检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Huang, Shengyi Gallouedec, Quentin Felten, Florian Raffin, Antonin Dossa, Rousslan Fernand Julien Zhao, Yanxiao Sullivan, Ryan Makoviychuk, Viktor Makoviichuk, Denys Danesh, Mohamad H. Roumegous, Cyril Chen, Jiayi Weng Chufan Rahman, Md Masudur Araujo, Joao G.M. Quan, Guorui Tan, Daniel Klein, Timo Charakorn, Rujikorn Towers, Mark Berthelot, Yann Mehta, Kinal Chakraborty, Dipam Charraut, Arjun K.G. Valentin Ye, Chang Liu, Zichen Alegre, Lucas N. Nikulin, Alexander Hu, Xiao Liu, Tianlin Choi, Jongwook Yi, Brent Hugging Face United States Drexel University United States Univ. Lyon Centrale Lyon CNRS INSA Lyon UCBL LIRIS UMR 5205 France SnT University of Luxembourg Luxembourg RMC Wesling Germany Araya Inc. Tokyo Japan School of Computer Science and Technology University of Chinese Academy of Sciences China Chengdu Institute of Computer Applications Chinese Academy of Sciences China University of Maryland College Park United States NVIDIA United States Snap Inc. United States School of Computer Science McGill University Canada Polytech Montpellier DO France Zhejiang University China Department of Computer Science Purdue University United States Chinese University of Hong Kong Shenzhen China University College London United Kingdom Agency for Science Technology and Research Singapore Faculty of Computer Science University of Vienna Vienna Austria UniVie Doctoral School Computer Science University of Vienna Austria Thailand University of Southampton United Kingdom Univ. Lille Inria CNRS Centrale Lille UMR 9189 CRIStAL France Saint-Gobain Research Paris France International Institute of Information Technology Hyderabad India AIcrowd SA Switzerland Valeo Driving Assistance Research France New York University United States Sea AI Lab Singapore Institute of Informatics Federal University of Rio Grande do Sul Brazil Tinkoff Russia Department of Automation Tsinghua University China University of Basel Switzerland University of Michigan United States UC Berkeley United States

In many Reinforcement Learning (RL) papers, learning curves are useful indicators to measure the effectiveness of RL algorithms. However, the complete raw data of the learning curves are rarely available. As a result, it is usually necessary to reproduce the experiments from scratch, which can be time-consuming and errorprone. We present Open RL Benchmark, a set of fully tracked RL experiments, including not only the usual data such as episodic return, but also all algorithmspecific and system metrics. Open RL Benchmark is community-driven: anyone can download, use, and contribute to the data. At the time of writing, more than 25,000 runs have been tracked, for a cumulative duration of more than 8 years. Open RL Benchmark covers a wide range of RL libraries and reference implementations. Special care is taken to ensure that each experiment is precisely reproducible by providing not only the full parameters, but also the versions of the dependencies used to generate it. In addition, Open RL Benchmark comes with a command-line interface (CLI) for easy fetching and generating figures to present the results. In this document, we include two case studies to demonstrate the usefulness of Open RL Benchmark in practice. To the best of our knowledge, Open RL Benchmark is the first RL benchmark of its kind, and the authors hope that it will improve and facilitate the work of researchers in the field. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Limit Distribution of a Risk Estimate in the Problem of Inverting Linear Homogeneous Operators with a Random Sample Size

引用

Journal of Mathematical sciences (United States) 2020年第1期248卷 123-128页

作者： Shestakov, O.V. Department of Mathematical Statistics Faculty of Computational Mathematics and Cybernetics M.V. Lomonosov Moscow State University Moscow Russian Federation Institute of Informatics Problems Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russian Federation

Inverse statistical problems associated with the inversion of some linear homogeneous transformation arise in areas such as tomography, plasma physics, optics, etc. As a rule, noise is present in observations, and it is necessary to apply some regularization methods. Recently, methods of threshold processing of wavelet expansion coefficients have become popular. When using threshold processing methods, it is usually assumed that the number of decomposition coefficients is fixed and the noise distribution is Gaussian. This model has been well studied in the literature, and the optimal threshold values have been calculated for different classes of signal functions. However, in some situations, the sample size is not known in advance and has to be modeled by some random variable. In this paper, a model with a random number of observations is considered, and it is shown that the limit distribution of the mean-square risk estimate is a shift-scale mixture of normal laws. © 2020, Springer science+Business Media, LLC, part of Springer Nature.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Quantum advantage with light

Quantum advantage with light

引用

Quantum Computing, Communication, and Simulation 2021

作者： Zhong, Han-Sen Wang, Hui Deng, Yu-Hao Chen, Ming-Cheng Peng, Li-Chao Luo, Yi-Han Qin, Jian Wu, Dian Ding, Xing Hu, Yi Hu, Peng Yang, Xiao-Yan Zhang, Wei-Jun Li, Hao Li, Yuxuan Jiang, Xiao Gan, Lin Yang, Guangwen You, Lixing Wang, Zhen Li, Li Liu, Nai-Le Lu, Chao-Yang Pan, Jian-Wei Hefei National Laboratory for Physical Sciences at Microscale Department of Modern Physics University of Science and Technology of China Hefei Anhui230026 China CAS Ctr. for Excellence and Synergetic Innovation Centre in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai201315 China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences 865 Changning Road Shanghai200050 China Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Tsinghua University China

ISBN: (数字)9781510642348

ISBN: (纸本)9781510642331

We realize quantum computational advantage in a Gaussian Boson Sampling (GBS) experiment. We inject 25 two mode squeezed states into a 100-mode ultralow-loss interferometer with full connectivity and random matrix. We rule out thermal states, distinguishable photons, and uniform distribution hypotheses. This GBS machine can sample 14 orders of magnitude faster than classical supercomputer. © 2021 SPIE.

关键词： Quantum optics

来源：评论

学校读者我要写书评

暂无评论

Data Partition Optimization for High Energy Efficiency by Decoupling Local Dependence in Holographic Video Decoder

Data Partition Optimization for High Energy Efficiency by De...

引用

IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Xinzhe Liu Jianwen Luo David Blinder Fupeng Chen Heng Yu Peter Schelkens Francky Catthoor Yajun Ha School of Information Science and Technology ShanghaiTech University Shanghai China Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Department of Electronics and Informatics (ETRO) Vrije Universiteit Brussel (VUB) Belgium Interuniversity Microelectronics Centre (IMEC) Leuven Belgium Silicon Realization Group Synopsys Shanghai China School of Computer Science University of Nottingham Ningbo China Ningbo China Catholic University of Leuven (K.U.Leuven) Leuven Belgium Shanghai Engineering Research Center of Energy Efficient and Custom AI IC Shanghai China

Holography has attracted considerable attention from researchers due to its ability to store and recreate the wavefront emanating from a three-dimensional object. However, holographic video requires enormous resolution $(128 k \times 128 k)$ at the same frame rates(60fps) as normal video to achieve acceptable visual effects. Data compression is thus essential for its storage/transmission. When implementing its decompression pipeline on hardware for mobile scenarios, data dependency and energy consumption must be handled carefully. In this work, we present a novel design framework and a data partition optimization approach to optimize the overall energy consumption by tackling local dependence in the motion compensation module for holographic video codec, and exploring the design space of data partition layout. First, we propose a local data dependency propagation (LDDP) method that transforms one holographic frame with strong local dependence into multiple mutually independent virtual blocks without local dependence at all. Second, we formulate a model for the data partitioning problem, allowing us to analyze and optimize energy consumption by adjusting the layout of data partitions. Third, we provide a heuristic and efficient solution to the formulated model taking advantage of the target application scenarios. Experiment results in various scenarios show that our proposed optimization method achieves 2.94 ~ 3.91 $\times$ energy efficiency and 46.37% ~ 63.63% area efficiency compared to baseline approaches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Chaotic Rhythms as Indicators of Faults in Technical Systems

Chaotic Rhythms as Indicators of Faults in Technical Systems

引用

International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： A. V. Makshanov A. A. Musaev D. A. Grigoriev Department of Computing Systems and Computer Science Admiral Makarov State University of Maritime and Inland Shipping Saint-Petersburg Russia St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) St. Petersburg State Institute of Technology (Technical University) Saint-Petersburg Russia Center for Econometrics and Business Analytics (CEBA) St. Petersburg State University (SPBU) Saint-Petersburg Russia

This article discusses diagnostics of the condition of complex technical systems based on analyzing the internal rhythms of vibroacoustic measurement sequences from the perspective of chaotic dynamics. This approach significantly increases the interpretability of diagnostic information and, consequently, the quality of diagnostic choices. The diagnostic process is based on the hypothesis that there are strong correlations between the degree of malfunction, manifested in the deviation of the system state from the routine values, and indicators of the degree of randomness of the measured processes. In other words, the deviation of the technical system from its operational state leads to the emergence of nonlinear effects. These effects generate chaotic dynamics of the observed processes. The article proposes algorithms for detecting, visualizing and diagnosing chaotic rhythms in vibroacoustic time series.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On the Choice of Thresholding Parameters for Non-Gaussian Noise Distribution

引用

Journal of Mathematical sciences (United States) 2020年第4期246卷 519-524页

作者： Kudryavtsev, A.A. Shestakov, O.V. Department of Mathematical Statistics Faculty of Computational Mathematics and Cybernetics M. V. Lomonosov Moscow State University Moscow Russian Federation Institute of Informatics Problems Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russian Federation

The paper considers the problem of estimating the signal function from noisy observations using threshold processing of its wavelet expansion coefficients. Under general assumptions about the properties of the noise distribution, the asymptotic order of the optimal threshold is calculated, minimizing the loss function, based on the probability that the maximum error in the wavelet coefficients exceeds a given critical level. © 2020, Springer science+Business Media, LLC, part of Springer Nature.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mean-Square Risk of the Threshold Processing in the Problem of Inverting the Radon Transform with a Random Sample Size

引用

Journal of Mathematical sciences (United States) 2020年第1期248卷 46-50页

作者： Shestakov, O.V. Department of Mathematical Statistics Faculty of Computational Mathematics and Cybernetics M.V. Lomonosov Moscow State University Moscow Russia Institute of Informatics Problems Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russian Federation

Methods for reconstructing tomographic images based on the inversion of the Radon transform are used in problems arising in medicine, biology, astronomy, and many other fields. In the presence of noise in the projection data, as a rule, it is necessary to apply regularization methods. Recently, methods of the threshold processing of wavelet expansion coefficients have become popular. The analysis of errors of these methods is an important practical task, since it makes it possible to assess the quality of both the methods themselves and the equipment used. When using threshold processing, it is usually assumed that the number of expansion coefficients is fixed, and the noise distribution is Gaussian. This model is well studied in the literature, and the optimal values of the threshold processing parameters are calculated for different classes of functions. However, in some situations, the amount of data is not known in advance and has to be modeled with a certain random variable. In this paper, we consider a model with a random amount of data containing Gaussian noise, and estimate the order of the mean-square risk with an increasing number of decomposition coefficients. © 2020, Springer science+Business Media, LLC, part of Springer Nature.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Application of Kronecker convolutions in deep learning technique for automated detection of kidney stones with coronal CT images

引用

Information sciences 2023年 640卷

作者： Patro, Kiran Kumar Allam, Jaya Prakash Neelapu, Bala Chakravarthy Tadeusiewicz, Ryszard Acharya, U Rajendra Hammad, Mohamed Yildirim, Ozal Plawiak, Pawel Department of Electronics and Communication Engineering Aditya Institute of Technology and Management AP Tekkali532201 India Department of Electronics and Communication Engineering National Institute of Technology Rourkela Odisha Rourkela769008 India Department of Biotechnology and Medical Engineering National Institute of Technology Rourkela Odisha Rourkela769008 India AGH University of Science and Technology Department of Biocybernetics and Biomedical Engineering Krakow Poland School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia EIAS Data Science Lab College of Computer and Information Sciences Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology Faculty of Computers and Information Menoufia University Shibin El Kom32511 Egypt Department of Software Engineering Firat University Elazig Turkey Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 Krakow31-155 Poland Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland

Kidney stone disease is a serious public health concern that is getting worse with changes in diet, obesity, medical conditions, certain supplements etc. A kidney stone also called a renal calculus, is a hard buildup of urine minerals that form in the kidneys. Computed tomography (CT) is one of the imaging models used to identify kidney stones by clinical experts. Due to the low resolution of these images, sometimes detecting kidney stones is tedious with the naked eye, which may lead to false alarms. In this work, a computer-based diagnosis system with a deep learning technique has been developed as a practical solution to aid clinicians in their diagnosis. The traditional convolutional neural network (CNN)-based deep learning technology can detect stones in the kidney. Still, it suffers from the performance and standard implementation of the convolution operations in convolution layers. A Kronecker product-based convolution technique is incorporated in the proposed deep learning architecture to reduce the redundancy in feature maps without convolution overlapping. Our proposed method helps to make the network more effective by extracting abstract and in-depth features from the input images. The publicly available GitHub kidney stone CT scans are utilized to develop the proposed architecture. Our automated model detected kidney stones with an accuracy of 98.56% utilizing CT images. Our system is more effective than the most recent and cutting-edge techniques developed for identifying kidney stones of any size, including the smallest ones. © 2023 The Author(s)

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of a Cloud Computing System using Queuing Model with Correlated Task Reneging 5

Performance Analysis of a Cloud Computing System using Queui...

引用

5th International Scientific Conference on Information, Control, and Communication Technologies, ICCT 2021

作者： Kumar, Rakesh Soodan, Bhavneet Singh Kuaban, Godlove Suila Czekalski, Piotr Sharma, Sapana School of Mathematics Shri Mata Vaishno Devi University Jammu and Kashmir Katra182320 India Department of Mathematics and Statistics Namibia University of Science and Technology Private Bag 13388 Windhoek Namibia 13 Jackson Kaujeua Street Windhoek Namibia Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44 - 100 Poland Department of Computer Graphics. Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland Department of Mathematics Cluster University of Jammu Jammu and Kashmir India

Queuing theory has been extensively used in the modelling and performance analysis of cloud computing systems. The phenomenon of the task (or request) reneging, that is, the dropping of requests from the request queue often occur in cloud computing systems, and it is important to consider it when developing performance evaluations models for cloud computing infrastructures. Majority of studies in the performance evaluation of cloud computing data centres with the use of queuing theory do not consider the fact that the tasks could be removed from queue without being serviced. The removal of tasks from the queue could be due to the user impatience, execution deadline expiration, security reasons, or as an active queue management strategy. The reneging could be correlated in nature, that is, if a request is dropped (or reneged) at any time epoch, and then there is a probability that a request may or may not be dropped at the next time epoch. This kind of dropping (or reneging) of requests is referred to as correlated request reneging. In this paper we have modelled a cloud computing infrastructure with correlated request reneging using queuing theory. An M/M/1/N queuing model with correlated reneging has been used to study the performance analysis of the load balancing server of a cloud computing system. The steady-state as well as the transient performance analyses have been carried out. Important measures of performance like a vera ge queue size, average delay, probability of task blocking, and the probability of no waiting in the queue are studied. Finally, some comparisons are performed which describe the effect of correlated task reneging over simple exponential reneging. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Bounds on the rate of convergence for MtX/MtX/1 queueing models

arXiv

引用

arXiv 2021年

作者： Zeifman, Alexander Satin, Yacov Sipin, Alexander Vologda State University Vologda Russia Institute of Informatics Problems Federal Research Center "Computer Science and Control" Russian Academy of Sciences Moscow Russia Vologda Research Center Russian Academy of Sciences Vologda Russia Vologda State University Vologda Russia

We apply the method of differential inequalities for the computation of upper bounds for the rate of convergence to the limiting regime for one specific class of (in)homogeneous continuous-time Markov chains. To obtain these estimates, we investigate the corresponding forward system of Kolmogorov differential equations. Copyright © 2021, The Authors. All rights reserved.

关键词： Approximation theory

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：