News
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Launching the Flower Federated Learning Tool
At this week’s google FL workshop, we are announcing our open source tool that makes it easier to devise and evaluate FL algorithms under real-world conditions: http://flower.dev. The paper can be found on arxiv.
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Research Group is Moving to Cambridge
Our research group is moving to the Department of Computer Science and Technology at the University of Cambridge for the beginning of the 2020-2021 academic year.
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Talk by Shangzhe Wu
Shangzhe Wu presented their work on “Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild” which was awarded Best Paper at CVPR 2020!
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Talk by Miltos Allamanis
Miltos Allamanis visited on 11 February 2020 and gave a talk on Analyzing Source Code using Graph Neural Networks and Natural Language.
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Talk by Andreas Soleiman
Andreas Soleiman visited from Uppsala University to present his work on battery-free backscatter systems: “Towards Sustainable Widespread Sensing”.
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Talk by Peter Blacker
Peter Blacker, from the University of Surrey, visited to present his talk on “Deep Learning in Space”.
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Talk by David Kotz
David Kotz, from Dartmouth College, visited to present his talk on “Secure, Intentional Communications with Mobile Devices”.
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Talk by Tao Gu
Tao Gu, from RMIT, visited to present their talk on “Surviving Screen-off Battery through Out-of-Band Wi-Fi Communication”.
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Workshop and Hackathon in Conjunction with Intel AI and Kellogg College
Edgar Liberis helped to organise a workshop and hackathon using Intel’s Neural Compute Stick (NCS) accelerator.
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Talk by Paul Whatmough
Paul Whatmough visited on 7 March and gave a talk on Algorithm-Hardware Co-Design for Energy-Efficient Neural Network Inference.
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Talk by Petar Veličković
Petar Veličković visited our group and spoke on the intersection of adversarial learning and graphs.
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ICLR 2019 accepted paper
Our paper, “A Systematic Study of Binary Neural Networks’ Optimisation”, was accepted at ICLR 2019.
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