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Improving Generative Model-based Unfolding with Schrödinger Bridges

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arXiv 2023年

作者： Diefenbacher, Sascha Liu, Guan-Horng Mikuni, Vinicius Nachman, Benjamin Nie, Weili Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Autonomous Control and Decision Systems Laboratory Georgia Institute of Technology AtlantaGA30332 United States National Energy Research Scientific Computing Center Berkeley Lab BerkeleyCA94720 United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States Machine Learning Research Group NVIDIA Research United States

Machine learning-based unfolding has enabled unbinned and high-dimensional differential cross section measurements. Two main approaches have emerged in this research area: one based on discriminative models and one based on generative models. The main advantage of discriminative models is that they learn a small correction to a starting simulation while generative models scale better to regions of phase space with little data. We propose to use Schrödinger Bridges and diffusion models to create SBUnfold, an unfolding approach that combines the strengths of both discriminative and generative models. The key feature of SBUnfold is that its generative model maps one set of events into another without having to go through a known probability density as is the case for normalizing flows and standard diffusion models. We show that SBUnfold achieves excellent performance compared to state of the art methods on a synthetic Z+jets dataset. © 2023, CC BY.

关键词： Phase space methods

Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms

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arXiv 2022年

作者： Li, Yang Lin, Qingfeng Liu, Ya-Feng Ai, Bo Wu, Yik-Chung Shenzhen Research Institute of Big Data Shenzhen518172 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China

Device activity detection in the emerging cell-free massive multiple-input multiple-output (MIMO) systems has been recognized as a crucial task in machine-type communications, in which multiple access points (APs) jointly identify the active devices from a large number of potential devices based on the received signals. Most of the existing works addressing this problem rely on the impractical assumption that different active devices transmit signals synchronously. However, in practice, synchronization cannot be guaranteed due to the low-cost oscillators, which brings additional discontinuous and nonconvex constraints to the detection problem. To address this challenge, this paper reveals an equivalent reformulation to the asynchronous activity detection problem, which facilitates the development of a centralized algorithm and a distributed algorithm that satisfy the highly nonconvex constraints in a gentle fashion as the iteration number increases, so that the sequence generated by the proposed algorithms can get around bad stationary points. To reduce the capacity requirements of the fronthauls, we further design a communication-efficient accelerated distributed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms outperform state-of-the-art approaches, and the proposed accelerated distributed algorithm achieves a close detection performance to that of the centralized algorithm but with a much smaller number of bits to be transmitted on the fronthaul links. Copyright © 2022, The Authors. All rights reserved.

关键词： Internet of things

Intellectual multi agent control of tripod 5th

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Intellectual multi agent control of tripod

5th International Conference on Robot Intelligence Technology and Applications, RiTA 2017

作者： Gaiduk, Anatoliy Kapustyan, Sergey Dyachenko, Alexander Prakapovich, Ryhor Podmazov, Ivan Department of Automatic Control Systems Southern Federal University Taganrog Russia Southern Scientific Center of the Russian Academy of Sciences Rostov-on-Don Russia Scientific Research Institute of Multiprocessor Computer Systems Southern Federal University Taganrog Russia United Institute of Informatics Problems NAS of Belarus Minsk Belarus

ISBN: (纸本)9783319784519

The analytical design method of the intellectual multi agent control for the mechanism of parallel structure of type the manipulator-tripod is considered in this paper. Tripod is intended for maintenance of the spatial technological movements of the a gripper with a working tool. A tripod’s construction is simple, but if the tripod’s control is intellectual then the big variety of technological operations can be realized. The tripod’s control system includes three agents. The algorithms of these agents are designed here. Application of the multi agent system simplifies the algorithm of the tripod’s control, in particular, with using of the intellectual approach. © Springer International Publishing AG, part of Springer Nature 2019.

关键词： Manipulators

Stable recovery of entangled weights: Towards robust identification of deep neural networks from minimal samples

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arXiv 2021年

作者： Fiedler, Christian Fornasier, Massimo Klock, Timo Rauchensteiner, Michael Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Heisenbergstr. 3 Stuttgart70569 Germany Institute for Data Science in Mechanical Engineering RWTH-Aachen University Dennewartstraße 27 Aachen50868 Germany Department of Mathematics Bolzmannstraße 3 85748 Garching Germany Department of Numerical Analysis and Scientific Computing Simula Research Laboratory Oslo Norway Department of Mathematics University of San Diego California San Diego United States

In this paper we approach the problem of unique and stable identifiability of generic deep artificial neural networks with pyramidal shape and smooth activation functions from a finite number of input-output samples. More specifically we introduce the so-called entangled weights, which compose weights of successive layers intertwined with suitable diagonal and invertible matrices depending on the activation functions and their shifts. We prove that entangled weights are completely and stably approximated by an efficient and robust algorithm as soon as O(D2 × m) nonadaptive input-output samples of the network are collected, where D is the input dimension and m is the number of neurons of the network. Moreover, we empirically observe that the approach applies to networks with up to O(D × mL) neurons, where mL is the number of output neurons at layer L. Provided knowledge of layer assignments of entangled weights and of remaining scaling and shift parameters, which may be further heuristically obtained by least squares, the entangled weights identify the network completely and uniquely. To highlight the relevance of the theoretical result of stable recovery of entangled weights, we present numerical experiments, which demonstrate that multilayered networks with generic weights can be robustly identified and therefore uniformly approximated by the presented algorithmic pipeline. In contrast backpropagation cannot generalize stably very well in this setting, being always limited by relatively large uniform error. In terms of practical impact, our study shows that we can relate input-output information uniquely and stably to network parameters, providing a form of explainability. Moreover, our method paves the way for compression of overparametrized networks and for the training of minimal complexity *** Codes 65D15, 68T07, 90C26 Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

Conception of Ontology for Computer Methods of Paintings Analysis

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Conception of Ontology for Computer Methods of Paintings Ana...

2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019

作者： Beloozerov, Viktor Murashov, Dmitrij Trusova, Yuliya Berezin, Aleksej Ivanova, Ekaterina All-Russia Institute for Scientific and Technical Information Department for Classification Systems Development Moscow Russia Institute of Educational Informatics Federal Research Center 'Information and Control' Moscow Russia A. A. Dorodnicyn Computing Center Federal Research Center 'Information and Control' Moscow Russia State Historical Muzeum Restoration Department Moscow Russia Ilya Glazuvov Russian Academy of Painting Sculpture and Architecture Department of Painting Restoration Moscow Russia

ISBN: (纸本)9781728144016

This paper describes the procedure of developing the 'OntArt' ontology for the subject area 'Attribution and restoration of works of easel oil painting'. Special attention is paid to the domain of computer methods application. The basis of the work is a previously developed thesaurus of this domain. The conceptual shell of the original thesaurus descriptors is the standard CIDOC CRM framework, which binds domain concepts to abstract philosophical categories. In order to connect particular concepts with abstract categories, it is proposed to include 21 intermediate-level conceptual classes in the CIDOC CRM structure. Thus, we have built a formalized structure of concepts for the area of attribution and restoration of painting, ranging from the highest philosophical abstractions to specialized methods of computer analysis of picture images. This structure includes about 1300 terms in Russian. The English part has about 500 terms and is replenished as the interlanguage equivalence of the terms is agreed. In the part of vocabulary of computer methods, we have a full bilingual ontology with one-To-one correspondence of the Russian and English versions. The current version of the ontology is implemented as a TiddlyWiki software module and is publicly available. © 2019 IEEE.

关键词： Ontology

The Cognitive Approach to the Coverage-Directed Test Generation

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Advances in Intelligent systems and computing 2018年 662卷 372-380页

作者： Klimenko, Anna Gorelova, Galina Korobkin, Vladimir Bibilo, Petr SFedU Acad. Kalyaev Scientific Research Institute of Multiprocessor Computer Systems Taganrog Russia SFedU Rostov-on-Don Russia Scientific-Research Institute of Multiprocessor Computing and Control Systems Taganrog Russia The State Scientific Institution "The United Institute of Informatics Problems of the National Academy of Sciences of Belarus" Minsk Belarus

ISBN: (纸本)9783319676203

The important contemporary issue of VLSI design verification is its time-consuming. The hardware model, written, for instance, with VHDL, is verified by formal and dynamic verification approaches. Dynamic verification (simulation) is widely-used due to the possibility of full automation of the process, but takes too much time due to its redundancy. The concept of the coverage-directed test generation is to redirect the test generator such as to reach uncovered metric points. There are several approaches for this, including genetic algorithms using, Bayesian network, Data mining, etc. The new cognitive approach to the coverage-directed test generation (CA CDG) is proposed within this paper. It is based on a cognitive map usage. The CA CDG is described, some simulation results are given. Also the future work areas are outlined. © 2018, Springer International Publishing AG.

关键词： Bayesian networks

Fog computing in new approach for monitoring of hazardous phenomena

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Journal of Physics: Conference Series 2019年第7期1333卷

作者： E V Melnik M V Orda-Zhigulina D V Orda-Zhigulina D Y Ivanov A A Rodina Southern Scientific Center of the Russian Academy of Sciences 41 Chekhova str. Rostov-on-Don 344006 Russia Research Institute for Multiprocessor Computing Systems of the Southern Federal University 2 Chekhova str. Taganrog 347922 Russia

This paper presents an investigation on applying fog computing to develop a new system of forecasting and monitoring of hazardous phenomena and ensuring the population safety. So, there have been various negative natural phenomena and processes that affect the coastal areas and coastal infrastructure in Ponto-Caspian region recently. Currently, data of hydrological, meteorological and biological monitoring systems are splitted. At present one of the promising trends of developing new methods and algorithms for the forecasting and monitoring systems of natural hazardous phenomena is processing of large volumes of unstructured data coming from various sources, detectors and so on. The authors of the paper estimate the developing of the methods and algorithms of forecasting and monitoring of hazardous phenomena and ensuring the population safety that could be realized in the base of fog computing.

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Reply to Baba and Kanamori

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Clinical infectious diseases : an official publication of the Infectious Diseases Society of America 2020年第5期71卷 1353-1355页

作者： Eelco Franz Ovidiu Rotariu Bruno S Lopes James L Bono Chad Laing Victor Gannon Angela H A M Van Hoek Ingrid Friesema Nigel P French Tessy George Patrick J Biggs Patricia Jaros Marta Rivas Isabel Chinen Josefina Campos Glen E Mellor P Scott Chandry Francisco Perez-Reche Ken J Forbes Norval Jc Strachan National Institute for Public Health and the Environment Centre for Infectious Disease Control Bilthoven The Netherlands. School of Biological Sciences University of Aberdeen Aberdeen Scotland United Kingdom. School of Medicine Medical Sciences & Nutrition University of Aberdeen Foresterhill Aberdeen Scotland United Kingdom. United States (US) Department of Agriculture Agricultural Research Service US Meat Animal Research Center Clay Center Nebraska USA. National Centre for Animal Diseases Canadian Food Inspection Agency Lethbridge Alberta Canada. National Microbiology Laboratory Public Health Agency of Canada Lethbridge Alberta Canada. mEpiLab Infectious Disease Research Centre School of Veterinary Science Massey University Palmerston North New Zealand. Instituto Nacional de Enfermedades Infecciosas Administracion Nacional del Laboratorios et Institutos de Salud "Dr. Carlos G. Malbrán" Ciudad Autónoma de Buenos Aires Buenos Aires Argentina. The Commonwealth Scientific and Industrial Research Organisation Agriculture and Food Werribee Australia. Institute of Complex Systems and Mathematical Biology Scottish Universities Physics Alliance School of Natural and Computing Sciences University of Aberdeen Aberdeen Scotland United Kingdom.

Max-min fairness user scheduling and power allocation in full-duplex OFDMA systems

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arXiv 2018年

作者： Zhang, Xiaozhou Chang, Tsung-Hui Liu, Ya-Feng Shen, Chao Zhu, Gang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Science and Engineering Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In a full-duplex (FD) multi-user network, the system performance is not only limited by the self-interference but also by the co-channel interference due to the simultaneous uplink and downlink transmissions. Joint design of the uplink/downlink transmission direction of users and the power allocation is crucial for achieving high system performance in the FD multi-user network. In this paper, we investigate the joint uplink/downlink transmission direction assignment (TDA), user paring (UP) and power allocation problem for maximizing the system max-min fairness (MMF) rate in a FD multi-user orthogonal frequency division multiple access (OFDMA) system. The problem is formulated with a two-time-scale structure where the TDA and the UP variables are for optimizing a long-term MMF rate while the power allocation is for optimizing an instantaneous MMF rate during each channel coherence interval. We show that the studied joint MMF rate maximization problem is NP-hard in general. To obtain high-quality suboptimal solutions, we propose efficient methods based on simple relaxation and greedy rounding techniques. Simulation results are presented to show that the proposed algorithms are effective and achieve higher MMF rates than the existing heuristic methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Optimization