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are based on the Cassowary algorithm, developed in part by Monash researchers. While constraint-based layout is powerful, it can be difficult for users to understand the interactions and behaviour
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queries, and automating data transformations. By combining advancements in natural language understanding, algorithm synthesis, and debugging, the proposed framework will enable developers to efficiently
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experiments for months before the value of output y is measured for some given input x. This creates an exciting challenge for AI researchers to develop smart algorithms that can find the optimal value of input
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This project will seek to further the research into and development of machine learning techniques that may be used to triage, classify, and otherwise process material of a distressing nature (such
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data infrastructure necessary for collaborative research into, and development of, analytical techniques and algorithmic models. The Faculty of Information Technology has a mission to advance social good
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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the headspace website. Possible approaches to addressing this challenge might include: Developing algorithms to identify patterns and preferences based on service users’ previous content engagement
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. Reviewing the literature on self-regulated learning and creating a set of responses from the bot 2. Developing rule-based chatbot 3. Evaluating the bot interface and functionality with a small group of users
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The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information
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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with