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X-WR-CALDESC:Events for Australian Data Science
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DTSTART:20200101T000000
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BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210818T100000
DTEND;TZID=Australia/Brisbane:20210818T104500
DTSTAMP:20211026T024225Z
CREATED:20210722T013921Z
LAST-MODIFIED:20211026T024225Z
UID:2298-1629280800-1629283500@australiandatascience.net
SUMMARY:AI4Pandemics Talk #3: Jeremy Howard\, fast.ai & University of San Francisco
DESCRIPTION:Speaker: Jeremy Howard \nYouTube Recording \nTitle: How a little-known data scientist convinced the West to wear face masks \n\n\nAbstract:\nThe title of this talk is actually the title of an article in The Telegraph  about my journey in co-founding the Masks4All movement. I share how I found myself becoming the face of Masks4All globally\, and what I learned about making an impact as a data scientist.
URL:https://australiandatascience.net/event/ai4pandemics-talk3-jeremy-howard/
LOCATION:Zoom
ORGANIZER;CN="Hamid Khataee":MAILTO:h.khataee@uq.edu.au
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210813T120000
DTEND;TZID=Australia/Brisbane:20210813T130000
DTSTAMP:20210812T220309Z
CREATED:20210812T220309Z
LAST-MODIFIED:20210812T220309Z
UID:2396-1628856000-1628859600@australiandatascience.net
SUMMARY:Going for Gold: Data Science and the Olympic Games
DESCRIPTION:Going for Gold: Data Science and the Olympic Games\n\nIn this Data Science in the News webinar\, we will explore the important role data science plays in sports and major events like the Olympics.\n\nRegister now\n\n\n\n\n\n\n\nModerator:\n\nDistinguished Professor Kerrie Mengersen – Director\, QUT Centre for Data Science\n\nPanellists:\n\nDr Lachlan Mitchell – Performance Scientist\, Queensland Academy of Sport\, Department of Tourism\, Innovation and Sport\nDr Paul Wu – Senior Lecturer\, Associate Investigator ARC Centre of Excellence for Mathematical & Statistical Frontiers and Centre for Data Science QUT\nDr Allan Hanh – Leader\, Centre of Excellence for Applied Sport Science Research at Queensland Academy of Sport\nProfessor Chris Drovandi – School of Mathematical Sciences\, Program Lead Program Leader Models and Algorithms Centre for Data Science\, QUT\nDr Char-lee Moyle – Senior Lecturer in Management\, QUT Business School\, Co-Leader Social Systems Domain Centre for Data Science\n\nMore about the Panel Session Topics\nDr Lachlan Mitchell: Data in the pool\nLachlan will provide an overview of the data QAS collects and analyses to help out athletes and coaches take on the world in the pool. \nDr Paul Wu: Finding a winning edge through data science: a swimming relay case study\nAs seen in the recent Tokyo Olympics\, swimming relays are a source of medal opportunities for Australia. With ever-increasing competition\, we show how statistical and machine learning approaches can help quantify factors that affect individual and team performances. We also developed a predictive model of gold and medalling probability given team make-up and strategy to support selectors and coaches. \nDr Allan Hanh: Interpreting the results of the Tokyo Olympics\nIn evaluating the performance of various nations at the Olympic Games\, commentators often refer to the number of medals won relative to national population\, but this is a flawed approach. In Tokyo\, the number of medals won was highly related to the size of national economies. The performance of some nations\, however\, differed from predictions derived from that relationship. Exploration of the reasons for the differences could yield insights to guide the evolving design of Australia’s high-performance sport system. \nProfessor Chris Drovandi: Who really won the Olympics?\nIn this talk\, Chris describes a statistical approach that can be used to adjust medal tallies for various factors such as GDP\, population size and number of athletes.  The method is applied to the Tokyo medal tally and some interesting outcomes are revealed. \nDr Char-lee Moyle: Reconceptualising the planning\, monitoring and evaluation of Mega Events: Possibilities for the Brisbane 2032 Olympic Games\nContemporary mega-events\, like the Olympic Games\, are iconic spectacles that can generate substantial economic activity and media attention for host nations\, as well as facilitate global peace and solidarity. However\, historical evidence of cost-blowouts\, exaggerated benefit claims for host nations\, and community disruption detract from potential benefits and have led to a rising crisis of confidence relating to the economic desirability of hosting the Olympic Games. This presentation will explore the history of mega event evaluation and the opportunities for better appraising the benefits for society. \nMore about the Moderator and Panellists\nDr Lachlan Mitchell is a Performance Scientist at the Queensland Academy of Sport specialising in the physiology of elite swimmers. He is a key member of the support team for a number of members of the Australian Dolphins and has supported coaches and athletes who have competed at the last three Olympic Games. Lachlan’s research has centred around new methods of assessing physiological and performance characteristics in elite swimmers\, methods of mathematically describing the relationship between training and performance and using data more effectively to inform training methods. \nDr Paul Wu is a senior lecturer in the School of Mathematical Sciences and a Chief Investigator in the Centre for Data Science (CDS). He is passionate about developing and applying Bayesian and machine learning methods to tackle complex\, real-world problems. Paul leads a number of collaborative projects between data science researchers\, applied researchers and industry practitioners\, especially in ecology\, and sports and fitness. \nDr Allan Hanh is a Strategic Advisor to the research unit of the Queensland Academy of Sport\, and also holds appointments as an Adjunct Professor at the University of Canberra and Griffith University. He is a former Chief Scientist of the Australian Institute of Sport\, where he worked for 27 years and still has an Honorary Emeritus position. He has a long history of involvement in research and the application of findings to practical work with sports. His research activities have included areas such as talent identification\, preparation of athletes for competition in the heat\, altitude training\, doping detection\, and development of technologies aimed at effective athlete monitoring in laboratory and field situations. \nProfessor Chris Drovandi is a Professor in Statistics and Data Science at the Queensland University of Technology (QUT)\, Australia.  He is currently the lead of the QUT Centre for Data Science Models and Algorithms Program. He is an Associate Investigator of the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers\, and an Associate Editor of Statistics and Computing. \nDr Char-lee Moyle is a Senior Lecturer in the School of Management and the Advance Queensland Innovation Metrics Mid-Career Research Fellow at the Queensland University of Technology. She is the co-lead of the Social Systems domain of the Centre for Data Science and a member of the Centre for Future Enterprise. Her domain expertise lies in the field of tourism and event economics.
URL:https://australiandatascience.net/event/going-for-gold-data-science-and-the-olympic-games/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210729T140000
DTEND;TZID=Australia/Brisbane:20210729T153000
DTSTAMP:20210702T020141Z
CREATED:20210702T020141Z
LAST-MODIFIED:20210702T020141Z
UID:2175-1627567200-1627572600@australiandatascience.net
SUMMARY:Data Science Under the Hood: Manifold Learning
DESCRIPTION:Data Science Under the Hood: Manifold Learning\nThis talk introduces Manifold Learning\, the technique to uncover the intrinsic shape of the original data. We also discuss how different manifold learning paradigms can be designed to be incorporated to a dimensionality reduction technique to learn the accurate low-dimensional data representation. \nRegister now
URL:https://australiandatascience.net/event/data-science-under-the-hood-manifold-learning/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210728T100000
DTEND;TZID=Australia/Brisbane:20210728T104500
DTSTAMP:20211026T024218Z
CREATED:20210715T035313Z
LAST-MODIFIED:20211026T024218Z
UID:2278-1627466400-1627469100@australiandatascience.net
SUMMARY:AI4Pandemics Talk #2: Kirsty Short\, UQ
DESCRIPTION:Speaker: Dr Kirsty Short\, The University of Queensland \nYouTube Recording \nTitle: The role of children in the spread of SARS-CoV-2 \nAbstract: \nThe role of children in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains highly controversial. To address this issue\, we performed a meta-analysis of the published literature on household SARS-CoV-2 transmission clusters (n = 213 from 12 countries). Only 8 (3.8%) transmission clusters were identified as having a pediatric index case. Asymptomatic index cases were associated with a lower secondary attack in contacts than symptomatic index cases (estimate risk ratio [RR]\, 0.17; 95% confidence interval [CI]\, 0.09-0.29). To determine the susceptibility of children to household infections the secondary attack rate in pediatric household contacts was assessed. The secondary attack rate in pediatric household contacts was lower than in adult household contacts (RR\, 0.62; 95% CI\, 0.42-0.91). These data have important implications for the ongoing management of the COVID-19 pandemic\, including potential vaccine prioritization strategies.
URL:https://australiandatascience.net/event/ai4pandemics-talk-2-kirsty-short-uq/
LOCATION:Zoom
ORGANIZER;CN="Hamid Khataee":MAILTO:h.khataee@uq.edu.au
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210726T110000
DTEND;TZID=Australia/Brisbane:20210802T150000
DTSTAMP:20210610T053238Z
CREATED:20210610T053238Z
LAST-MODIFIED:20210610T053238Z
UID:2025-1627297200-1627916400@australiandatascience.net
SUMMARY:ECSSC2021
DESCRIPTION:Early Career and Student Statistician Conference 2021 (formerly Young Statisticians Conference) \nThe Early Career & Student Statisticians Conference (ECSSC) 2021 will be held from 26 July to 1 August 2021. We are delighted to announce that we will be holding our conference virtually! ECSSC2021 will bring together the best students and early-career professionals in statistics and data analysis from all around Australia. This event is not to be missed! For the first time we are offering a day for high school students with two streams (years 7-10 and 11-12). Registration for high school students is free of charge. \nTo keep up-to-date with ECSSC2021\, please go to the official conference website. \nWe are also offering a range of pre conference workshops that can be viewed here. \n 
URL:https://australiandatascience.net/event/ecssc2021/
ATTACH;FMTTYPE=image/png:https://australiandatascience.net/wp-content/uploads/2021/06/ECSSC-Logo.png
ORGANIZER;CN="Statistical Society of Australia (SSA)":MAILTO:eo@statsoc.org.au
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210725T110000
DTEND;TZID=Australia/Brisbane:20210725T150000
DTSTAMP:20210708T000706Z
CREATED:20210707T235855Z
LAST-MODIFIED:20210708T000706Z
UID:2188-1627210800-1627225200@australiandatascience.net
SUMMARY:Workshop: Statistical Shape Analysis via Topological Data Analysis
DESCRIPTION:The Statistical Society of Australia and the Early Career and Student Statistician Conference are offering their 2nd short course leading up to the conference\, to be held virtually on \n25 Jul 2021\, 11:00 AM – 3:00 PM AEST. \nAbout the short course: \nAs modern data applications become complex in size and structure\, identifying the underlying shape and structure has become of fundamental importance. The classical approaches such as dimension reduction are challenging for handling these applications. Topological data analysis (TDA) is a rapidly developing collection of methods that focuses on the “shape” of data. TDA can uncover the underlying low-dimensional geometric and topological structures from high-dimensional datasets. TDA has been successfully applied to various areas\, including biology\, network data\, material science\, and geology\, in recent years. The goal of the lecture is to introduce novel TDA methods that can capture geometric or topological information of data and make statistical inferences. This lecture aims to familiarize these new methods along with their applications to various types of data. \nAbout the presenter: \nChul Moon received his Ph.D. in Statistics from the University of Georgia. He joined the Department of Statistical Science at Southern Methodist University as an Assistant Professor in 2018. His research interests include topological data analysis\, empirical likelihood\, and ranked set sampling. His research aims to develop statistical methods in biosciences and geosciences. \nPrerequisites: \nBasic statistical knowledge and R. \nFor more information and to register please click here.
URL:https://australiandatascience.net/event/workshop-statistical-shape-analysis-via-topological-data-analysis/
LOCATION:Zoom
CATEGORIES:Online workshop
ORGANIZER;CN="Statistical Society of Australia (SSA)":MAILTO:eo@statsoc.org.au
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210724T110000
DTEND;TZID=Australia/Brisbane:20210724T150000
DTSTAMP:20210708T000603Z
CREATED:20210708T000439Z
LAST-MODIFIED:20210708T000603Z
UID:2194-1627124400-1627138800@australiandatascience.net
SUMMARY:Workshop: Convex Optimization for Statistical and Machine Learning with CVXR
DESCRIPTION:The Statistical Society of Australia and he Early Career Student Statistician Conference 2021 are offering this workshop on Convex Optimization for Statistical and Machine Learning with CVXR. \nOptimization plays an important role in fitting many statistical models. Some examples include least squares\, ridge and lasso regression\, Huber regression\, and support vector machines. CVXR is an R package that provides an object-oriented modeling language for convex optimization. It allows the user to formulate convex optimization problems in a natural mathematical syntax rather than the standard form required by most solvers. Moreover\, problems can be easily modified and re-solved\, making the package ideal for prototyping new statistical methods. First\, the user specifies an objective and set of constraints by combining constants\, variables\, and parameters using a library of functions with known mathematical properties. CVXR then applies disciplined convex programming (DCP) to verify the problem’s convexity. Once verified\, the problem is automatically converted into quadratic or conic form and passed to a solver like OSQP\, MOSEK\, or GUROBI. We demonstrate CVXR’s modeling framework with several applications in statistics and machine learning. \nWe will begin with a gentle introduction to convex optimization using examples from ordinary least squares and penalized regression. This will be followed by a high-level description of CVXR\, how it differs from other packages\, and a discussion of the domain specific language that CVXR implements. We will show how CVXR works on different classes of problems\, such as linear programs\, quadratic programs\, and semidefinite programs\, and demonstrate its usage with a variety of examples. Finally\, we will have a segment for potential developers in which we go over the nuts and bolts of adding new functions to CVXR’s library. \nAbout the presenter: Anqi Fu is a Ph.D candidate in the Electrical Engineering department at Stanford University. Her research focuses on developing algorithms and software for large-scale optimization with applications to data science. One of her recent projects leverages methods from optimal control to design treatment plans for cancer radiation therapy. Prior to starting her Ph.D\, Anqi worked as a machine learning scientist at H2O.ai. She received an M.S. in Statistics from Stanford University\, and a B.S. in Electrical Engineering and a B.A. in Economics from the University of Maryland\, College Park. \nPrerequisites:  A working knowledge of statistics and linear algebra\, and basic experience with a scripting language like R. We also invite attendees to bring problems of interest\, which we will do our best to formulate and solve in CVXR. \nFor more information and to register please click here. \n 
URL:https://australiandatascience.net/event/workshop-convex-optimization-for-statistical-and-machine-learning-with-cvxr/
LOCATION:Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210714T173000
DTEND;TZID=Australia/Brisbane:20210714T190000
DTSTAMP:20210617T013848Z
CREATED:20210617T013848Z
LAST-MODIFIED:20210617T013848Z
UID:2046-1626283800-1626289200@australiandatascience.net
SUMMARY:A Celebration of Mathematics – Diversity in STEM
DESCRIPTION:A Celebration of Mathematics – Diversity in STEM\nAMSI welcomes all students\, researchers and professionals with an interest in STEM to join the team for a relaxed evening of talks and lively discussions! \nRegister now
URL:https://australiandatascience.net/event/a-celebration-of-mathematics-diversity-in-stem/
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210714T120000
DTEND;TZID=Australia/Brisbane:20210714T130000
DTSTAMP:20210625T054601Z
CREATED:20210625T053614Z
LAST-MODIFIED:20210625T054601Z
UID:2158-1626264000-1626267600@australiandatascience.net
SUMMARY:ACEMS Virtual Public Lecture - A Song of Wind & Fire
DESCRIPTION:ACEMS Virtual Public Lecture – A Song of Wind & Fire: a statistical journey through an uncertain world\n\n\nIn this lecture\, ACEMS Associate Investigator Dr Rachael Quill will explore how shedding light on the uncertainties of wind flow across the environment can support informed decision-making in bushfire management and renewable energy generation.\nThe weather and its uncertainties influence our decisions every day. Did you take an umbrella today\, just in case\, or did you get caught in that shower? In many scenarios\, being unprepared for the unknown might only mean a dampening of our pride. But in others\, the cost of not understanding uncertainty can be catastrophic. \n\nRegister now
URL:https://australiandatascience.net/event/acems-virtual-public-lecture-a-song-of-wind-fire/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210714T100000
DTEND;TZID=Australia/Brisbane:20210719T104500
DTSTAMP:20211026T024210Z
CREATED:20210709T023716Z
LAST-MODIFIED:20211026T024210Z
UID:2221-1626256800-1626691500@australiandatascience.net
SUMMARY:AI4Pandemics Talk #1: Chris Rackauckas\, MIT
DESCRIPTION:The first AI4PAN seminar speaker will be Chris Rackauckas (MIT) \nYouTube Recording \nTitle: \nLearning Epidemic Models That Extrapolate. \nAbstract: \nModern techniques of machine learning are uncanny in their ability to automatically learn predictive models directly from data. However\, they do not tend to work beyond their original training dataset. Mechanistic models utilize characteristics of the problem to ensure accurate qualitative extrapolation but can lack in predictive power. How can we build techniques which integrate the best of both approaches? In this talk we will discuss the body of work around universal differential equations\, a technique which mixes traditional differential equation modeling with machine learning for accurate extrapolation from small data. We will showcase how incorporating different variations of the technique\, such as Bayesian symbolic regression and optimizing the choice of architectures\, can lead to the recovery of predictive epidemic models in a robust way. The numerical difficulties of learning potentially stiff and chaotic models will highlight how most of the adjoint techniques used throughout machine learning are inappropriate for learning scientific models\, and techniques which mitigate these numerical ills will be demonstrated. We end by showing how these improved stability techniques have been automated and optimized by the software of the SciML organization\, allowing practitioners to quickly scale these techniques to real-world applications. \n\n 
URL:https://australiandatascience.net/event/ai4pan-seminar-series-with-chris-rackauckas-mit/
LOCATION:Zoom
CATEGORIES:Seminar
ORGANIZER;CN="Hamid Khataee":MAILTO:h.khataee@uq.edu.au
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210712T080000
DTEND;TZID=Australia/Brisbane:20210723T170000
DTSTAMP:20210507T075841Z
CREATED:20210507T075306Z
LAST-MODIFIED:20210507T075841Z
UID:1909-1626076800-1627059600@australiandatascience.net
SUMMARY:2021 AMSI Winter School on Statistical Data Science
DESCRIPTION:2021 AMSI Winter School on Statistical Data Science\nAMSI and Queensland University of Technology are proud to present the 2021 Winter School on Statistical Data Science from 12-23 July. \nFor the first time\, the program will be hosted virtually with options for students to attend event hubs in selected states. Boasting an impressive speaker line-up\, attendees can delve deeper into modules focusing on: \n\nBayesian statistics\,\nAdvanced Markov chains and Monte Carlo methods\nLikelihood-free inference\nModern neural networks\nDimension reduction for high dimensional data\n\nThis event is aimed at postgraduate students\, early career researchers and industry professionals wanting to sharpen their skills. \nApplications are now open and will close at 11.59pm on Sunday 20 June. \nScholarships are also available to AMSI Member students requiring financial assistance to cover program fees. To apply\, go to https://ws.amsi.org.au/apply-for-a-scholarship/ \nFor any further enquiries\, please contact coordinator_rhed@amsi.org.au or visit our website for more details https://ws.amsi.org.au/ \nIf you are an academic and know of someone who may be interested in attending\, we encourage you to forward these details and spread the word about the program. \nApply Now
URL:https://australiandatascience.net/event/2021-amsi-winter-school-on-statistical-data-science/
CATEGORIES:Event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210705T090000
DTEND;TZID=Australia/Brisbane:20210709T150000
DTSTAMP:20210610T051526Z
CREATED:20210610T051526Z
LAST-MODIFIED:20210610T051526Z
UID:2017-1625475600-1625842800@australiandatascience.net
SUMMARY:Australian and New Zealand Statistical Conference (ANZSC2021)
DESCRIPTION:Australian and New Zealand Statistical Conference (ANZSC2021) \nThe organising committee warmly invites you to the 2021 Australian and New Zealand Statistical Conference\, which will take place online from the 5th to the 9th July 2021. \nThis conference brings together three leading statistical communities – the Statistical Society of Australia\, the New Zealand Statistical Association – and the Australian Conference on Teaching Statistics. \nThe aim of this Conference is to bring together a broad range of researchers and practitioners across a variety of statistical disciplines to facilitate the exchange of theory\, methods and applications. \n  \n  \nWith these three societies working together there will be strong program components of interest to a wide diversity of academic\, government\, and industry colleagues. This includes the full spectrum of delegates from those advancing theoretical methodology to those working on industry applications (in traditional and non-traditional statistical areas). Of particular interest is how Big Data continues to impact all of us. \nThe program is available here.
URL:https://australiandatascience.net/event/australian-and-new-zealand-statistical-conference-anzsc2021/
LOCATION:Virtual – Zoom and Slack\, Australia
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210629
DTEND;VALUE=DATE:20210701
DTSTAMP:20210624T020310Z
CREATED:20210624T015831Z
LAST-MODIFIED:20210624T020310Z
UID:2098-1624924800-1625097599@australiandatascience.net
SUMMARY:ACEMS Impact Workshop for Researchers and Students
DESCRIPTION:ACEMS Impact Workshop for Researchers and Students\nACEMS is pleased to invite you to attend a workshop on the topic of Research Impact\, tailored for the mathematical sciences.  It will be co-facilitated by Impact Research Academy and ACEMS. \nWorkshop Details – Please RSVP (for Zoom Links) \nAims and Benefits of Workshop \nThis workshop is designed\, firstly\, to be of practical career benefit to participating researchers and research students and\, secondly\, to help you generate outputs to communicate and promote the benefits of your research. \nThe workshop will help participants to: \n\nunderstand the growing significance of research impact in the Australian\, and wider\, research context – and provide practical knowledge to help you in your research career\nthink about the benefits\, within and beyond academia\, realised from the mathematical sciences (from theoretical to applied) and your research\nbuild and share knowledge\, and grow capabilities\, around research impact\, including best practices for creating\, capturing\, valuing\, and communicating your research impact\nengage in practical activities designed to help you\n\nexplore a mixture of methods to value your research impact\ncommunicate some of your research impact (prospectively or retrospectively)\n\n\nenjoy discussions designed to help us all think about how we can amplify our impact\nhelp you prepare research impact statements/narratives\, including for use in reporting and promoting your work\n\nThe workshop will be held online (over Zoom) over two part-days.  Ideally\, participants will attend both days (or as much as they can). \n\nDates: 29th & 30th June\nTime: 9.30am – 12.30pm AEST\nWhere: Via Zoom (note there is a different link for each day)\nPlease click on this Eventbrite page to:\n\nview the program overview for both days\nregister to attend (you will receive Zoom links following registration)\nstay updated on any developments (including local node activities linked to the workshop)
URL:https://australiandatascience.net/event/acems-impact-workshop-for-researchers-and-students-2/
CATEGORIES:Online workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210623T093000
DTEND;TZID=Australia/Brisbane:20210623T103000
DTSTAMP:20210617T012300Z
CREATED:20210617T012259Z
LAST-MODIFIED:20210617T012300Z
UID:2043-1624440600-1624444200@australiandatascience.net
SUMMARY:Bayesian hierarchical stacking—All models are wrong\, but some are somewhere useful
DESCRIPTION:Bayesian hierarchical stacking—All models are wrong\, but some are somewhere useful\nStacking is a widely used model averaging technique. Like many other ensemble methods\, stacking is more effective when model predictive performance is heterogeneous in inputs\, in which case we can further improve the stacked mixture with a hierarchical model. In this talk I will focus on the recent development of Bayesian hierarchical stacking: an approach that locally aggregates models. The weight is  a function of data\, partially-pooled\, inferred using Bayesian inference\,  and can further incorporate other structured priors and complex data. I will also discuss some theory bounds: when and why model averaging is useful; what model dissimilarity metric is relevant to Bayesian ensembles. \nRegister now
URL:https://australiandatascience.net/event/bayesian-hierarchical-stacking-all-models-are-wrong-but-some-are-somewhere-useful/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210622T180000
DTEND;TZID=Australia/Brisbane:20210622T193000
DTSTAMP:20210604T042940Z
CREATED:20210602T231905Z
LAST-MODIFIED:20210604T042940Z
UID:1994-1624384800-1624390200@australiandatascience.net
SUMMARY:AI and the Future of Education
DESCRIPTION:AI and the Future of Education\nMonash Education\, in collaboration with the Monash Data Futures Institute\, is organizing a panel discussion on “AI and the future of education” with internationally acclaimed researchers who will cast a critical eye on the increasing attention being paid to AI-driven applications and systems in education. \nThe panel will explore questions like “what forms of AI technology are being implemented in education\, and what implications do they have for students\, teachers and education institutions?” and “how do the imagined educational benefits of AI contrast with the practical limitations of actually using these technologies?”. \nRegister now
URL:https://australiandatascience.net/event/ai-and-the-future-of-education/
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210621T000000
DTEND;TZID=Australia/Brisbane:20210723T000000
DTSTAMP:20210610T054119Z
CREATED:20210610T054008Z
LAST-MODIFIED:20210610T054119Z
UID:2031-1624233600-1626998400@australiandatascience.net
SUMMARY:ECSSC2021 Video Competition
DESCRIPTION:ECSSC2021 Video Competition  \nSubmissions will open shortly for ECSSC2021 Video Competition. Working on any research? Put a video together and demonstrate your ability to concisely disseminate your research to a wider audience. Any student or early career statistician (within 5 years of graduation) in a statistics related field is welcome to enter the competition (sorry – previous winners are excluded). There is no entry fee! \nFor inspiration\, please consider viewing previous submissions and winners. All submitted videos have been posted in the here. \n\n\n\nSubmissions open\n21st June 2021\n\n\nSubmissions close\n23rd July 2021\n\n\nPeople’s choice voting opens\n26th July 2021\n\n\nPeople’s choice voting closes\n1st August 2021\n\n\nWinners Announced\n1st August 2021
URL:https://australiandatascience.net/event/ecssc2021-video-competition/
ORGANIZER;CN="Statistical Society of Australia (SSA)":MAILTO:eo@statsoc.org.au
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Brisbane:20210616T140000
DTEND;TZID=Australia/Brisbane:20210616T150000
DTSTAMP:20210604T072211Z
CREATED:20210604T072151Z
LAST-MODIFIED:20210604T072211Z
UID:2006-1623852000-1623855600@australiandatascience.net
SUMMARY:Hosted by ACEMS | Oracle for Research Grants to Support Researchers\, Data & Projects
DESCRIPTION:Hosted by ACEMS | Oracle for Research Grants to Support Researchers\, Data & Projects\nYou are invited to attend an ACEMS event about free computational grants and community support for researchers and collaborative projects with Oracle for Research. Please see below for more information\, and register via EventBrite. \nACEMS is pleased to host this online talk\, Q&A\, and discussion\, with guests from Oracle for Research. \nOverview: \nIn this online session\, you can learn about opportunities to accelerate research to results\, and gain support for collaborative projects\, using cloud computing and computational grants from Oracle for Research. \nBenefits of Oracle for Research grants will be discussed\, including: \n\nAccess to free cloud credits to support your AI\, HPC and GPU workloads\nAccess to scalable cloud-computing capabilities and advanced analytics for data-intensive research experiments\nOpportunities to connect with other research institutions and industry partners\nReceive technical assistance with Oracle Cloud platform and infrastructure\n\nNote: there are other/further benefits for research students\, entrepreneurs\, and also projects eligible for Oracle’s Community Model Support. \nTopics covered will include: \n\nWhat is Oracle for Research?\nOracle for Research team members supporting researchers and facilitating access to grants and community support\nCase studies for Oracle for Research Grants\nThe easy Oracle for Research grant application process and what to do if you’re interested in applying\nHow Oracle for Research is seeking to support and build community\nAnswers to FAQ About Grants (No\, Oracle does not own your data/IP)\n\nQ&A and Discussion: \nFollowing the presentation from Oracle for Research guests\, there will be a moderated Q&A and discussion. This will provide an opportunity to: \n\nAsk any questions about the Oracle for Research grants and Community Support Model\nEngage in a moderated discussion about research and projects which may be suitable for support from Oracle for Research\nShare ideas for possible new projects (including\, for example\, in relation to environmental modelling\, health\, bioinformatics\, geospatial applications – and more)\n\nWho should attend? \nThis session is designed to be of particular benefit to researchers (across diverse disciplines)\, research students\, research partners\, and others from outside academia who may be interested in collaboration (and grant support). \nAttendees will include those from mathematics\, statistics\, data science\, and other research disciplines\, plus ACEMS extended network and other interested guests\, including from the Australian Data Science Network\, industry and otherwise outside academia. \nFeel free to invite others in your network who may be interested in attending. \nRSVP to Attend: \nPlease RSVP to attend\, via this Eventbrite form. You will then receive the Zoom link to join the online event. \n 
URL:https://australiandatascience.net/event/hosted-by-acems-oracle-for-research-grants-to-support-researchers-data-projects/
CATEGORIES:Online workshop
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