检索结果-内蒙古大学图书馆

arXiv 2017年

作者： Yang, Liu Zamani, Hamed Zhang, Yongfeng Guo, Jiafeng Bruce Croft, W. Center for Intelligent Information Retrieval University of Massachusetts Amherst AmherstMA United States CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China

The recent boom of AI has seen the emergence of many human-computer conversation systems such as Google Assistant, Microsoft Cortana, Amazon Echo and Apple Siri. We introduce and formalize the task of predicting questions in conversations, where the goal is to predict the new question that the user will ask, given the past conversational context. This task can be modeled as a "sequence matching" problem, where two sequences are given and the aim is to learn a model that maps any pair of sequences to a matching probability. Neural matching models, which adopt deep neural networks to learn sequence representations and matching scores, have attracted immense research interests of information retrieval and natural language processing communities. In this paper, we first study neural matching models for the question retrieval task that has been widely explored in the literature, whereas the effectiveness of neural models for this task is relatively unstudied. We further evaluate the neural matching models in the next question prediction task in conversations. We have used the publicly available Quora data and Ubuntu chat logs in our experiments. Our evaluations investigate the potential of neural matching models with representation learning for question retrieval and next question prediction in conversations. Experimental results show that neural matching models perform well for both tasks. Copyright © 2017, The Authors. All rights reserved.

关键词： Forecasting

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Launching the VASCO Citizen science Project

arXiv

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arXiv 2020年

作者： Villarroel, Beatriz Pelckmans, Kristiaan Solano, Enrique Laaksoharju, Mikael Souza, Abel Dom, Onyeuwaoma Nnaemeka Laggoune, Khaoula Mimouni, Jamal Guergouri, Hichem Mattsson, Lars García, Aurora Lago Soodla, Johan Castillo, Diego Shultz, Matthew E. Aworka, Rubby Comerón, Sébastien Geier, Stefan Marcy, Geoffrey W. Gupta, Alok C. Bergstedt, Josefine Bär, Rudolf E. Buelens, Bart Enriquez, Emilio Mellon, Christopher K. Prieto, Almudena Wamalwa, Dismas Simiyu de Souza, Rafael S. Ward, Martin J. Nordita KTH Royal Institute of Technology Stockholm University Roslagstullsbacken 23 StockholmSE-106 91 Sweden Instituto de Astrofísica de Canarias Avda Vía Láctea s/n Tenerife La LagunaE-38205 Spain Department of Information Technology Uppsala University Box 337 UppsalaSE-751 05 Sweden P.O. Box 78 Villanueva de la CañadaE-28691 Spain Autonomous Distributed Systems Lab Department of Computing Science Umeå Universitet Umeå901 87 Sweden Center for Basic Space Science National Space Research and Development Agency P.O. Box 2022 Nsukka Enugu410002 Nigeria Sirius Astronomy Association Sirius Astronomy Association BP 18 Cité du 20 Aout Constantine25000 Algeria Department of Physics University of Constantine 1 LPMPS CERIST Constantine25000 Algeria Science of Matter Division Research Unit in Scientific Mediation CERIST Constantine25016 Algeria IES Tartessos Barriada Hiconsa s/n Camas Sevilla41900 Spain Department of Physics & Astronomy University of Delaware 217 Sharp Lab NewarkDE19716 United States Ghana Space Science and Technology Institute Atomic-Haatso Road Kwabenya Box LG 80 Accra233 Ghana University of Ghana Summerhill Estates Ltd Rd Santeo P.O. Box LG 25 Legon Accra Ghana Departamento de Astrofísica Universidad de La Laguna Tenerife La LagunaE-38206 Spain Cuesta de San José s/n La Palma Breña Baja38712 Spain Space Laser Awareness 3883 Petaluma Hill Rd Santa RosaCA95404 United States Manora Peak Nainital263 001 India Freelance Uppsala752 17 Sweden Institute for Particle Physics and Astrophysics ETH Zürich Wolfgang-Pauli-Strasse 27 ZürichCH-8093 Switzerland Mol2400 Belgium Department of Astrophysics IMAPP Radboud University Nijmegen Nijmegen6525 AJ Netherlands Galileo project affiliate Meru Physics Department University of Science and Technology Meru P.O. Box Kenya972-60200 Kenya Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences 80

The Vanishing & Appearing Sources during a Century of Observations (VASCO) project investigates astronomical surveys spanning a time interval of 70 years, searching for unusual and exotic transients. We present herein the VASCO Citizen science Project, which can identify unusual candidates driven by three different approaches: hypothesis, exploratory, and machine learning, which is particularly useful for SETI searches. To address the big data challenge, VASCO combines three methods: the Virtual Observatory, user-aided machine learning, and visual inspection through citizen science. Here we demonstrate the citizen science project and its improved candidate selection process, and we give a progress report. We also present the VASCO citizen science network led by amateur astronomy associations mainly located in Algeria, Cameroon, and Nigeria. At the moment of writing, the citizen science project has carefully examined 15,593 candidate image pairs in the data (ca. 10% of the candidates), and has so far identified 798 objects classified as "vanished". The most interesting candidates will be followed up with optical and infrared imaging, together with the observations by the most potent radio telescopes. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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Constraints on black-hole charges with the 2017 EHT observations of M87*

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Physical Review D 2021年第10期103卷 104047-104047页

作者： Prashant Kocherlakota Luciano Rezzolla Heino Falcke Christian M. Fromm Michael Kramer Yosuke Mizuno Antonios Nathanail Héctor Olivares Ziri Younsi Kazunori Akiyama Antxon Alberdi Walter Alef Juan Carlos Algaba Richard Anantua Keiichi Asada Rebecca Azulay Anne-Kathrin Baczko David Ball Mislav Baloković John Barrett Bradford A. Benson Dan Bintley Lindy Blackburn Raymond Blundell Wilfred Boland Katherine L. Bouman Geoffrey C. Bower Hope Boyce Michael Bremer Christiaan D. Brinkerink Roger Brissenden Silke Britzen Avery E. Broderick Dominique Broguiere Thomas Bronzwaer Do-Young Byun John E. Carlstrom Andrew Chael Chi-kwan Chan Shami Chatterjee Koushik Chatterjee Ming-Tang Chen Yongjun Chen (陈永军) Paul M. Chesler Ilje Cho Pierre Christian John E. Conway James M. Cordes Thomas M. Crawford Geoffrey B. Crew Alejandro Cruz-Osorio Yuzhu Cui Jordy Davelaar Mariafelicia De Laurentis Roger Deane Jessica Dempsey Gregory Desvignes Sheperd S. Doeleman Ralph P. Eatough Joseph Farah Vincent L. Fish Ed Fomalont Raquel Fraga-Encinas Per Friberg H. Alyson Ford Antonio Fuentes Peter Galison Charles F. Gammie Roberto García Olivier Gentaz Boris Georgiev Ciriaco Goddi Roman Gold José L. Gómez Arturo I. Gómez-Ruiz Minfeng Gu (顾敏峰) Mark Gurwell Kazuhiro Hada Daryl Haggard Michael H. Hecht Ronald Hesper Luis C. Ho (何子山) Paul Ho Mareki Honma Chih-Wei L. Huang Lei Huang (黄磊) David H. Hughes Shiro Ikeda Makoto Inoue Sara Issaoun David J. James Buell T. Jannuzi Michael Janssen Britton Jeter Wu Jiang (江悟) Alejandra Jimenez-Rosales Michael D. Johnson Svetlana Jorstad Taehyun Jung Mansour Karami Ramesh Karuppusamy Tomohisa Kawashima Garrett K. Keating Mark Kettenis Dong-Jin Kim Jae-Young Kim Jongsoo Kim Junhan Kim Motoki Kino Jun Yi Koay Yutaro Kofuji Patrick M. Koch Shoko Koyama Carsten Kramer Thomas P. Krichbaum Cheng-Yu Kuo Tod R. Lauer Sang-Sung Lee Aviad Levis Yan-Rong Li (李彦荣) Zhiyuan Li (李志远) Michael Lindqvist Rocco Lico Greg Lindahl Jun Liu (刘俊) Kuo Liu Elisabetta Liuzzo Wen-Ping Lo Andrei P. Lobanov Laurent Loinard Colin Lonsdale Ru-Sen Lu Institut für Theoretische Physik Goethe-Universität Max-von-Laue-Strasse 1 60438 Frankfurt Germany Frankfurt Institute for Advanced Studies Ruth-Moufang-Strasse 1 60438 Frankfurt Germany School of Mathematics Trinity College Dublin 2 Ireland Department of Astrophysics Institute for Mathematics Astrophysics and Particle Physics (IMAPP) Radboud University P.O. Box 9010 6500 GL Nijmegen Netherlands Black Hole Initiative at Harvard University 20 Garden Street Cambridge Massachusetts 02138 USA Center for Astrophysics—Harvard & Smithsonian 60 Garden Street Cambridge Massachusetts 02138 USA Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 D-53121 Bonn Germany Tsung-Dao Lee Institute and School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China Institut für Theoretische Physik Goethe-Universität Frankfurt Max-von-Laue-Straße 1 D-60438 Frankfurt am Main Germany Department of Physics National and Kapodistrian University of Athens Panepistimiopolis GR 15783 Zografos Greece Mullard Space Science Laboratory University College London Holmbury St. Mary Dorking Surrey RH5 6NT United Kingdom Massachusetts Institute of Technology Haystack Observatory 99 Millstone Road Westford Massachusetts 01886 USA National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo 181-8588 Japan Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n E-18008 Granada Spain Department of Physics Faculty of Science University of Malaya 50603 Kuala Lumpur Malaysia Center for Computational Astrophysics Flatiron Institute 162 Fifth Avenue New York New York 10010 USA Institute of Astronomy and Astrophysics Academia Sinica 11F of Astronomy-Mathematics Building AS/NTU No. 1 Sec. 4 Roosevelt Rd Taipei 10617 Taiwan R.O.C. Departament d’Astronomia i Astrofísica Universitat de València C. Dr. Moliner 50 E-46100 Burjassot València Spain Observatori Astronòmic Universitat de València C. Catedrático José Beltrán 2 E-46980 Paterna

Our understanding of strong gravity near supermassive compact objects has recently improved thanks to the measurements made by the Event Horizon Telescope (EHT). We use here the M87* shadow size to infer constraints on the physical charges of a large variety of nonrotating or rotating black holes. For example, we show that the quality of the measurements is already sufficient to rule out that M87* is a highly charged dilaton black hole. Similarly, when considering black holes with two physical and independent charges, we are able to exclude considerable regions of the space of parameters for the doubly-charged dilaton and the Sen black holes.

关键词： Alternative gravity theories Experimental studies of gravity General relativity Radio, microwave, & sub-mm astronomy Accretion disk & black-hole plasma Classical black holes Galaxies Electromagnetic radiation astronomy

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The Smart Street Lighting System Based on NB-IoT

The Smart Street Lighting System Based on NB-IoT

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Chinese Automation Congress

作者： Shichao Chen Shuangshuang Han Gang Xiong Fei-Yue Wang Jia Xu Kun Wang Macau University of Science and Technology Chinese Academy of Sciences Macau China The Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing University of Chemical Technology Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries The State Key laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Qingdao China Beijing University of Chemical Technology Beijing China

With the development of communication technology, in order to meet the smart city's demand for intelligent infrastructure, the smart street lighting system based on NB-IoT is an effective method to realize the goal. This paper elaborates on the smart street lighting system's architecture, including the perception and control layer, the transport layer, the platform layer and the application layer. In addition, the actual system is built to verify. This system uses STM32 to build the perception and controller, and relies on China Telecom's NB-IoT communication network for the data transmission, finally using the IoT management platform-Huawei OceanConnect- to implement the connection management, the device management, the data calculation and the remote control functions. This system verifies the feasibility of the smart street lighting system based on NB-IoT technology, which provides the reference for the promotion and application. It is expected to provide intelligent, diversified, efficient and economical services for the smart cities.

关键词： Smart street lighting system NB-IoT IoT Smart city

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Cells grouping scheme against pilot contamination in large scale antennas system

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Journal of Systems Engineering and Electronics 2016年第3期27卷 531-540页

作者： Zhichao Zhou Yang Xiao Dong Wang Institute of Information Science Beijing Jiaotong UniversityBeijing 100044China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing 100044China

The influence of cells groupings factor to the performance of the cells groupings time-shift pilot scheme is researched for the multiple cells large scale antennas systems（LSAS）. The former researches have confirmed that the cells groupings time-shift pilots scheme is effective to reduce inter-cell interference, especially pilot contamination, which results from the pilot reuse in adjacent cells. However, they have not specified reasonable cells groupings factor, which plays a critical role in the general performance of the LSAS. Therefore, this problem is researched in details. The time for reverse-link data transmission will be compressed, when the groupings factor surpasses a certain range. Thus it is not always beneficial to increase the cells groupings factor without limitation. Furthermore,a reasonable cells groupings factor is deduced from the perspective of optimization to enhance the system performance. Simulations verify the proposed cell grouping factor.

关键词： large scale antenna system multiple cells inter-cell interference time-shift pilots scheme cells grouping factor system performance

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Multi-bit leveled homomorphic encryption via ***-based 12th

Multi-bit leveled homomorphic encryption via ***-based

引用

12th International Conference on Information Security and Cryptology, INSCRYPT 2016

作者： Li, Zengpeng Ma, Chunguang Morais, Eduardo Du, Gang College of Computer Science and Technology Harbin Engineering University Harbin15001 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Institute of Computing University of Campinas Campinas13083-050 Brazil

ISBN: (纸本)9783319547046

Fully Homomorphic Encryption (FHE) is a cryptographic primitive that allows computing over encrypted data without decrypting the corresponding ciphertexts. In general, existing FHE schemes can be achieved using standard Learning with Errors (LWE) assumption and most of the schemes are single-bit encryption. Hence, the construction of multi-bit FHE with high efficiency remains an open problem in cryptography. In this paper, we propose multi-bit versions of Public key Encryption (PKE) via the dual LWE-based firstly proposed by Gentry, Peikert, and Vaikuntanathan at STOC 2008. We initially develop an universal construction derived from a general structure of the underlying combined public matrix for constructing the multi-bit version which increases the size of ciphertexts linearly. Then, utilizing multi-bit PKE scheme as building block, we propose a new multi-bit FHE scheme under the assumption of decisional LWE is hard and prove the scheme is IND-CPA-secure. © Springer International Publishing AG 2017.

关键词： Public key cryptography

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Secure detection of image manipulation by means of random feature selection

arXiv

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arXiv 2018年

作者： Chen, Zhipeng Tondi, Benedetta Li, Xiaolong Ni, Rongrong Zhao, Yao Barni, Mauro Institute of Information Science Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong University Beijing100044 China Department of Computer Science Tangshan Normal University Tangshan063000 China Department of Information Engineering and Mathematics University of Siena Via Roma 56 Siena53100 Italy

We address the problem of data-driven image manipulation detection in the presence of an attacker with limited knowledge about the detector. Specifically, we assume that the attacker knows the architecture of the detector, the training data and the class of features V the detector can rely on. In order to get an advantage in his race of arms with the attacker, the analyst designs the detector by relying on a subset of features chosen at random in V. Given its ignorance about the exact feature set, the adversary attacks a version of the detector based on the entire feature set. In this way, the effectiveness of the attack diminishes since there is no guarantee that attacking a detector working in the full feature space will result in a successful attack against the reduced-feature detector. We theoretically prove that, thanks to random feature selection, the security of the detector increases significantly at the expense of a negligible loss of performance in the absence of attacks. We also provide an experimental validation of the proposed procedure by focusing on the detection of two specific kinds of image manipulations, namely adaptive histogram equalization and median filtering. The experiments confirm the gain in security at the expense of a negligible loss of performance in the absence of attacks. Copyright © 2018, The Authors. All rights reserved.

关键词： Feature extraction

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Search for long-lived particles decaying in the CMS endcap muon detectors in proton-proton collisions at √s = 13 TeV

arXiv

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arXiv 2021年

作者： Sirunyan, A.M. Tumasyan, A. Adam, W. Bergauer, T. Dragicevic, M. Erö, J. Escalante Del Valle, A. Frühwirth, R. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Madlener, T. Mikulec, I. Pitters, F.M. Rad, N. Schieck, J. Schöfbeck, R. Spanring, M. Templ, S. Waltenberger, W. Wulz, C.-E. Zarucki, M. Chekhovsky, V. Litomin, A. Makarenko, V. Suarez Gonzalez, J. Darwish, M.R. de Wolf, E.A. Di Croce, D. Janssen, X. Kello, T. Lelek, A. Pieters, M. Rejeb Sfar, H. van Haevermaet, H. van Mechelen, P. van Putte, S. van Remortel, N. Blekman, F. Bols, E.S. Chhibra, S.S. D’Hondt, J. de Clercq, J. Lontkovskyi, D. Lowette, S. Marchesini, I. Moortgat, S. Morton, A. Python, Q. Tavernier, S. van Doninck, W. van Mulders, P. Beghin, D. Bilin, B. Clerbaux, B. de Lentdecker, G. Dorney, B. Favart, L. Grebenyuk, A. Kalsi, A.K. Makarenko, I. Moureaux, L. Pétré, L. Popov, A. Postiau, N. Starling, E. Thomas, L. Vander Velde, C. Vanlaer, P. Vannerom, D. Wezenbeek, L. Cornelis, T. Dobur, D. Gruchala, M. Khvastunov, I. Niedziela, M. Roskas, C. Skovpen, K. Tytgat, M. Verbeke, W. Vermassen, B. Vit, M. Bruno, G. Bury, F. Caputo, C. David, P. Delaere, C. Delcourt, M. Donertas, I.S. Giammanco, A. Lemaitre, V. Mondal, K. Prisciandaro, J. Taliercio, A. Teklishyn, M. Vischia, P. Wertz, S. Wuyckens, S. Alves, G.A. Hensel, C. Moraes, A. Aldá Júnior, W.L. Belchior Batista Das Chagas, E. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Coelho, E. da Costa, E.M. da Silveira, G.G. de Jesus Damiao, D. Fonseca De Souza, S. Martins, J. Matos Figueiredo, D. Medina Jaime, M. Mora Herrera, C. Mundim, L. Nogima, H. Rebello Teles, P. Sanchez Rosas, L.J. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Torres Da Silva De Araujo, F. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Lemos, D.S. Mercadante, P.G. Novaes, S.F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Atanasov, I. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Bonchev, M. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Wien Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista São Paulo Brazil Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics CHEP-FU Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta University of Technology Lappeenranta Finland IRFU CEA Université Paris-Saclay

A search for long-lived particles (LLPs) produced in decays of standard model (SM) Higgs bosons is presented. The data sample consists of 137 fb−1 of proton-proton collisions at √s = 13 TeV, recorded at the LHC in 2016–2018. A novel technique is employed to reconstruct decays of LLPs in the endcap muon detectors. The search is sensitive to a broad range of LLP decay modes and to masses as low as a few GeV. No excess of events above the SM background is observed. The most stringent limits to date on the branching fraction of the Higgs boson to LLPs subsequently decaying to quarks and τ+τ− are found for proper decay lengths greater than 6, 20, and 40 m, for LLP masses of 7, 15, and 40 GeV, respectively. © 2021, CC BY.

关键词： Bosons

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The NANOGrav 15 yr data Set: Looking for Signs of Discreteness in the Gravitational-wave Background

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The Astrophysical Journal 2024年第1期978卷 31-31页

作者： Gabriella Agazie Akash Anumarlapudi Anne M. Archibald Zaven Arzoumanian Jeremy George Baier Paul T. Baker Bence Bécsy Laura Blecha Adam Brazier Paul R. Brook Lucas Brown Sarah Burke-Spolaor J. Andrew Casey-Clyde Maria Charisi Shami Chatterjee Tyler Cohen James M. Cordes Neil J. Cornish Fronefield Crawford H. Thankful Cromartie Kathryn Crowter Megan E. DeCesar Paul B. Demorest Heling Deng Timothy Dolch Elizabeth C. Ferrara William Fiore Emmanuel Fonseca Gabriel E. Freedman Nate Garver-Daniels Peter A. Gentile Joseph Glaser Deborah C. Good Kayhan Gültekin Jeffrey S. Hazboun Ross J. Jennings Aaron D. Johnson Megan L. Jones Andrew R. Kaiser David L. Kaplan Luke Zoltan Kelley Matthew Kerr Joey S. key Nima Laal Michael T. Lam William G. Lamb Bjorn Larsen T. Joseph W. Lazio Natalia Lewandowska Tingting Liu Duncan R. Lorimer Jing Luo Ryan S. Lynch Chung-Pei Ma Dustin R. Madison Alexander McEwen James W. McKee Maura A. McLaughlin Natasha McMann Bradley W. Meyers Patrick M. Meyers Chiara M. F. Mingarelli Andrea Mitridate Priyamvada Natarajan Cherry Ng David J. Nice Stella Koch Ocker Ken D. Olum Timothy T. Pennucci Benetge B. P. Perera Nihan S. Pol Henri A. Radovan Scott M. Ransom Paul S. Ray Joseph D. Romano Jessie C. Runnoe Shashwat C. Sardesai Ann Schmiedekamp Carl Schmiedekamp Kai Schmitz Brent Shapiro-Albert Xavier Siemens Joseph Simon Magdalena S. Siwek Sophia V. Sosa Fiscella Ingrid H. Stairs Daniel R. Stinebring Kevin Stovall Abhimanyu Susobhanan Joseph K. Swiggum Stephen R. Taylor Jacob E. Turner Caner Unal Michele Vallisneri Sarah J. Vigeland Haley M. Wahl London Willson Caitlin A. Witt David Wright Olivia Young Center for Gravitation Cosmology and Astrophysics Department of Physics University of Wisconsin-milwaukee P.O. Box 413 Milwaukee WI 53201 USA Newcastle University NE1 7RU UK X-Ray Astrophysics Laboratory NASA Goddard Space Flight Center Code 662 Greenbelt MD 20771 USA Department of Physics Oregon State University Corvallis OR 97331 USA Department of Physics and Astronomy Widener University One University Place Chester PA 19013 USA Physics Department University of Florida Gainesville FL 32611 USA Cornell Center for Astrophysics and Planetary Science and Department of Astronomy Cornell University Ithaca NY 14853 USA Cornell Center for Advanced Computing Cornell University Ithaca NY 14853 USA Institute for Gravitational Wave Astronomy and School of Physics and Astronomy University of Birmingham Edgbaston Birmingham B15 2TT UK Institute of Cosmology Department of Physics and Astronomy Tufts University Medford MA 02155 USA Department of Physics and Astronomy West Virginia University P.O. Box 6315 Morgantown WV 26506 USA Center for Gravitational Waves and Cosmology West Virginia University Chestnut Ridge Research Building Morgantown WV 26505 USA Department of Physics University of Connecticut 196 Auditorium Road U-3046 Storrs CT 06269-3046 USA andrew.casey-clyde@uconn.edu Department of Physics and Astronomy Vanderbilt University 2301 Vanderbilt Place Nashville TN 37235 USA Department of Physics New Mexico Institute of Mining and Technology 801 Leroy Place Socorro NM 87801 USA Department of Physics Montana State University Bozeman MT 59717 USA Department of Physics and Astronomy Franklin & Marshall College P.O. Box 3003 Lancaster PA 17604 USA National Research Council Research Associate National Academy of Sciences Washington DC 20001 USA resident at Naval Research Laboratory Washington DC 20375 USA Department of Physics and Astronomy University of British Columbia 6224 Agricultural Road Vancouver BC V6T 1Z1 Canada George Mason Un

The cosmic merger history of supermassive black hole binaries (SMBHBs) is expected to produce a low-frequency gravitational wave background (GWB). Here we investigate how signs of the discrete nature of this GWB can manifest in pulsar timing arrays through excursions from, and breaks in, the expected $f_{\mathrm{GW}}^{-2/3}$ power-law of the GWB strain spectrum. To do this, we create a semi-analytic SMBHB population model, fit to NANOGrav's 15 yr GWB amplitude, and with 1,000 realizations we study the populations' characteristic strain and residual spectra. Comparing our models to the NANOGrav 15 yr spectrum, we find two interesting excursions from the power-law. The first, at $2 \; \mathrm{nHz}$, is below our GWB realizations with $p$-value significance $p = 0.05$ to $0.06$ ($\approx 1.8 \sigma - 1.9 \sigma$). The second, at $16 \; \mathrm{nHz}$, is above our GWB realizations with $p = 0.04$ to $0.15$ ($\approx 1.4 \sigma - 2.1 \sigma$). We explore the properties of a loud SMBHB which could cause such an excursion. Our simulations also show that the expected number of SMBHBs decreases by three orders of magnitude, from $\sim 10^6$ to $\sim 10^3$, between $2\; \mathrm{nHz}$ and $20 \; \mathrm{nHz}$. This causes a break in the strain spectrum as the stochasticity of the background breaks down at $26^{+28}_{-19} \; \mathrm{nHz}$, consistent with predictions pre-dating GWB measurements. The diminished GWB signal from SMBHBs at frequencies above the $26~\mathrm{nHz}$ break opens a window for PTAs to detect continuous GWs from individual SMBHBs or GWs from the early universe.

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Sparse Word Embeddings Using 1 Regularized Online Learning

Sparse Word Embeddings Using 1 Regularized Online Learning

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25th International Joint Conference on Artificial Intelligence, IJCAI 2016

作者： Sun, Fei Guo, Jiafeng Lan, Yanyan Xu, Jun Cheng, Xueqi CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China

Recently, Word2Vec tool has attracted a lot of interest for its promising performances in a variety of natural language processing (NLP) tasks. However, a critical issue is that the dense word representations learned in Word2Vec are lacking of interpretability. It is natural to ask if one could improve their interpretability while keeping their performances. Inspired by the success of sparse models in enhancing interpretability, we propose to introduce sparse constraint into Word2Vec. Specifically, we take the Continuous Bag of Words (CBOW) model as an example in our study and add the l regularizer into its learning objective. One challenge of optimization lies in that stochastic gradient descent (SGD) cannot directly produce sparse solutions with 1 regularizer in online training. To solve this problem, we employ the Regularized Dual Averaging (RDA) method, an online optimization algorithm for regularized stochastic learning. In this way, the learning process is very efficient and our model can scale up to very large corpus to derive sparse word representations. The proposed model is evaluated on both expressive power and interpretability. The results show that, compared with the original CBOW model, the proposed model can obtain state-of-the-art results with better interpretability using less than 10% non-zero elements. © 2016 International Joint Conferences on Artificial Intelligence. All rights reserved.

关键词： Optimization

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