi":"10.1080/01621459.2025.2588464","DOIUrl":"https://doi.org/10.1080/01621459.2025.2588464","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"36 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148767391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Discussion of “The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review” “ICML 2023排名实验：检验ML/AI同行评议中的作者自我评估”讨论
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-08-20 DOI: 10.1080/01621459.2026.2638494
Ying Wang, Mengye Ren
{"title":"Discussion of “The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review”","authors":"Ying Wang, Mengye Ren","doi":"10.1080/01621459.2026.2638494","DOIUrl":"https://doi.org/10.1080/01621459.2026.2638494","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"33 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148767384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Discussion of “The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review” “ICML 2023排名实验：检验ML/AI同行评议中的作者自我评估”讨论
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-08-20 DOI: 10.1080/01621459.2025.2612634
Linjun Zhang, Lexin Li
{"title":"Discussion of “The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review”","authors":"Linjun Zhang, Lexin Li","doi":"10.1080/01621459.2025.2612634","DOIUrl":"https://doi.org/10.1080/01621459.2025.2612634","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"63 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148767390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comments: Can Statistics and AI Technologies Help Our Troubled Review System? 评论：统计和人工智能技术能帮助我们陷入困境的审查系统吗？
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-08-20 DOI: 10.1080/01621459.2026.2657554
Xiao-Li Meng
{"title":"Comments: Can Statistics and AI Technologies Help Our Troubled Review System?","authors":"Xiao-Li Meng","doi":"10.1080/01621459.2026.2657554","DOIUrl":"https://doi.org/10.1080/01621459.2026.2657554","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"376 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148767385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
From Authors to Reviewers: Leveraging Rankings to Improve Peer Review 从作者到审稿人：利用排名来改善同行评审
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-08-20 DOI: 10.1080/01621459.2025.2568056
Weichen Wang, Chengchun Shi
{"title":"From Authors to Reviewers: Leveraging Rankings to Improve Peer Review","authors":"Weichen Wang, Chengchun Shi","doi":"10.1080/01621459.2025.2568056","DOIUrl":"https://doi.org/10.1080/01621459.2025.2568056","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"2 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148767388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage. 构建遗传风险评分：稳健贝叶斯方法通过预测汇总统计和灵活收缩。
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-07-13 DOI: 10.1080/01621459.2026.2663587
Yuzheng Dun,Nilanjan Chatterjee,Jin Jin,Akihiko Nishimura
{"title":"Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage.","authors":"Yuzheng Dun,Nilanjan Chatterjee,Jin Jin,Akihiko Nishimura","doi":"10.1080/01621459.2026.2663587","DOIUrl":"https://doi.org/10.1080/01621459.2026.2663587","url":null,"abstract":"Polygenic risk scores (PRS) developed from genome-wide association studies (GWAS) can be used for risk stratification by quantifying the genetic contribution to disease, and many clinical applications have been proposed. Bayesian methods are popular for building PRS because of their natural ability to regularize models and incorporate external information. In this article, we present new theoretical results, methods, and extensive numerical studies to advance Bayesian methods for PRS applications. We identify a potential risk, under a common Bayesian PRS framework, of posterior impropriety when integrating the required GWAS summary statistics and linkage disequilibrium (LD) data from distinct sources. As a principled remedy, we propose a projection of the summary statistics that ensures compatibility between the two sources and in turn a proper behavior of the posterior. We further introduce a new PRS method, with accompanying software, under the less-explored Bayesian bridge prior to more flexibly model varying sparsity levels in effect-size distributions. We extensively benchmark it against alternative Bayesian methods using synthetic and real datasets, quantifying the impact of prior specification and LD estimation strategy. Our proposed PRS-Bridge, equipped with the projection technique and flexible prior, demonstrates the most consistent and generally superior performance across a variety of scenarios.","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"10 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148432652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhanced Marginal Sensitivity Model and Bounds 增强边际敏感性模型和边界
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-07-08 DOI: 10.1080/01621459.2026.2699465
Yi Zhang, Wenfu Xu, Zhiqiang Tan
{"title":"Enhanced Marginal Sensitivity Model and Bounds","authors":"Yi Zhang, Wenfu Xu, Zhiqiang Tan","doi":"10.1080/01621459.2026.2699465","DOIUrl":"https://doi.org/10.1080/01621459.2026.2699465","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"64 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148416286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
MOSAiC: Multi-site One-Shot Aggregation of Compressed Risk Functions 马赛克：压缩风险函数的多站点单次聚合
IF 3.7 1区 数学
Journal of the American Statistical Association Pub Date : 2026-07-08 DOI: 10.1080/01621459.2026.2698025
Yong Chen, Yiwen Lu, Jing-Mei Qiu, Huiyuan Wang, Yudong Wang
{"title":"MOSAiC: Multi-site One-Shot Aggregation of Compressed Risk Functions","authors":"Yong Chen, Yiwen Lu, Jing-Mei Qiu, Huiyuan Wang, Yudong Wang","doi":"10.1080/01621459.2026.2698025","DOIUrl":"https://doi.org/10.1080/01621459.2026.2698025","url":null,"abstract":"","PeriodicalId":17227,"journal":{"name":"Journal of the American Statistical Association","volume":"62 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148415941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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