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Mixture Models with Grouping Structure: Retail Analytics Applications Haidar Almohri Wayne State University
Wayne State University Wayne State University Dissertations 1-1-2018 Mixture Models With Grouping Structure: Retail Analytics Applications Haidar Almohri Wayne State University, Follow this and additional works at: https://digitalcommons.wayne.edu/oa_dissertations Part of the Business Administration, Management, and Operations Commons, Engineering Commons, and the Statistics and Probability Commons Recommended Citation Almohri, Haidar, "Mixture Models With Grouping Structure: Retail Analytics Applications" (2018). Wayne State University Dissertations. 1911. https://digitalcommons.wayne.edu/oa_dissertations/1911 This Open Access Dissertation is brought to you for free and open access by DigitalCommons@WayneState. It has been accepted for inclusion in Wayne State University Dissertations by an authorized administrator of DigitalCommons@WayneState. MIXTURE MODELS WITH GROUPING STRUCTURE: RETAIL ANALYTICS APLICATIONS by HAIDAR ALMOHRI DISSERTATION Submitted to the Graduate School of Wayne State University, Detroit, Michigan in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY 2018 MAJOR: INDUSTRIAL ENGINEERING Approved By: Advisor Date © COPYRIGHT BY HAIDAR ALMOHRI 2018 All Rights Reserved DEDICATION To my lovely daughter Nour. ii ACKNOWLEDGMENTS I would like to thank my advisor Dr. Ratna Babu Chinnam for introducing me to this fascinating research topic and for his guidance, technical advise, and support throughout this research. I am also grateful to my committee members, Dr. Alper Murat, Dr. Evrim Dalkiran for their time and interest in this thesis and for providing helpful comments for my research. Special thanks go to Dr. Arash Ali Amini for providing valuable suggestions to improve this work. I also thank my family and friends for their continuous support. iii TABLE OF CONTENTS DEDICATION . -
EDTAS | Human Biotechnologies Speaker Biographies
SPEAKERS dst.defence.gov.au/edtas #EDTAS 1 2 SPEAKERS DR ALEX ZELINSKY he was awarded the Pearcey Medal, the CHIEF DEFENCE ICT industry’s premier prize for lifetime SCIENTIST achievement. In 2003, 2004 and 2005, the World Economic Forum selected Dr Dr Alex Zelinsky is Zelinsky as a Technology Pioneer. He is Australia’s Chief Defence a Fellow of the Institute of Electrical and Scientist. His scientific Electronics Engineers, the Australian career includes working as a computer Academy of Technology and Engineering, scientist, a systems engineer and a the Institute of Engineers Australia and the roboticist. His career spans innovation, Australian Institute of Company Directors. science and technology, research and development, commercial start-ups and education. As Chief Defence Scientist PROF PETER RATHJEN since March 2012, he leads the Defence Science and Technology program VICE CHANCELLOR, UNIVERSITY OF within the Department of Defence. ADELAIDE Prior to joining Defence, Dr Zelinsky Professor Peter was Group Executive for Information Rathjen commenced as the University Sciences at the CSIRO. Dr Zelinsky was of Adelaide’s 22nd Vice-Chancellor Chief Executive Officer and co-founder and President on 8 January 2018. of Seeing Machines, a high-technology company developing computer vision He is an Australian scientist and systems. The company is listed on the medical researcher internationally London Stock Exchange and was a start-up recognised in stem cell science. from the Australian National University Professor Rathjen is an alumnus of the in Canberra, Australia, where Dr Zelinsky University of Adelaide, as are all of the was Professor of Systems Engineering. members of his immediate family Dr Zelinsky has received numerous awards Professor Rathjen was appointed Dean of and recognition of his work. -
Mini-Batch Learning of Exponential Family Finite Mixture Models Hien D Nguyen, Florence Forbes, Geoffrey Mclachlan
Mini-batch learning of exponential family finite mixture models Hien D Nguyen, Florence Forbes, Geoffrey Mclachlan To cite this version: Hien D Nguyen, Florence Forbes, Geoffrey Mclachlan. Mini-batch learning of exponential family finite mixture models. Statistics and Computing, Springer Verlag (Germany), 2020, 30, pp.731-748. 10.1007/s11222-019-09919-4. hal-02415068v2 HAL Id: hal-02415068 https://hal.archives-ouvertes.fr/hal-02415068v2 Submitted on 26 Mar 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Mini-batch learning of exponential family finite mixture models Hien D. Nguyen1∗, Florence Forbes2, and Geoffrey J. McLachlan3 September 6, 2019 1Department of Mathematics and Statistics, La Trobe University, Melbourne, Victoria, Australia. 2Univ. Grenoble Alpes, Inria, CNRS, Grenoble INPy, LJK, 38000 Grenoble, France. yInstitute of Engineering Univ. Grenoble Alpes. 3School of Mathematics and Physics, University of Queensland, St. Lucia, Brisbane, Australia. ∗Corresponding author: Hien Nguyen (Email: [email protected]). Abstract Mini-batch algorithms have become increasingly popular due to the requirement for solving optimization problems, based on large-scale data sets. Using an existing online expectation-- maximization (EM) algorithm framework, we demonstrate how mini-batch (MB) algorithms may be constructed, and propose a scheme for the stochastic stabilization of the constructed mini-batch algorithms. -
An Introduction to MM Algorithms for Machine Learning and Statistical
An Introduction to MM Algorithms for Machine Learning and Statistical Estimation Hien D. Nguyen November 12, 2016 School of Mathematics and Physics, University of Queensland, St. Lucia. Centre for Advanced Imaging, University of Queensland, St. Lucia. Abstract MM (majorization–minimization) algorithms are an increasingly pop- ular tool for solving optimization problems in machine learning and sta- tistical estimation. This article introduces the MM algorithm framework in general and via three popular example applications: Gaussian mix- ture regressions, multinomial logistic regressions, and support vector ma- chines. Specific algorithms for the three examples are derived and numer- ical demonstrations are presented. Theoretical and practical aspects of MM algorithm design are discussed. arXiv:1611.03969v1 [stat.CO] 12 Nov 2016 1 Introduction Let X X Rp and Y Y Rq be random variables, which we shall refer to ∈ ⊂ ∈ ⊂ as the input and target variables, respectively. We shall denote a sample of n in- n dependent and identically distributed (IID) pairs of variables D = (Xi, Yi) { }i=1 1 ¯ n as the data, and D = (xi, yi) as an observed realization of the data. Under { }i=1 the empirical risk minimization (ERM) framework of Vapnik (1998, Ch. 1) or the extremum estimation (EE) framework of Amemiya (1985, Ch. 4), a large number of machine learning and statistical estimation problems can be phrased as the computation of min θ; D¯ or θˆ = arg min θ; D¯ , (1) θ Θ R θ Θ R ∈ ∈ where θ; D¯ is a risk function defined over the observed data D¯ and is de- R pendent on some parameter θ Θ. -
VLSCI Is Funded by the Victorian Government and Contributing Institutions and Is Hosted by the University of Melbourne
VLSCI is funded by the Victorian Government and contributing institutions and is hosted by the University of Melbourne. This petascale facility delivers expertise and systems for life sciences computing. From 2010-2014 the first ever IBM Research Collaboratory for Life Sciences was co-located at VLSCI. CONTENTS EXECUTIVE REPORTS 06. AustrALIAN HPC AT SupercoMPUTING Steering Committee Chair’s Report ................. 6 2014 ................................................................... 52 Scientific Advisory Committee Chair’s Report 8 Director’s Report ................................................. 9 07. INTERActioNS ................................................ 54 In the news ........................................................ 58 01. VLSCI NOW ....................................................... 12 Industry Engagement....................................... 60 About the VLSCI................................................ 13 Our People ........................................................ 14 08. CAREER DevelopMENT FOR COMPUTATIONAL BioloGists .................... 62 02. 2014 SNAPSHots ........................................... 16 PhD Top-Ups, Summer Internships, UROP .... 64 Research Impact ............................................... 17 Internships 2013-2014 ..................................... 68 Collaborations ................................................... 20 Skills Development ........................................... 69 Martin Krzywinski Melbourne Tour ................. 22 MSc (Bioinformatics) Graduates -
Econometrics and Statistics (Ecosta 2018)
EcoSta2018 PROGRAMME AND ABSTRACTS 2nd International Conference on Econometrics and Statistics (EcoSta 2018) http://cmstatistics.org/EcoSta2018 City University of Hong Kong 19 – 21 June 2018 c ECOSTA ECONOMETRICS AND STATISTICS. All rights reserved. I EcoSta2018 ISBN: 978-9963-2227-3-5 c 2018 - ECOSTA Econometrics and Statistics All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted, in any other form or by any means without the prior permission from the publisher. II c ECOSTA ECONOMETRICS AND STATISTICS. All rights reserved. EcoSta2018 Co-chairs: Igor Pruenster, Alan Wan, Ping-Shou Zhong. EcoSta Editors: Ana Colubi, Erricos J. Kontoghiorghes, Manfred Deistler. Scientific Programme Committee: Tomohiro Ando, Jennifer Chan, Cathy W.S. Chen, Hao Chen, Ming Yen Cheng, Jeng-Min Chiou, Terence Chong, Fabrizio Durante, Yingying Fan, Richard Gerlach, Michele Guindani, Marc Hallin, Alain Hecq, Daniel Henderson, Robert Kohn, Sangyeol Lee, Degui Li, Wai-Keung Li, Yingying Li, Hua Liang, Tsung-I Lin, Shiqing Ling, Alessandra Luati, Hiroki Masuda, Geoffrey McLachlan, Samuel Mueller, Yasuhiro Omori, Marc Paolella, Sandra Paterlini, Heng Peng, Artem Prokhorov, Jeroen Rombouts, Matteo Ruggiero, Mike K.P. So, Xinyuan Song, John Stufken, Botond Szabo, Minh-Ngoc Tran, Andrey Vasnev, Judy Huixia Wang, Yong Wang, Yichao Wu and Jeff Yao. Local Organizing Committee: Guanhao Feng, Daniel Preve, Geoffrey Tso, Inez Zwetsloot, Catherine Liu, Zhen Pang. c ECOSTA ECONOMETRICS AND STATISTICS. All rights reserved. III EcoSta2018 Dear Colleagues, It is a great pleasure to welcome you to the 2nd International Conference on Econometrics and Statistics (EcoSta 2018). The conference is co-organized by the working group on Computational and Methodological Statistics (CMStatistics), the network of Computational and Financial Econometrics (CFEnetwork), the journal Economet- rics and Statistics (EcoSta) and the Department of Management Sciences of the City University of Hong Kong (CityU). -
CITATION Award of the Degree of Doctor of Laws Honoris Causa Professor John Hay, AC
CITATION Award of the Degree of Doctor of Laws honoris causa Professor John Hay, AC Chancellor, Professor John Hay, AC, holds degrees in English Literature from the University of Western Australia and Cambridge University, where he held a Hackett Research Scholarship. He is a Fellow of the Australian Academy of the Humanities, the Australian College of Educators and the Australian Institute of Management and has been invested as National Living Pedagogue by the Swedish Academy for Higher Education. He held the position of Chair of English and Head of the Department in the University of Western Australia, where he was also Deputy Chair of the Academic Board. He taught and researched Australian, English and French literature, bibliography and English in secondary education. At Monash University, he was Dean of Arts and Chair of the National Key Centre for Australian Studies and was then appointed Senior Deputy Vice-Chancellor. In 1992, Professor Hay was appointed Vice-Chancellor and President of Deakin University in Victoria and took up his current position of Vice-Chancellor and President of The University of Queensland on January 1, 1996. Under his leadership, both Deakin University and The University of Queensland were named Australia’s Universities of the Year by the Good Universities Guide. The University of Queensland has advanced to second or third position nationally for total competitive research funding and has become Australia’s most successful university in winning and being short-listed for national university teaching awards. Professor Hay has led the development of a nationally unprecedented series of research institutes and centres at UQ with funding in excess of $700 million, and has forged close bonds with both state and federal governments as well as private benefactors such as The Atlantic Philanthropies. -
Mixture Model Clustering in the Analysis of Complex Diseases
CORE Metadata, citation and similar papers at core.ac.uk Provided by Helsingin yliopiston digitaalinen arkisto Department of Computer Science Series of Publications A Report A-2012-2 Mixture Model Clustering in the Analysis of Complex Diseases Jaana Wessman To be presented, with the permission of the Faculty of Science of the University of Helsinki, for public criticism in Auditorium XIV, University of Helsinki Main Building, on 13 April 2012 at noon. University of Helsinki Finland Supervisor Heikki Mannila, Department of Information and Computer Science and Helsinki Institute of Information Technology, Aalto University, Finland and Leena Peltonen (died 11th March 2010), University of Helsinki and National Public Health Institute, Finland Pre-examiners Sampsa Hautaniemi, Docent, Institute of Biomedicine, University of Helsinki, Finland Martti Juhola, Professor, Department of Computer Science, University of Tampere, Finland Opponent Tapio Elomaa, Professor, Department of Software Systems, Tampere University of Technology, Finland Custos Hannu Toivonen, Professor, Department of Computer Science, University of Helsinki, Finland Contact information Department of Computer Science P.O. Box 68 (Gustaf Hällströmin katu 2b) FI-00014 University of Helsinki Finland Email address: [email protected].fi URL: http://www.cs.Helsinki.fi/ Telephone: +358 9 1911, telefax: +358 9 191 51120 Copyright © 2012 Jaana Wessman ISSN 1238-8645 ISBN 978-952-10-7897-2 (paperback) ISBN 978-952-10-7898-9 (PDF) Computing Reviews (1998) Classification: I.5.3, J.2 Helsinki 2012 Unigrafia Mixture Model Clustering in the Analysis of Complex Diseases Jaana Wessman Department of Computer Science P.O. Box 68, FI-00014 University of Helsinki, Finland Jaana.Wessman@iki.fi PhD Thesis, Series of Publications A, Report A-2012-2 Helsinki, Mar 2012, 119+11 pages ISSN 1238-8645 ISBN 978-952-10-7897-2 (paperback) ISBN 978-952-10-7898-9 (PDF) Abstract The topic of this thesis is the analysis of complex diseases, and specifically the use of k-means and mixture modeling based clustering methods to do it. -
Centenary Edition
Acting royalty THE RISE OF UQ ALUMNUS GEOFFREY RUSH GRADUATE contact CENTENARY EDITION CENTENARY EDITION Graduate Contact now online at www.uq.edu.au/graduatecontact At UQ’s Queensland Brain Institute, you’ll find a team of big thinkers working with very smart little creatures. Engineer turned biologist Srini, along with fellow researchers, is investigating the flight behaviour of bees to develop an aircraft guidance system using biology inspired robotics. THE UNIVERSITY OF SRINI A recipient of the Prime Minister’s Prize for Science, Srini came to UQ for the opportunity to conduct ground breaking research. He was also attracted to UQ’s unique, collaborative environment which encourages researchers working across many teams and institutes, to achieve their best. Begin your UQ research experience today. Australia’s most convenient RHD entry scheme means you apply for admission and scholarship with just one form, any day of the year. To apply, visit uq.edu.au/grad-school and discover world-class research for yourself. uq.edu.au/grad-school FullPageAd_Srini_forCONTACT.indd 1 14/01/10 11:52 AM + FROM THE CHANCELLOR Welcome to this special Centenary edition of Graduate Contact. An Act of State Parliament established The University of Queensland in December 1909, CONTENTS and this year we are celebrating the diverse 06 17 achievements of alumni like yourselves, who will continue to shape UQ’s future well beyond 2010. I experienced my first graduation ceremonies as Chancellor in July, and repeating these duties in December brought home the extraordinary achievements of UQ students across many different fields. Particularly pleasing has been presenting awards to a growing number of research higher degree graduates, people whose original work paves the way for others to follow. -
Sponsored by the International Biometric Society
Sponsored by the International Biometric Society The International Biometric Society is devoted to the development and application of statistical and mathematical theory and methods in the biosiciences. The Conference is grateful for the support of the following organisations: The Federation of Pharmaceutical Manufacturers' Associations of JAPAN Organised by the Biometric Society of Japan, Japanese Region of the International Biometric Society Contents List of Sponsors Inside Front Cover Welcome from Presidents Page 2 Welcome from Chairs Page 3 Programme at a Glance Page 4 - 6 Opening Session Page 7 IBC2012 Governance Meetings Schedule Page 8 Organising Committees Page 9 Awards at IBC Kobe 2012 Page 10 General Information Page 11 Venue Information Page 12 Presentation Instruction Page 13 Social Programme Page 15 Mid-Conference Tours Page 16 Scientifi c Programme Page 21 Satellite Symposium Page 46 Map of KICC Page 60 Access Map Page 61 Floorplan Page 62 1 XXVIth International Biometric Conference Message from the IBS President and the IBC 2012 Organising President It is with great pleasure that we welcome all delegates, their families and friends to the XXVIth International Biometric Conference (IBC 2012) being hosted by the Japanese Region in Kobe. It is nearly thirty years since they hosted the one previous IBC held in Japan in Tokyo in 1984. Toshiro Tango and his Local Organising Committee (LOC) have done a wonderful job in providing a socially and scientifi cally inviting program at an outstanding venue. The Kobe International Convention Centre provides excellent spaces for formal meetings/scientifi c sessions and informal conversations/ networking activities which are an essential part of every IBC. -
WINTER NEWSLETTER 2021 Winter NEWSLETTER – July 2021
WINTER NEWSLETTER 2021 Winter NEWSLETTER – July 2021 Dear ANZSCDB members, Welcome to our winter newsletter for 2021. As I hope you will see in our news, there are moves towards opening up of more scientific activities and even partial return to in-person gatherings and events. For our Society this has already resulted in a very successful and enjoyable local-and-zoom symposium from Brisbane in the autumn, with an upcoming symposium in Melbourne and a spring event we can look forward to in Adelaide later in the year. We are full of admiration and thanks for the hard work of the local organisers, our State Reps and others, in hosting these events. As we are learning, every one of these events, and other conferences, is a massive juggling act, with arrangements in limbo up to the last minute, thanks to ongoing travel restrictions, lockdowns, and the continuing spectre of COVID hanging over our nations. We Antipodeans face an interesting and challenging period ahead, as the rest of the world opens up and resumes conferencing - without us! While, in the previous newsletter, I applauded our governments for heeding science in their approach to the pandemic, I find myself utterly dismayed at the unscientific approach now being applied to vaccinating the population. So, until this is achieved, the rest of the world awaits us re-joining them. Our other members performing heroic juggling acts are all those engaged in delivering undergraduate teaching and graduate training. With a widespread and shifting mix of remote and in-person contact, this continues to be a difficult period. -
Australian Animal Welfare Strategy Final Report - Animals in the Wild Sector Review of Existing Animal Welfare Arrangements
Australian Animal Welfare Strategy Final report - Animals in the Wild Sector Review of Existing Animal Welfare Arrangements AUSTRALIAN ANIMAL WELFARE STRATEGY FINAL REPORT ANIMALS IN THE WILD SECTOR ANIMAL WELFARE ARRANGEMENTS Lyndy Scott Page 0 Final Report Australian Animal Welfare Strategy Final report - Animals in the Wild Sector Review of Existing Animal Welfare Arrangements Index Page Executive Summary 2 Introduction 4 Definition of ‘animals in the wild’ 4 Priorities 4 Value Statement 5 Progress against Australian Animal Welfare Strategy Tasks 9 Conclusion 33 Appendix 1 Acronyms used in the report 34 Appendix 2 Wild Animals Working Group members 36 Appendix 3 Some thoughts on sentience 38 Appendix 4 Task 3 – review committee structures, functions and 41 membership at national, State/Territory and local government levels Appendix 5a-e Task 6 - explore animal welfare performance measures 59 not covered by Animal Health Australia Appendix 6a-q Task 9 - consultancy to review current Australian 96 legislation, produce a needs analysis report Appendix 7a Task 12 – review/collate websites promoting animal 163 welfare legislation, codes, etc Appendix 7b Task 12 – review/collate extension work promoting 208 animal welfare legislation, codes, etc Appendix 8a,b Task 16 – research/monitor community attitudes to, 209 and behaviours about, animals in the wild Appendix 9 Task 29 – review current literature, operating procedures 214 and guidlelines for care of captive and non-captive Australian wildlife Appendix 10a,b Tasks 31 and 32 - review practices/procedures