Phase I I/UCRC Carnegie Mellon University: Center for Big Learning CBL

第一阶段 I/UCRC 卡内基梅隆大学:大学习中心 CBL

基本信息

  • 批准号:
    1747769
  • 负责人:
  • 金额:
    $ 75万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-02-15 至 2018-07-31
  • 项目状态:
    已结题

项目摘要

This project establishes the Industry/University Cooperative Research Center for Big Learning (CBL). With substantial breakthroughs in deep learning, the renaissance of machine intelligence is unfolding. The vision is to create intelligence towards the intelligence-driven society. Through catalyzing the fusion of diverse expertise from the consortium of faculty members, students, industry partners, and federal agencies, CBL seeks to create state-of-the-art deep learning methodologies and technologies and enable intelligent applications, transforming broad domains, such as business, media, healthcare, Internet-of-Things, and cybersecurity. This timely initiative creates a unique platform for empowering our next-generation talents with real-world relevance and significance.The mission is to pioneer novel deep learning algorithms, intelligent systems, and novel applications through unified and coordinated efforts in the CBL consortium via fusion of broad expertise from our large number of center faculty members, students, industry partners, and government agencies. The Carnegie-Mellon University site will focus on deep learning algorithms and platforms and work with other sites on novel applications.The CBL is expected to have broad transformative impacts in technologies, education, and the society. CBL seeks to create pioneering research and applications to address a broad spectrum of real-world challenges, making significant contributions and impacts to the deep learning community, the industry and the society at large. The discoveries from CBL will make significant contributions to promote products and industrial services in general and CBL industry partners in particular. As the magnet of deep learning research and applications, CBL offers an ideal platform to nurture next-generation talents through world-class mentors from both academia and industry, disseminate the cutting-edge technologies, and facilitate industry/university collaborative research.The center repository will be hosted at http://nsfcbl.org. The data, code, documents will be well organized and maintained on the CBL server for the duration of the center plus five years. The internal code repository will be managed by GitLab. After the software packages are well documented and tested, they will be released and managed by popular public servers, such as GitHub and Bitbucket.
该项目建立了大学习产业/大学合作研究中心(CBL)。随着深度学习的重大突破,机器智能的复兴正在展开。我们的愿景是创造智能,走向智能驱动的社会。通过促进来自教师,学生,行业合作伙伴和联邦机构联盟的各种专业知识的融合,CBL寻求创建最先进的深度学习方法和技术,并实现智能应用,转变广泛的领域,如商业,媒体,医疗保健,物联网和网络安全。CBL的使命是通过CBL联盟的统一和协调努力,通过融合我们大量中心教职员工、学生、行业合作伙伴和政府机构的广泛专业知识,为我们的下一代人才提供一个独特的平台,使其具有现实意义和重要性。该网站将专注于深度学习算法和平台,并与其他网站合作开发新的应用程序。CBL预计将在技术,教育和社会方面产生广泛的变革性影响。CBL致力于开创性的研究和应用,以应对广泛的现实挑战,为深度学习社区、行业和整个社会做出重大贡献和影响。CBL的发现将为促进产品和工业服务,特别是CBL行业合作伙伴做出重大贡献。作为深度学习研究和应用的磁石,CBL提供了一个理想的平台,通过来自学术界和工业界的世界级导师培养下一代人才,传播前沿技术,促进产学合作研究。中心存储库将托管在http://nsfcbl.org上,数据,代码,文档将在CBL服务器上进行良好的组织和维护,为期五年。内部代码库将由GitLab管理。在软件包经过良好的文档记录和测试后,它们将由流行的公共服务器(如GitHub和Bitbucket)发布和管理。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Ruslan Salakhutdinov其他文献

Ground-truthed and high-resolution drone images of the leafy spurge weed plant (Euphorbia esula)
多叶大戟杂草(大戟属)的实地验证和高分辨率无人机图像
  • DOI:
    10.1038/s41597-025-05094-6
  • 发表时间:
    2025-05-06
  • 期刊:
  • 影响因子:
    6.900
  • 作者:
    Kyle Doherty;Max Gurinas;Erik Samsoe;Charles Casper;Beau Larkin;Philip Ramsey;Brandon Trabucco;Ruslan Salakhutdinov
  • 通讯作者:
    Ruslan Salakhutdinov
DeCoT: Debiasing Chain-of-Thought for Knowledge-Intensive Tasks in Large Language Models via Causal Intervention
DeCoT:通过因果干预消除大型语言模型中知识密集型任务的思维链偏差
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Tamera Lanham;Anna Chen;Ansh Radhakrishnan;Benoit Steiner;Carson E. Denison;Danny Hernan;Dustin Li;Esin Durmus;Evan Hubinger;Xingxuan Li;Yew Ruochen Zhao;Bosheng Ken Chia;Zhoubo Li;Ningyu Zhang;Yunzhi Yao;Meng Wang;Kaixin Ma;Hao Cheng;Xiaodong Liu;Eric Nyberg;Alex Troy Mallen;Akari Asai;Victor Zhong;Rajarshi Das;Stephen L. Morgan;Christopher Winship;Weijia Shi;Xiaochuang Han;Mike Lewis;Luke Tsvetkov;Zettlemoyer Scott;Wen;Xin Su;Tiep Le;Steven Bethard;Yifan Kai Sun;Ethan Xu;Hanwen Zha;Yue Liu;Hugo Touvron;Louis Martin;Kevin Stone;Peter Al;Amjad Almahairi;Yasmine Babaei;Nikolay;Cunxiang Wang;Xiaoze Liu;Xian;Keheng Wang;Feiyu Duan;Peiguang Sirui Wang;Junda Wu;Tong Yu;Shuai Li;Deconfounded;Suhang Wu;Min Peng;Yue Chen;Jinsong Su;Shicheng Xu;Liang Pang;Huawei Shen;Xueqi Cheng;Zhilin Yang;Peng Qi;Saizheng Zhang;Yoshua Ben;William Cohen;Ruslan Salakhutdinov;Jia;Kun;Zhen;Chenhan Yuan;Qianqian Xie;Jimin Huang;Li;Yangyi Chen;Ganqu Cui;Hongcheng;Fangyuan Gao;Xingyi Zou;Heng Cheng;Ji
  • 通讯作者:
    Ji
Ordovician mantle dynamics in NE-Japan constraints from layered structures of Cumulate Member in the Hayachine-Miyamori Ophiolite
日本东北部奥陶纪地幔动力学受早山-宫森蛇绿岩堆积段层状结构的约束
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Makoto Yamada;Denny Wu;Yao-Hung Hubert Tsai;Hirofumi Ohta;Ruslan Salakhutdinov;Ichiro Takeuchi;Kenji Fukumizu;木村 皐史・小澤 一仁・飯塚 毅
  • 通讯作者:
    木村 皐史・小澤 一仁・飯塚 毅
Tree Search for Language Model Agents
语言模型代理的树搜索
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jing Yu Koh;Stephen McAleer;Daniel Fried;Ruslan Salakhutdinov
  • 通讯作者:
    Ruslan Salakhutdinov
C AUSAL R: Causal Reasoning over Natural Language Rulebases
C AUSAL R:自然语言规则库的因果推理
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jason Weston;Antoine Bordes;S. Chopra;Thomas Wolf;Lysandre Debut;Julien Victor Sanh;Clement Chaumond;Anthony Delangue;Pier;Tim ric Cistac;Rémi Rault;Morgan Louf;Funtow;Sam Davison;Patrick Shleifer;V. Platen;Clara Ma;Yacine Jernite;J. Plu;Canwen Xu;Zhilin Yang;Peng Qi;Saizheng Zhang;Y. Bengio;William Cohen;Ruslan Salakhutdinov
  • 通讯作者:
    Ruslan Salakhutdinov

Ruslan Salakhutdinov的其他文献

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{{ truncateString('Ruslan Salakhutdinov', 18)}}的其他基金

AF: RI: Medium: Collaborative Research: Understanding and Improving Optimization in Deep and Recurrent Networks
AF:RI:中:协作研究:理解和改进深度和循环网络的优化
  • 批准号:
    1763562
  • 财政年份:
    2018
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant
Carnegie Mellon University Planning Grant: I/UCRC for Big Learning
卡内基梅隆大学规划补助金:I/UCRC for Big Learning
  • 批准号:
    1650485
  • 财政年份:
    2017
  • 资助金额:
    $ 75万
  • 项目类别:
    Standard Grant

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