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arXiv 2018年

作者： Ye, Min Abbe, Emmanuel Department of Electrical Engineering Princeton University PrincetonNJ United States Program in Applied and Computational Mathematics Department of Electrical Engineering Princeton University School of Mathematics Institute for Advanced Study PrincetonNJ08544 United States

This paper develops coding techniques to reduce the running time of distributed learning tasks. It characterizes the fundamental tradeoff to compute gradients (and more generally vector summations) in terms of three parameters: computation load, straggler tolerance and communication cost. It further gives an explicit coding scheme that achieves the optimal tradeoff based on recursive polynomial constructions, coding both across data subsets and vector components. As a result, the proposed scheme allows to minimize the running time for gradient computations. Implementations are made on Amazon EC2 clusters using Python with mpi4py package. Results show that the proposed scheme maintains the same generalization error while reducing the running time by 32% compared to uncoded schemes and 23% compared to prior coded schemes focusing only on stragglers (Tandon et al., ICML 2017). Copyright © 2018, The Authors. All rights reserved.

关键词： Python

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The implementation of K-Means clustering in kovats retention index on gas chromatography

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IOP Conference Series: Materials Science and engineering 2021年第1期1087卷

作者： T R Noviandy A Maulana N R Sasmita R Suhendra Muslem G M Idroes M Paristiowati Z Helwani E Yandri S Rahimah Muhammad Irvanizam R Idroes Department of Informatics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia Computational and Applied Statistics Research Group Department of Statistics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia Department of Chemistry Faculty of Mathematics and Sciences Universitas Negeri Jakarta Jl. Rawamangun Muka Jakarta 13220 Indonesia Department of Chemical Engineering Universitas Riau Pekanbaru 28293 Indonesia Graduate School of Renewable Energy Darma Persada University Jl. Radin Inten 2 Pondok Kelapa East Jakarta 13450 Indonesia Department of Food Industrial Technology Faculty of Agroindustrial Technology Universitas Padjadjaran Jatinangor 54363 Indonesia Faculty of Teacher Training and Education Abulyatama University Lampoh Keudee Aceh Besar 23372 Indonesia Department of Pharmacy Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia

In this study, the retention index data of 146 compounds that are found in coal and petroleum-derived liquid fuels were grouped using the K-means clustering method, and the similarities between each cluster were analyzed. The psycho-chemical properties of each compound in the cluster were identified and compared with other clusters. Each compound's retention index is grouped based on the similarity between the column polarity and heating rate of one compound to another. Based on the results of tests carried out on nine differentk values, it is known that the grouping with the value of k = 3 is the best determined from the obtained silhouette score = 0.568, where this score is higher than the score obtained on the other k values. The results of clustering with k = 3 obtained three clusters, namely cluster C1, cluster C2, and cluster C3. Cluster C1 and cluster C2 consist of chemical compounds that have a relatively low carbon number and molecular mass, but in cluster C2 the molecular mass of the compound is lower than in cluster C1. In contrast, the C3 cluster consists of chemical compounds that have a relatively high carbon number and molecular mass.

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Estimation in the group action channel

arXiv

引用

arXiv 2018年

作者： Abbe, Emmanuel Pereira, João M. Singer, Amit Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Electrical Engineering Department Princeton University PrincetonNJ United States Department of Mathematics Princeton University PrincetonNJ United States

MSC Codes 94A15, 62B10We analyze the problem of estimating a signal from multiple measurements on a group action channel that linearly transforms a signal by a random group action followed by a fixed projection and additive Gaussian noise. This channel is motivated by applications such as multi-reference alignment and cryoelectron microscopy. We focus on the large noise regime prevalent in these applications. We give a lower bound on the mean square error (MSE) of any asymptotically unbiased estimator of the signal's orbit in terms of the signal's moment tensors, which implies that the MSE is bounded away from 0 when N=σ2dis bounded from above, where N is the number of observations, σ is the noise standard deviation, and d is the so-called moment order cutoff. In contrast, the maximum likelihood estimator is shown to be consistent if N=σ2ddiverges. Copyright © 2018, The Authors. All rights reserved.

关键词： Mean square error

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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Publisher Correction: Comprehensive molecular characterization of mitochondrial genomes in human cancers

引用

Nature genetics 2023年第5期55卷 893页

作者： Yuan Yuan Young Seok Ju Youngwook Kim Jun Li Yumeng Wang Christopher J Yoon Yang Yang Inigo Martincorena Chad J Creighton John N Weinstein Yanxun Xu Leng Han Hyung-Lae Kim Hidewaki Nakagawa Keunchil Park Peter J Campbell Han Liang Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon Korea. Department of Health Science and Technology Samsung Advanced Institute for Health Science and Technology Sungkyunkwan University School of Medicine Seoul Korea. Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine Houston TX USA. Division of Biostatistics The University of Texas Health Science Center at Houston School of Public Health Houston TX USA. Department of Medicine and Dan L. Duncan Cancer Center Division of Biostatistics Baylor College of Medicine Houston TX USA. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore MD USA. Department of Biochemistry and Molecular Biology The University of Texas Health Science Center at Houston McGovern Medical School Houston TX USA. Department of Biochemistry Ewha Womans University School of Medicine Seoul Korea. Laboratory for Cancer Genomics RIKEN Center for Integrative Medical Sciences Yokohama Japan. Division of Hematology/Oncology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Korea. kpark@skku.edu. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. pc8@sanger.ac.uk. Cambridge University Hospitals NHS Foundation Trust Cambridge UK. pc8@sanger.ac.uk. Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. hliang1@***. Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine Houston TX USA. hliang1@***. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. hliang1@mdanderson

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Mixed mode oscillations and phase locking in coupled FitzHugh-Nagumo model neurons

arXiv

引用

arXiv 2018年

作者： Davison, Elizabeth N. Aminzare, Zahra Leonard, Naomi Ehrich Dey, Biswadip Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08540 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

We study the dynamics of a low-dimensional system of coupled model neurons as a step towards understanding the vastly complex network of neurons in the brain. We analyze the bifurcation structure of a system of two model neurons with unidirectional coupling as a function of two physiologically relevant parameters: the external current input only to the first neuron and the strength of the coupling from the first to the second neuron. Leveraging a timescale separation, we prove necessary conditions for multiple timescale phenomena observed in the coupled system, including canard solutions and mixed mode oscillations. For a larger network of model neurons, we present a sufficient condition for phase locking when external inputs are heterogeneous. Finally, we generalize our results to directed trees of model neurons with heterogeneous inputs.34A26, 34C15, 34C60, 34D15, 34E17, 37G05, 37G10, 92B20, 92C20 Copyright © 2018, The Authors. All rights reserved.

关键词： Bifurcation (mathematics)

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Rational design of stealthy hyperuniform two-phase media with tunable order

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Physical Review E 2018年第2期97卷 023311-023311页

作者： Robert A. DiStasio, Jr. Ge Zhang Frank H. Stillinger Salvatore Torquato Department of Chemistry and Chemical Biology Cornell University Ithaca New York 14853 USA Department of Chemistry Princeton University Princeton New Jersey 08544 USA Department of Physics Princeton Institute for the Science and Technology of Materials and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Disordered stealthy hyperuniform materials are exotic amorphous states of matter that have attracted recent attention because of their novel structural characteristics (hidden order at large length scales) and physical properties, including desirable photonic and transport properties. It is therefore useful to devise algorithms that enable one to design a wide class of such amorphous configurations at will. In this paper, we present several algorithms enabling the systematic identification and generation of discrete (digitized) stealthy hyperuniform patterns with a tunable degree of order, paving the way towards the rational design of disordered materials endowed with novel thermodynamic and physical properties. To quantify the degree of order or disorder of the stealthy systems, we utilize the discrete version of the τ order metric, which accounts for the underlying spatial correlations that exist across all relevant length scales in a given digitized two-phase (or, equivalently, a two-spin state) system of interest. Our results impinge on a myriad of fields, ranging from physics, materials science and engineering, visual perception, and information theory to modern data science.

关键词： Pattern formation

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The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

arXiv

引用

arXiv 2024年

作者： Kazerooni, Anahita Fathi Khalili, Nastaran Liu, Xinyang Gandhi, Deep Jiang, Zhifan Anwar, Syed Muhammed Albrecht, Jake Adewole, Maruf Anazodo, Udunna Anderson, Hannah Baid, Ujjwal Bergquist, Timothy Borja, Austin J. Calabrese, Evan Chung, Verena Conte, Gian-Marco Dako, Farouk Eddy, James Ezhov, Ivan Familiar, Ariana Farahani, Keyvan Franson, Andrea Gottipati, Anurag Haldar, Shuvanjan Iglesias, Juan Eugenio Janas, Anastasia Johansen, Elaine Jones, Blaise V. Khalili, Neda Kofler, Florian LaBella, Dominic Lai, Hollie Anne Van Leemput, Koen Li, Hongwei Bran Maleki, Nazanin McAllister, Aaron S. Meier, Zeke Menze, Bjoern Moawad, Ahmed W. Nandolia, Khanak K. Pavaine, Julija Piraud, Marie Poussaint, Tina Prabhu, Sanjay P. Reitman, Zachary Rudie, Jeffrey D. Sanchez-Montano, Mariana Shaikh, Ibraheem Salman Sheth, Nakul Tu, Wenxin Wang, Chunhao Ware, Jeffrey B. Wiestler, Benedikt Zapaishchykova, Anna Bornhorst, Miriam Deutsch, Michelle Fouladi, Maryam Lazow, Margot Mikael, Leonie Hummel, Trent Kann, Benjamin de Blank, Peter Hoffman, Lindsey Aboian, Mariam Nabavizadeh, Ali Packer, Roger Bakas, Spyridon Resnick, Adam Rood, Brian Vossough, Arastoo Linguraru, Marius George Children’s Hospital of Philadelphia PhiladelphiaPA United States Department of Neurosurgery University of Pennsylvania PhiladelphiaPA United States University of Pennsylvania PhiladelphiaPA United States Sheikh Zayed Institute for Pediatric Surgical Innovation Children’s National Hospital WashingtonDC United States Sage Bionetworks United States Lab Crestview Radiology Lagos Nigeria McGill University MontrealQC Canada Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Division of Computational Pathology Department of Pathology and Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Department of Neurosurgery The University of Southern California CA United States Department of Radiology Duke University Medical Center DurhamNC United States Mayo Clinic MN United States Center for Global Health Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Informatics Technical University Munich Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD United States C. S. Mott Children’s Hospital University of Michigan MI United States Biomedical Engineering Rutgers University New BrunswickNJ United States Athinoula A Martinos Center for Biomedical Imaging Massachusetts General Hospital BostonMA United States Yale University New HavenCT United States PrecisionFDA U.S. Food and Drug Administration Silver SpringMD United States Cincinnati Children’s Hospital Medical Center OH United States Helmholtz AI Helmholtz Munich Germany Department of Radiation Oncology Duke University Medical Center DurhamNC United States Department of Radiology Children’s Health Orange County CA United States Department of Applied Mathematics and Computer Science Technical University of De

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs challenge, focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors. © 2024, CC BY.

关键词： Deep learning

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Recovering Signals from their FROG Trace

Recovering Signals from their FROG Trace

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Tamir Bendory Dan Edidin Yonina C. Eldar The Program in Applied and Computational Mathematics Princeton University Princeton NJ USA Department of Mathematics University of Missouri Columbia Missouri USA The Andrew and Erna Viterbi Faculty of Electrical Engineering Technion - Israel Institute of Technology Haifa Israel

ISBN: (纸本)9781538646595

The problem of recovering a signal from its power spectrum is called phase retrieval. This problem appears in a variety of scientific applications, such as ultra-short laser pulse characterization and diffraction imaging. However, the problem for one-dimensional signals is ill-posed as there is no one-to-one mapping between a one-dimensional signal and its power spectrum. In the field of ultra-short laser pulse characterization, it is common to overcome this ill-posedness by using a technique called Frequency-Resolved Optical Gating (FROG). In FROG, the measured data, referred to as FROG trace, is the Fourier magnitude of the product of the underlying signal with several translated versions of itself. Therefore, in order to recover a signal from its FROG trace, one needs to invert a system of phaseless quartic equations. In this paper, we explore the symmetries and uniqueness of the FROG mapping. Our main result states that a signal bandlimited to B is determined uniquely, up to symmetries, by only 3B FROG measurements.

关键词： phase retrieval phaseless quartic system of equations ultra-short laser pulse characterization FROG signals Ultrashort laser pulses power spectra frogs Amphibians RECOVERING Trace One dimensional quartic equations

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Universal research index: An inclusive metric to quantify scientific research output

引用

Journal of Academic Librarianship 2023年第3期49卷

作者： Keshavarz-Fathi, Mahsa Yazdanpanah, Niloufar Kolahchi, Sajad Ziaei, Heliya Darmstadt, Gary L. Dorigo, Tommaso Dochy, Filip Levin, Lisa Thongboonkerd, Visith Ogino, Shuji Chen, Wei-Hsin Perc, Matjaz Tremblay, Mark S. Olusanya, Bolajoko O. Rao, Idupulapati M. Hatziargyriou, Nikos Moradi-Lakeh, Maziar Bella, Federico Rosivall, Laszlo Gandomi, Amir H. Sorooshian, Armin Gupta, Manoj Gal, Ciprian Lozano, Andres M. Weaver, Connie Tanzer, Michael Poggi, Alessandro Sepanlou, Sadaf G. Weiskirchen, Ralf Jambrak, Anet Režek Torres, Pedro J. Capanoglu, Esra Barba, Francisco J. Ernest, Chua Kian Jon Sigman, Mariano Pluchino, Stefano Gharehpetian, Gevork B. Fereshtehnejad, Seyed-Mohammad Yang, Muh-Hwa Thomas, Sabu Cai, Wenju Comini, Elisabetta Scolding, Neil J. Myles, Paul S. Nieto, Juan J. Perry, George Sedikides, Constantine Rezaei, Nima School of Medicine Tehran University of Medical Sciences Tehran Iran Universal Scientific Education and Research Network (USERN) Iran Department of Pediatrics Stanford University School of Medicine Stanford CA United States Istituto Nazionale di Fisica Nucleare (INFN) Via Francesco Marzolo Sezione di Padova Italy High Impact Learning Academy Learning and Development Department Brussels Belgium Center for Marine Biodiversity and Conservation Integrative Oceanography Division Scripps Institution of Oceanography University of California San Diego San Diego CA United States Medical Proteomics Unit Office for Research and Development Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA United States Program in MPE Molecular Pathological Epidemiology Department of Pathology Brigham and Women's Hospital and Harvard Medical School Boston MA United States Broad Institute of MIT and Harvard Cambridge MA United States Department of Aeronautics and Astronautics National Cheng Kung University Tainan Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung 407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung 411 Taiwan Faculty of Natural Sciences and Mathematics University of Maribor Maribor Slovenia Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Complexity Science Hub Vienna Vienna Austria Alma Mater Europaea Maribor Slovenia Children's Hospital of Eastern Ontario Research Institute Department of Pediatrics University of Ottawa Ottawa ON Canada Centre for Healthy Start Initiative Ikoyi Lagos Nigeria Alliance of Bioversity International International Center for Tropical Agriculture Cali Colombia International Centre of Insect Physiology and Ecology (ICIPE) Nairobi Kenya School of Electrical and Computer Engineering Natio

Scientometrics and bibliometrics, the subfields of library and information science, deal with the quantity and quality of research outputs. Currently, various scientometric indices are being used to quantify and compare research outputs. The most widely known is the h-index. However, this index and its derivatives suffer from dependence on the mere count of a scholar's highly cited publications. To remedy this deficiency, we developed a novel index, the Universal Research Index (UR-Index) (https://***/UR-Index/) by which every single publication has its own impact on the total score. We developed this index by surveying international top 1 % cited scientists in various disciplines and included additional component variables such as publication type, leading role of a scholar, co-author count, and source metrics to this scientometric index. We acknowledge that unconscious biases built into the component variables included in the UR-Index might put research from specific groups at a disadvantage, thus continued efforts to improve equitable scholarly impact in science and academia are encouraged. © 2023 Elsevier Inc.

关键词： Citations CiteScore h-index Impact factor Leading author Research impact Scholarly impact Scholarly output Scientometrics UR-Index USERN

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