john shawe-taylor- centre for computational statistics and machine learning

8/3/2019 John Shawe-Taylor- Centre for Computational Statistics and Machine Learning

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April, 2007 CSML External Launch

Centre for Computational

Statistics and Machine Learning

LaunchJohn Shawe-Taylor

April, 2007




Aims of the new centre

Create a framework within which the different groups

can cooperate synergistically Build bridges to the many groups at UCL that could

benefit from advanced data analysis

Develop collaborations with commercial, industrialand scientific groups beyond UCL

Part of a drive towards handling large data for which

there is no pre-defined analysis technique Pioneer a new synthesis between traditional

statistics and new machine learning approaches




Emphasis of orientation Well-founded approaches to data analysis and

machine learning: Statistically analysed

Bayesian approaches

Frequentist analysis

Understanding why and when the differentapproaches are more appropriate – and developingthe theoretical models to match practical applications

Aim to become internationally recognised for thetheoretical foundations and innovative applications ofcomputational statistics and machine learning




Current members

Gatsby Unit

Maneesh Sahani Peter Dayan

Yee Whye Teh

One more position to be

filled Statistics

Philip Dawid

Tom Fearns

Trevor Sweeting

Computer Science

David Barber

Mark Herbster

Massimiliano Pontil

Simon Prince

John Shawe-Taylor

Support:

Jacky Pallace, centremanager

Clare Scurfield, admin support Tom Diethe, web development

and support




Activities: general Seminar series at Gatsby, Statistics, and Computer

Science to be promoted centrally One day PASCAL workshop on May 21 linking with

groups at Cambridge, Bristol, Southampton and Paris Reading groups created with activities visible through

the web site Workshops on specialist themes: eg open house on

complex output learning in July 2006 Visitor programme to ensure exploit potential to

attract international contacts for short stop-overs andlonger visits

MSc Programme in Intelligent systems (Dir Mark) MSc in Computational Statistics and Machine

Learning to be launched in 2008




Activities: clinics New approach to building collaborations with ‘users’

from inside and outside UCL

Half day event at which a potential user will presenttheir problem and describe their data if necessarycovered by an NDA

Representatives of different approaches supportedwithin the centre: kernel methods, statistics, Bayesianinference, etc, discuss options for analysis

Centre able to finance PhDs to assist with initial

pump-priming implementation of interesting solutions Potential for joint grant applications with appropriate

IPR agreements




Activities: clinics First clinic was held in March

Marco Gillies presented a problem concerningintelligent animation

He will discuss the problem, his experience andsome ideas that arose out of the discussions

We would welcome proposals for new clinics

First phase is a discussion with a representative of thecentre to assess potential and identify key issues

If considered useful, presentation at the Clinic could behandled jointly with the representative

No guarantee of outcome, but hopefully helpful discussions




Activities: Industrial Club proposal

Henry Stott from Decision Technologies will

share some thoughts on this option




Web site: www.csml.ucl.ac.uk Active web site providing portal for all dealings with

the centre Entry point for new contacts: can learn about what

approaches can do, how to register for activitiesincluding clinics

Listings for seminars, reading groups, etc.

Easy to enter and register for new events on-line

Automatic generation of emails to interested parties

Supported by database storing activities andcontacts, etc.




Presentations of the three component

groups

Computer Science group: JS-T

Statistics group: Philip Dawid

Gatsby Computational Neuroscience Unit:Peter Dayan




Current Computer Science group David Barber

expert in Bayesian inference over graphical models

has been working in modelling discrete dynamical systems

Mark Herbster graph-based semi-supervised and transductive learning

probabilistic and geometric approaches, spectral clustering

expert in analysis of on-line learning algorithms in an adversarial setting

Massi Pontil

expert in learning theory (particularly kernel methods, regularisation,convex optimisation)

EPSRC advanced research fellow with associated project investigatingmultiple task learning

Simon Prince

applying Bayesian inference in Computer Vision

John Shawe-Taylor

Additional members

Charles Micchelli (Expert in Computational Mathematics)




Current projects




EU Network of Excellence: Principled machine learning, linked to statistics, optimisation and

applications:

computer vision

Brain computer interfaces natural language processing and textual information access

Multimodal integration

speech

JS-T is scientific coordinator (Southampton coordinating site) Linking 56 sites across Europe, Israel and Australia

Innovative management style and broad impact




VISDEM

Inference in Complex StochasticEnvironmental Models

EPSRC funded multi-site project

Involving Manfred Opper from TU Berlin, Aston,Surrey and Met office reps

Bayesian inference for stochastic differentialequations modelling uncertainty and finer scaleeffects

Generating interest in the Met office

Many other potential applications of the technology




Learning the Structure of Music (LeStruM) EPSRCfunded project with University of Plymouth, LeibnizInstitute of Neurobiology and Johannes KeplerUniversity Linz Making fMRI and EEG scans of subjects listening to music Relating structure of responses to structure in the music Insight into how music creates effects and possibly how the

brain processes it?




SMART

Statistical Multilingual Analysis for Retrieval andTranslation (SMART) EU funded STREP

8 site project lead by Xerox research labs in Grenoble

Apply recent advances in machine learning to statistical

machine translation and cross-lingual retrieval

Particularly correlation analysis and discriminative kernelmethods for structured output learning together with on-line adaptation of translation models




Advanced Research Fellowship

5 year EPSRC Advanced Research

Fellowship for Massimiliano Pontil Includes a standard EPSRC project

Learning multiple tasks

Theoretical analysis and practicalimplementations




Gatsby Computational Neuroscience Unit




Statistics Group




Clinics example




Club proposal




Summary

Centre aims to set the agenda for fundamental

analysis in computational statistics and machinelearning

Can provide eclectic support covering the main well-

founded approaches to data analysis Hence providing innovative and informed advice for

users with a wide variety of problems and data fromscience or commerce

Registration on website to be invited soon

But drinks NOW!

john shawe-taylor- centre for computational statistics and machine learning

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