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检索条件"机构=Research Center of Machine Learning and Data Analysis"
295 条 记 录,以下是21-30 订阅
排序:
A MEMORY EFFICIENT RANDOMIZED SUBSPACE OPTIMIZATION METHOD FOR TRAINING LARGE LANGUAGE MODELS
arXiv
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arXiv 2025年
作者: Chen, Yiming Zhang, Yuan Liu, Yin Yuan, Kun Wen, Zaiwen Beijing International Center for Mathematical Research Peking University Beijing China Center for Data Science Peking University Beijing China Center for Machine Learning Research Peking University Beijing China
The memory challenges associated with training Large Language Models (LLMs) have become a critical concern, particularly when using the Adam optimizer. To address this issue, numerous memory-efficient techniques have ...
来源: 评论
EPR-Net: constructing a non-equilibrium potential landscape via a variational force projection formulation
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National Science Review 2024年 第7期11卷 135-147页
作者: Yue Zhao Wei Zhang Tiejun Li Center for Data Science Peking University Zuse Institute Berlin Department of Mathematics and Computer Science Freie Universit?t Berlin Laboratory of Mathematics and Applied Mathematics(LMAM)and School of Mathematical Sciences Peking University Center for Machine Learning Research Peking University
We present EPR-Net, a novel and effective deep learning approach that tackles a crucial challenge in biophysics: constructing potential landscapes for high-dimensional non-equilibrium steady-state ***-Net leverages a ... 详细信息
来源: 评论
Method for Finding an Investment Strategy in the Case of a Sparse Covariance Matrix
Method for Finding an Investment Strategy in the Case of a S...
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International Conference on Management of Large-Scale System Development (MLSD)
作者: Victor Gorelik Tatiana Zolotova Department of Simulation Systems and Operations Research Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia Department of Data Analysis and Machine Learning Financial University under the Government of the Russian Federation Moscow Russia
An optimality principle is proposed for making investment decisions based on efficiency and risk assessments with a sparse covariance matrix. The method is implemented as a program with a graphical interface and demon... 详细信息
来源: 评论
How Transformers Get Rich: Approximation and Dynamics analysis
arXiv
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arXiv 2024年
作者: Wang, Mingze Yu, Ruoxi Weinan, E. Wu, Lei School of Mathematical Sciences Peking University China School of Mathematical Sciences Center for Machine Learning Research AI for Science Institute Peking University China Center for Data Science Peking University China School of Mathematical Sciences Center for Machine Learning Research Peking University China
Transformers have demonstrated exceptional in-context learning capabilities, yet the theoretical understanding of the underlying mechanisms remains limited. A recent work (Elhage et al., 2021) identified a "rich&... 详细信息
来源: 评论
Multi-Scale Clinical-Guided Binocular Fusion Framework for Predicting New-Onset Hypertension Over a Four-Year Period
Multi-Scale Clinical-Guided Binocular Fusion Framework for P...
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IEEE International Symposium on Biomedical Imaging
作者: Haoshen Li Zifan Chen Jie Zhao Heyun Chen Hexin Dong Mingze Yuan Bin Dong Li Zhang Center for Data Science Peking University China National Engineering Laboratory for Big Data Analysis and Applications Peking University China Peking University Changsha Institute for Computing and Digital Economy China Beijing International Center for Mathematical Research Peking University China Center for Machine Learning Research Peking University China
Hypertension is a major global health concern, linked to various cardiovascular diseases and associated with distinct ocular manifestations. While recent advances in artificial intelligence have enabled accurate diagn... 详细信息
来源: 评论
Revealing excited states of rotational Bose-Einstein condensates
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The Innovation 2024年 第1期5卷 41-48页
作者: Jianyuan Yin Zhen Huang Yongyong Cai Qiang Du Lei Zhang School of Mathematical Sciences Laboratory of Mathematics and Applied MathematicsPeking UniversityBeijing 100871China Department of Mathematics National University of SingaporeSingapore 119076Singapore Department of Mathematics University of CaliforniaBerkeleyBerkeleyCA 94720USA School of Mathematical Sciences Beijing Normal UniversityBeijing 100875China Department of Applied Physics and Applied Mathematics and Data Science Institute Columbia UniversityNew YorkNY 10027USA Beijing International Center for Mathematical Research Center for Quantitative BiologyCenter for Machine Learning ResearchPeking UniversityBeijing 100871China
Rotational Bose-Einstein condensates can exhibit quantized vortices as topological *** this study,the ground and excited states of the rotational Bose-Einstein condensates are systematically studied by calculating the... 详细信息
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ENHANCING ZEROTH-ORDER FINE-TUNING FOR LANGUAGE MODELS WITH LOW-RANK STRUCTURES
arXiv
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arXiv 2024年
作者: Chen, Yiming Zhang, Yuan Cao, Liyuan Yuan, Kun Wen, Zaiwen Beijing International Center for Mathematical Research Peking University Beijing China Center for Data Science Peking University Beijing China Center for Machine Learning Research Peking University Beijing China
Parameter-efficient fine-tuning (PEFT) significantly reduces memory costs when adapting large language models (LLMs) for downstream applications. However, traditional first-order (FO) fine-tuning algorithms incur subs...
来源: 评论
Thai Conversational Chatbot Classification Using BiLSTM and data Augmentation  1st
Thai Conversational Chatbot Classification Using BiLSTM and ...
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1st International Conference on data Science and Artificial Intelligence, DSAI 2023
作者: Lhasiw, Nunthawat Tanantong, Tanatorn Sanglerdsinlapachai, Nuttapong Thammasat Research Unit in Data Innovation and Artificial Intelligence Department of Computer Science Faculty of Science and Technology Thammasat University Pathum Thani Thailand Strategic Analytics Networks with Machine Learning and AI Research Team National Electronics and Computer Technology Center Pathum Thani Thailand
Chatbot platforms, e.g., Facebook and Line, have revolutionized human interaction in the digital age. In order to develop an automatic chatbot classification, there are several challenges especially for Thai chat mess... 详细信息
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Deliberative XAI: How Explanations Impact Understanding and Decision-Making of AI Novices in Collective and Individual Settings
arXiv
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arXiv 2024年
作者: Schmude, Timothée Koesten, Laura Möller, Torsten Tschiatschek, Sebastian University of Vienna Faculty of Computer Science Research Network Data Science Doctoral School Computer Science Austria University of Vienna Faculty of Computer Science Research Group Visualization and Data Analysis Austria University of Vienna Faculty of Computer Science Research Group Visualization and Data Analysis Research Network Data Science Austria University of Vienna Faculty of Computer Science Research Network Data Science Research Group Data Mining and Machine Learning Austria
XAI research often focuses on settings where people learn about and assess algorithmic systems individually. However, as more public AI systems are deployed, it becomes essential for XAI to facilitate collective under...
来源: 评论
NC-ALG: Graph-Based Active learning under Noisy Crowd  40
NC-ALG: Graph-Based Active Learning under Noisy Crowd
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40th IEEE International Conference on data Engineering, ICDE 2024
作者: Zhang, Wentao Wang, Yexin You, Zhenbang Li, Yang Cao, Gang Yang, Zhi Cui, Bin Center for Machine Learning Research Peking University China Key Lab of High Confidence Software Technologies Peking University China Institute of Advanced Algorithms Research Shanghai China Institute of Computational Social Science Peking University Qingdao China National Engineering Labratory for Big Data Analytics and Applications China TEG Tencent Inc. Department of Data Platform China Beijing Academy of Artificial Intelligence China
Graph Neural Networks (GNNs) have achieved great success in various data mining tasks but they heavily rely on a large number of annotated nodes, requiring considerable human efforts. Despite the effectiveness of exis... 详细信息
来源: 评论