Machine Learning Systems

Designing systems that are largely defined by the execution of machine learning workloads present new open problems that straddle the domains of systems, hardware and artificial intelligence. Cyber-physical systems are a prime example of this emerging category. This activity considers the needs of the next generation of machine-learning-centric systems in terms of: design, interfaces and abstractions; parallel, distributed and scalable learning/inference algorithms; hardware co-design for efficiency and high-utilization; and finally, interpretability, security and testing.

Selected Publications

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• DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination

  M.R.U. Saputra P.P.B. de Gusmao C.X. Lu Y. Almalioglu S. Rosa C. Chen J. Wahlstrom W. Wang A. Markham and N. Trigoni

  In IEEE Robotics and Automation Letters (RAL) + IEEE ICRA. 2020.

  Details about DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination | BibTeX data for DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination | Download  (pdf) of DeepTIO: A Deep Thermal−Inertial Odometry with Visual Hallucination

• Distilling Knowledge From a Deep Pose Regressor Network

  Muhamad Risqi U. Saputra Pedro P. B. de Gusmao Yasin Almalioglu Andrew Markham and Niki Trigoni

  In IEEE/CVF International Conference on Computer Vision (ICCV). 2019.

  Details about Distilling Knowledge From a Deep Pose Regressor Network | BibTeX data for Distilling Knowledge From a Deep Pose Regressor Network | Download of Distilling Knowledge From a Deep Pose Regressor Network

• Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning

  Muhamad Risqi U. Saputra Pedro P. B. de Gusmao Sen Wang Andrew Markham and Niki Trigoni

  In IEEE International Conference on Robotics and Automation (ICRA). 2019.

  Details about Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning | BibTeX data for Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning | Download  (pdf) of Learning Monocular Visual Odometry through Geometry−Aware Curriculum Learning