Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Zheng, Shuyuan"'
Autor:
Liu, Junkai, Tong, Yujie, Huang, Hui, Zheng, Shuyuan, Yang, Muyun, Wu, Peicheng, Onizuka, Makoto, Xiao, Chuan
Legal facts refer to the facts that can be proven by acknowledged evidence in a trial. They form the basis for the determination of court judgments. This paper introduces a novel NLP task: legal fact prediction, which aims to predict the legal fact b
Externí odkaz:
http://arxiv.org/abs/2409.07055
Autor:
Zhong, Yongrui, Ge, Yunqing, Qin, Jianbin, Zheng, Shuyuan, Tang, Bo, Qiu, Yu-Xuan, Mao, Rui, Yuan, Ye, Onizuka, Makoto, Xiao, Chuan
Benchmarking is crucial for evaluating a DBMS, yet existing benchmarks often fail to reflect the varied nature of user workloads. As a result, there is increasing momentum toward creating databases that incorporate real-world user data to more accura
Externí odkaz:
http://arxiv.org/abs/2405.01312
Autor:
Wu, Zengqing, Peng, Run, Zheng, Shuyuan, Liu, Qianying, Han, Xu, Kwon, Brian Inhyuk, Onizuka, Makoto, Tang, Shaojie, Xiao, Chuan
Large Language Models (LLMs) have increasingly been utilized in social simulations, where they are often guided by carefully crafted instructions to stably exhibit human-like behaviors during simulations. Nevertheless, we doubt the necessity of shapi
Externí odkaz:
http://arxiv.org/abs/2402.12327
Autor:
Zheng, Shuyuan
甲第24933号
情博第844号
新制||情||141(附属図書館)
(主査)教授 伊藤 孝行, 教授 鹿島 久嗣, 教授 岡部 寿男, 阿部 正幸(NTT社会情報研究所)
学位規則第4条第1項該当
Doctor of Inf
情博第844号
新制||情||141(附属図書館)
(主査)教授 伊藤 孝行, 教授 鹿島 久嗣, 教授 岡部 寿男, 阿部 正幸(NTT社会情報研究所)
学位規則第4条第1項該当
Doctor of Inf
Externí odkaz:
http://hdl.handle.net/2433/285867
Computer simulations offer a robust toolset for exploring complex systems across various disciplines. A particularly impactful approach within this realm is Agent-Based Modeling (ABM), which harnesses the interactions of individual agents to emulate
Externí odkaz:
http://arxiv.org/abs/2311.06330
Publikováno v:
Proceedings of the VLDB Endowment, 16(7): 1657--1670, 2023
The Shapley value (SV) is a fair and principled metric for contribution evaluation in cross-silo federated learning (cross-silo FL), wherein organizations, i.e., clients, collaboratively train prediction models with the coordination of a parameter se
Externí odkaz:
http://arxiv.org/abs/2209.04856
Publikováno v:
In Ecological Indicators October 2024 167
Publikováno v:
Proceedings of the 2022 IEEE International Conference on Big Data, 1525-1534. (https://ieeexplore.ieee.org/document/10020232)
The difficulty in acquiring a sufficient amount of training data is a major bottleneck for machine learning (ML) based data analytics. Recently, commoditizing ML models has been proposed as an economical and moderate solution to ML-oriented data acqu
Externí odkaz:
http://arxiv.org/abs/2106.04384
There is a growing trend regarding perceiving personal data as a commodity. Existing studies have built frameworks and theories about how to determine an arbitrage-free price of a given query according to the privacy loss quantified by differential p
Externí odkaz:
http://arxiv.org/abs/2105.01651
Publikováno v:
In Ecological Indicators February 2024 159