Machine Learning

Agile Cyber Security Summit – BFSI Singapore 2024

The Agile CyberSecurity SG Summit 2024 (CSSG24) is a premier gathering tailored for BFSI security and technology professionals driving innovation in Singapore. This conference serves as a catalyst for immersive discussions, tackling challenges, and fostering the exchange of best practices within the dynamic landscape of cybersecurity and its impact on the BFSI sector and more. […]

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CIO Technology Playbook 2023

Businesses across vertical industries, both in technology savvy as well as emerging countries across Asia/Pacific are changing at blistering pace. Digital technologies are redefining the competitive landscape, lowering traditional barriers to entry. Data-driven innovation is underpinning businesses’ ability to deliver hyper-personalized customer experience, create new sources of revenue using value-added digital services built around existing

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2nd Digital Transformation Jordan

Following the huge success of the first edition, Digital Transformation Jordan returns in physical form on the 14 – 15 March 2022! With the newly approved National Strategy for Digital Transformation, Jordan aims to improve the transparency, flexibility, reliability, and sustainability of digital services, as well as reduce digital services’ time and costs, all consistent

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Using AI Intelligently: Smart ways to use Artificial Intelligence in Payments

What is artificial intelligence? Introduction The concept of artificial intelligence (AI) has been around for a long time and is now making major inroads into financial services. AI has a significant impact in areas such as fraud and compliance, credit scoring, financial distress prediction, robo-advising and algorithmic trading in many financial services firms. For example:

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Real-Time Prediction of Online False Information Purveyors and their Characteristics

Abstract Disinformation, misinformation, and other `fake news’ – collectively false information is quick and inexpensive to create and distribute in our increasingly digital and connected world. Identifying false information early and cost effectively can offset some of those operational advantages. In this paper, we develop light-weight machine learning models that utilize (1) a novel data

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Simon Lucey

Australian Institute for Machine Learning (AIML), University of Adelaide My research is motivated from a passion for discovering the “why?” behind “how?” with respect to core problems in Artificial Intelligence, Computer Vision and Machine Learning. I am currently leading the CI2CV laboratory, newly re-located to the Robotics Institute, Carnegie Mellon University in Pittsburgh, PA, USA where we

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