Conveners
Cognitive Computing and Machine Learning: I
- Fulufhelo Nelwamondo (CSIR)
Cognitive Computing and Machine Learning: II
- Amit Mishra (University of Cape Town)
Cognitive Computing and Machine Learning: III
- Kiernan Mike (Microsoft)
Prof.
Amit Mishra
(University of Cape Town)
04/12/2017, 11:00
Cognitive Computing & Machine Learning
Invited talk (plenary/keynote)
Unsupervised machine learning can be used to infer the hidden relationships inside of big data where there exists unknown structure and frameworks. Component based analysis seeks to reveal the correlation and variation within a dataset, processing and understanding these results can be challenging. 3D and 2D visualisation is used as a tool for expressing these n-th dimensional results in a...
Prof.
Russ Taylor
(Inter-University Institute for Data Intensive Astronomy)
04/12/2017, 11:30
Cognitive Computing & Machine Learning
Talk
The construction of MeerKAT and emergence of the African VLBI network marks the beginning of the radio astronomy big data revolution in South Africa, and the first steps of the scientific and data pathway to the Square Kilometre Array (SKA). This journey to the SKA represents one of the most significant data challenges in scientific research of the coming decade. To rise to the scientific...
Mr
Kiernan Mike
(Microsoft)
04/12/2017, 12:00
Cognitive Computing & Machine Learning
Talk
Prof.
Fulufhelo Nelwamondo
(CSIR)
04/12/2017, 13:30
Cognitive Computing & Machine Learning
Invited talk (plenary/keynote)
Mechanism Design lies in the area of game theory, with aims to design games whose equilibria have desired objectives such as high efficiency or revenue optimisation. Algorithmic Mechanism Design focuses on Mechanism Design in algorithmically-complex scenarios, and it employs various analytics tools with considerations on computational constraints that exist in polynomial time. What makes this...
Mr
Aljeshi Ahmed
(Intel Corporation)
04/12/2017, 14:00
HPC Techniques and Computer Science
Talk
In this presentation, attendees will hear about the latest Intel Technologies in AI and HPC. This will include Processors, Fabric, Accelerators, and some s/w as well. Also, I will touch base on some of Intel recent strategic acquisitions (e.g. Nervana, MobileEye, and Movidius). I will also include some benchmarks on different CPU's/applications that we tested.
Dr
Xiaoyi Lu
(The Ohio State University)
04/12/2017, 14:30
HPC Techniques and Computer Science
Talk
The convergence of HPC, Big Data, and Deep Learning is becoming the next game-changing business opportunity. Apache Hadoop, Spark, gRPC/TensorFlow, and Memcached are becoming standard building blocks in handling Big Data oriented processing and mining. Modern HPC bare-metal systems and Cloud Computing platforms have been fueled by the advances in multi-/many-core architectures, RDMA-enabled...
Dr
Davide Bacciu
(University of Pisa)
05/12/2017, 13:30
Cognitive Computing & Machine Learning
Invited talk (plenary/keynote)
The focus of this talk is an analysis of the upcoming trends in Deep Learning research, in particular as regards the most promising application fields which are likely to benefit from the AI revolution. We will take a deep dive into Deep Learning applications to Life Science and the Internet of Things, highlighting the challenges and advantages related to working on data with a structured...
Dr
Febe de Wet
(Stellenbosch University)
05/12/2017, 14:00
Cognitive Computing & Machine Learning
Talk
Recent developments in the field of machine learning (ML) have been influenced by advances in computational technology as well as the availability of large volumes of data. One field in which progress has been accelerated substantially is Natural Language Processing (NLP). NLP is a broad research field including topics such as natural language understanding and natural language generation. The...
Dr
Michael Burke
(Council for scientific and industrial research/ University of Witwatersrand)
05/12/2017, 14:20
Cognitive Computing & Machine Learning
Talk
Video cameras are increasingly deployed in exploration, monitoring and surveillance applications. These cameras produce vast amounts of information, which needs to be condensed into manageable quantities for both storage and human-operator evaluation. While data compression can address the former, this does not aid operators, who are often faced with the daunting task of analysing lengthy...
Mr
Matthew Finlayson
(Student)
05/12/2017, 14:40
Cognitive Computing & Machine Learning
Talk
Blockchain based cryptocurrencies are proving themselves to be both popular and unpredictable. In this project we attempt to design a software system to predict the price movement of Bitcoin using Machine Learning techniques. We focus on feature selection, data processing and the training of various classifier neural networks.
