Seminar and Conference News
Title: Scalable Machine Learning for R with MapR
Prior to joining MapR, Joe developed predictive models in health care for Optum (a division of UnitedHealth) as Chief Scientist. He was the first Fellow for Optum's start-up, Optum Labs and has several patents pending.
Before his time at Optum, Joe accumulated over 10 years of data science experience at Fair Isaac, Lexis Nexis, HNC Software and ID Analytics (now LifeLock) specializing in business problems such as fraud & anomaly detection, which yielded a patent for identity theft detection.
Seminar: Social Network 2.0 – from sharing experiences to sharing values, Prof Xue Li, Canberra, Tuesday 6 Dec
Topic: Social Network 2.0 – from sharing experiences to sharing values
Speaker: Prof. Xue Li, University of Queensland
Date and time: 4:30-5:30pm, Tuesday 6 Dec 2016
Location: 6C34 (Building 6, room C34), University of Canberra
In current social networks, people share their information, feelings, and experiences with or without their true online identities. For the last 10 years, we have experienced many problems such as spamming, cyberbullying, and misusage of social media for causing problems such as London Riots. One key question is about whether we are OK to associate our true identity with the cyber identity. In social network connected services such as Uber and Airbnb, people are using there traceable identities in the cyberspace, where all transactions are protected by insurance companies or by law. So the question is: if people are willing to use their true identity online in order to share services and values, how can we make social networks a trust-worthy place? In this talk, we discuss the concept of Social Network 2.0 as an emerging type of social networks where people are OK to use their true identities to come together in order to share the services and values. We will present our understanding on the problems on this type of new generation social networks and some of our research initiatives.
About the speaker:
Dr Xue Li is a Professor in DKE (Data and Knowledge Engineering) Division, School of Information Technology, the University of Queensland in Australia. He obtained a BSc in Computer Science in Chongqing University, China in 1982, a MSc in the University of Queensland in 1989, and a PhD in Information Systems in QUT 1997. His research interests are in data mining, intelligent information systems, and social computing. He has over 160 publications as monograph, edited books, book chapters, and journal and conference papers. He was recognized as one of the Top-50 “Most Powerful People in Australia” in 2015 by Australian Financial Review. He has successfully supervised 17 PhD candidates to completion as their Principal Supervisor. He is currently a Chief Investigator for three ARC (Australian Research Council) Funding Projects. He is an Associate Editor of Journal of Advanced Internet of Things.
Seminar: Exploring causal relationships in observational data, Prof. Jiuyong Li. Canberra, 4:15pm Wed 16 Nov 2016
Topic: Exploring causal relationships in observational data
Speaker: Prof. Jiuyong Li, University of South Australia
Date and time: 4:15-5:15pm, Wednesday 16 Nov 2016
Location: Visitor Centre theatre, AIS, Bruce, Canberra
Association analysis is an important technology in data mining, and has been widely used in many application areas. However, associations in data can be spurious and they do not indicate causal-effect relationships that are ultimate goals for many scientific explorations and social studies. While the techniques for association discovery become mature, the problem for identifying non-spurious associations becomes prominent. In this talk, I will discuss some current methods for causal relationship discovery and our research work in this direction.
About the speaker:
Dr Jiuyong Li is a Professor and an Associate Head of School at the School of Information Technology and Mathematical Sciences of University of South Australia. He leads the Data Analytics Group in the School. His main research interests are in data mining, bioinformatics, and data privacy. He has led five Australian Research Council Discovery projects and leads a Data to Decision CRC project. He has published more than 100 papers, mostly in leading journals and conferences in the areas. His software tools have been used in several real world projects. He has been a chair (or a PC chair) of multiple Australasian data mining and artificial intelligence conferences and international causal discovery workshops. He has received senior visiting fellowships from Nokia Foundation, the Australian Academy of Science, and Japan Society of Promotion of Science.
Short Course on R and Data Mining
Information Technology and Engineering, University of Canberra
Target Audience: IT&E Project students (ICTP students,
Technology Project students, ISES students), IT&E HDR students and
Staff, members of the Canberra Data Scientists Group
Fees: There is no fees for the short course but seats are limited to 60 – so register early through http://www.meetup.com/CanberraDataSci/events/234168862/
Time: 9:30am – 12:30pm, Fri 7 Oct 2016
Room: 2B7 (Building 2, room B7, University of Canberra)
Map and Parking:
The course will cover R programming, data exploration and visualisation, and data mining with R. It will cover four topics below in two sessions. Each 1.5-hour session will consist of presentations on two topics, followed by lab for students to do exercises.
- R Programming and Data Exploration and Visualisation with R
- Regression and Classification with R
- Association Rule Mining with R
- Text Mining with R -- an Analysis of Twitter Data
Instructions, prerequisites and slides for the course are or will be available at http://www.rdatamining.com/training/uc.
Sorry, this seminar has been cancelled.
Topic: Entity Extraction from Text Documents
Topic: Detecting Persistent Threats using Sequence Statistics
Speaker: Dr. Ted Dunning, Chief Application Architect at MapR
Time and date: 4:30-6:30pm, Monday 5 September 2016
Location: 40 Cameron Avenue in Belconnen at HP Enterprise
In a persistent threat, the attacker often penetrates a system but exploits information captured there elsewhere at a throttled rate to avoid detection. In some cases, the attacker even takes measures to protect the penetrated system from other attackers to avoid the detailed inspection that often accompanies the detection of a compromise. I will describe one particular kind of situation in which a single point of compromise is used to extract consumer financial information that is then used elsewhere to commit fraud. This kind of attack can be difficult to detect and hard to trace. In fact, however, detailed examination of transaction histories across thousands to millions of accounts can provide a very sensitive indicator of such activity and can often pin-point the original point of compromise. The detection technique that I will describe has very broad applicability across many problems that involve sequences of symbols and has produced state-of-art results in genomics, fraud detection, text analysis, retail recommendations and predicting attrition and profitability. The specific case that I describe in this talk is also interesting since the technique was initially developed using synthetic data which emulated real data closely enough that a fraud ring was detected the first time out.
About the speaker:
Ted Dunning is Chief Application Architect at MapR Technologies and committer and PMC member of the Apache Mahout, Apache ZooKeeper, and Apache Drill projects. Ted has been very active in mentoring new Apache projects and is currently serving as vice president of incubation for the Apache Software Foundation. Ted was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems. He built fraud detection systems for ID Analytics (LifeLock) and he has 24 patents issued to date and a dozen pending. Ted has a PhD in computing science from the University of Sheffield. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting.
Pizzas and drinks will be sponsored by MapR. The venue will be sponsored by HP Enterprise.
14th Australasian Data Mining Conference (AusDM 2016)
6-8 December 2016
Join us on LinkedIn: http://www.linkedin.com/groups/AusDM-4907891
The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. AusDM'16 seeks to showcase: Research Prototypes; Industry Case Studies; Practical Analytics Technology; and Research Student Projects.
Publication and topics
We are calling for papers, both research and applications, and from both academia and industry, for presentation at the conference. Accepted papers will be published in an up-coming volume (Data Mining and Analytics 2016) of the Conferences in Research and Practice in Information Technology (CRPIT) series by the Australian Computer Society which is also held in full-text on the ACM Digital Library. AusDM invites contributions addressing current research in data mining and knowledge discovery as well as experiences, novel applications and future challenges.
Submission of papers
- Academic submissions: Regular academic submissions can be made in Research Track reporting on research progress, with a paper length of between 8 and 12 pages in CRPIT style.
- Industry submissions: Submissions can be made in the Application Track to report on specific data mining implementations and experiences in governments and industry projects. Submissions in this category can be between 4 and 8 pages in CRPIT style.
- Industry Showcase submissions: Submission from industry and government on an analytics solution that has raised profits, reduced costs and/or achieved other important policy and/or business outcomes can be made in this track with a one page Abstract only.
Online submission system
Paper Submission: extended to 6pm, Friday 2 Sept 2016, Australian Eastern Standard Time (AEST)
Authors Notified: Monday 24 October 2016
Camera Ready Submission: Monday 7 November 2016
Conference Dates: 6-8 December 2016
A/Prof. Andrew Robinson from Melbourne University gave a talk on Data Mining for Biosecurity Regulation at a seminar organised by the Canberra Data Scientists meetup group today.
Slides of the talk can be found at http://www.meetup.com/CanberraDataSci/files/.
Topic: Data Mining for Biosecurity Regulation
About the speaker:
Training certificates have been sent out. If you haven't received a certificate, please contact me on yanchang(at)RDataMining.com and also tell me when you attended the workshop, so that I can send a certificate to you. Thanks.
See the link below for photos at the Machine Learning 102 Workshop for the Big Data and Analytics course at the S P Jain School of Global Management, Mumbai, India, 30 May - 5 June 2016.To students at above workshop: