The Manchester MLO Group conducts world-leading research into a wide
range of techniques and applications of machine learning, optimization,
data mining, probabilistic modelling, pattern recognition and machine
perception. The group spans the field from new theoretical developments
to large applications, and is currently supported by a
number of research bodies, including EPSRC, BBSRC, and several
industry partners.
NEWS:
...show older news items...
January 2012:
Gavin Brown was interviewed on BBC Radio Manchester regarding the REUNITE project.
The University has also issued a press release, and
the Manchester Evening News also ran
the story. UPDATE: The BBC World Service's flagship
technology programme "Click" also featured the project. The podcast
is
available here.
December 2011:
Congratulations to MLO members
Adam Pocock,
Gavin Brown and (APT member)
Mikel Lujan,
on acceptance of their paper to AISTATS 2012, titled
'Informative Priors for Markov Blanket Discovery'.
November 2011:
Joshua Knowles went to the Smart Cities conference in Westminster
to learn about opportunities for ML and Optimization in the future of
power distribution,
waste management, transportation, communications...and a lot more, to
help our cities become greener and more sustainable.
November 2011:
Congratulations to Gavin Brown, Adam Pocock, Ming-Jie Zhao, and Mikel Lujan on acceptance of their
JMLR paper 'Conditional Likelihood Maximisation: A
Unifying Framework for Mutual Information Feature Selection'. Check back for a pre-print in a
few
weeks!
October 2011:
We are pleased to report the successful completion of the REUNITE project.
October 2011:
Congrats to MLO members Richard Allmendinger and Joshua Knowles for their paper "Evolutionary Search in Lethal Environments" at
ECTA 2011, which was nominated for the Best Paper Award !
September 2011:
Congrats to MLO members Ahmad Salman and Ke Chen, for two recent publications
accepted in IEEE TNN and NIPS 2011 !!
Chen K. & Salman A., Learning speaker-specific characteristics with a deep neural architecture.
IEEE Transactions on Neural Networks and Learning Systems, vol. 23, 2012.
Chen K. & Salman A., Extracting speaker-specific information with a regularized Siamese deep network.
Advances in Neural Information Processing Systems 25 (NIPS'11), MIT Press, 2011.
Want to study with us for a PhD?
|
RESEARCH PROFILE
speech recognition,
reinforcement learning,
ensemble methods,
multiobjective optimisation,
systems biology,
probabilistic models,
evolutionary algorithms,
image processing,
deep neural nets,
dynamical systems,
boosting,
information theory,
bayesian methods,
online learning,
fuzzy systems,
speaker identification,
optimisation algorithms,
semi-supervised learning,
unsupervised learning,
biochemical networks,
neural networks,
concept drift,
feature selection,
game theory,
dimensionality reduction,
|
