We are delighted to announce that Dr. José Miguel Hernández-Lobato will join Cambridge MLG as a University Lecturer in Machine Learning later this year. Miguel joins us from Harvard and has a broad range of interests in probabilistic machine learning. For more details see his website.
Author Archive for: MLGall
Cambridge Machine Learning Group has a strong involvement with the new Alan Turing Institute. The ATI is the national institute for research in Data Science and is headquartered in London. It brings together researchers from five top British universities: the Universities of Cambridge, Edinburgh, Oxford, and Warwick, and University College London.
Our own Prof. Zoubin Ghahramani has been appointed University of Cambridge Liason Director.
Group members Prof. Carl Rasmussen and Dr. Adrian Weller have been appointed as ATI Faculty Fellows.
Well done to Yarin Gal who has been awarded the Michael and Morven Heller Research Fellowship at St Catherine’s College, Cambridge.
The fellowship is awarded to
“… exceptional candidates in the field of Computer Science including those who will apply Computer Science to ‘big data’ in all fields including biomedical sciences generally.”
Congratulations to Professor David MacKay who has been awarded a Knighthood in the 2016 New Years honours list. More information on the story can be found here.
The University of Cambridge is inviting applications for a faculty position in the Machine Learning group. The position also offers the opportunity to participate in the newly established national Alan Turing Institute for Data Science (turing.ac.uk). Application instructions at:
The closing date for applications is 11 January 2016.
Zoubin Ghahramani appointed Deputy Director of the new Leverhulme Centre for the Future of Intelligence
The University of Cambridge has announced a new research centre thanks to a £10 million grant from the Leverhulme Trust. Zoubin Ghahramani has been appointed as Deputy Director. According to Zoubin:
“The field of machine learning continues to advance at a tremendous pace, and machines can now achieve near-human abilities at many cognitive tasks—from recognising images to translating between languages and driving cars. We need to understand where this is all leading, and ensure that research in machine intelligence continues to benefit humanity. The Leverhulme Centre for the Future of Intelligence will bring together researchers from a number of disciplines, from philosophers to social scientists, cognitive scientists and computer scientists, to help guide the future of this technology and study its implications.”
Click here to read more about the centre.
We are pleased to announce the Cambridge-Tübingen PhD fellowships between the University of Cambridge Machine Learning Group and the Max Planck Institute for Intelligent Systems Empirical Inference Department in Tübingen.
Seven new papers from the group are to appear at the 2015 conference on Advances in Neural Information Processing Systems (NIPS 2015), to be held in December in Montreal, Canada.
The list of papers are:
- Statistical Model Criticism using Kernel Two Sample Tests
James Lloyd and Zoubin Ghahramani
- MCMC for Variationally Sparse Gaussian Processes
James Hensman, Alex Matthews, Maurizio Filippone and Zoubin Ghahramani
- Stochastic Expectation Propagation
Yingzhen Li, Jose Miguel Hernandez-Lobato and Richard Turner
- A Linear-Time Particle Gibbs Sampler for Infinite Hidden Markov Models
Nilesh Tripuraneni, Shane Gu, Hong Ge and Zoubin Ghahramani
- Neural Adaptive Sequential Monte Carlo
Shane Gu, Zoubin Ghahramani and Richard Turner
- Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions
Amar Shah and Zoubin Ghahramani
- Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Felipe Tobar, Thang Bui and Richard Turner
For the most up to date versions of the papers, visit the authors’ webpages, which may be found through our group members page.
Richard Turner has been appointed University Lectureship in Computer Vision and Machine Learning. His research programme spans computer perception, signal processing, machine learning, and neuroscience. He’ll strengthen connections between the Computational and Biological Learning Lab, the Machine Intelligence Lab and the Signal Processing Lab.
Richard Turner’s website: http://www.gatsby.ucl.ac.uk/~turner/