Archive for machine learning

ERC descriptors

Posted in Statistics, Travel, University life with tags , , , , , , , , , , , , on November 9, 2020 by xi'an

Here are the descriptors (or keywords) validated by the (European Research Council) ERC for submitting grant proposal. The recent addition of PE1_15 in the Mathematics panel should help when submitting more methodological projects:

PE1_14 Mathematical statistics
PE1_15 Generic statistical methodology and modelling
PE1_19 Scientific computing and data processing

even though other panels could prove equally suited for some, as in Computer Science and Informatics,

PE6_7 Artificial intelligence, intelligent systems, natural language processing
PE6_10 Web and information systems, data management systems, information retrieval and digital libraries, data fusion
PE6_11 Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
PE6_12 Scientific computing, simulation and modelling tools
PE6_13 Bioinformatics, bio-inspired computing, and natural computing

in Systems and Communication Engineering,

PE7_7 Signal processing

in Integrative Biology,

LS2_11 Bioinformatics and computational biology
LS2_12 Biostatistics

in Prevention,Diagnosis and Treatment of Human Diseases,

LS7_1 Medical imaging for prevention, diagnosis and monitoring of diseases
LS7_2 Medical technologies and tools (including genetic tools and biomarkers) for prevention, diagnosis, monitoring and treatment of diseases

and in Social Sciences and Humanities,

SH1_6 Econometrics; operations research
SH4_9 Theoretical linguistics; computational linguistics

launch of ELLIS

Posted in Statistics, University life with tags , , , , , , , , , on September 15, 2020 by xi'an

The European Laboratory for Learning and Intelligent Systems (ELLIS) is a network (inspired by the Canadian LMB CIFAR network ) that has been recently created to keep European research in artificial intelligence and machine learning at the forefront, to keep up with North America and China where the AI investments are far superior. It has currently 30 units and will be officially launched this Tuesday, 15 September with live streaming. (I am part of the Paris Ellis Unit, directed by Gabiel Peyré.) It also organizes PhD and postdoc exchange programs.

Savage Award session today at JSM

Posted in Kids, Statistics, Travel, University life with tags , , , , , , , , , , on August 3, 2020 by xi'an

Pleased to broadcast the JSM session dedicated to the 2020 Savage Award, taking place today at 13:00 ET (17:00 GMT), with two of the Savage nominees being former OxWaSP students (and Warwick PhD students). For those who have not registered for JSM, the talks are also available on Bayeslab. (As it happens, I was also a member of the committee this year, but do not think this could be deemed a CoI!)

112 Mon, 8/3/2020, 1:00 PM – 2:50 PM Virtual
Savage Award Session — Invited Papers
International Society for Bayesian Analysis (ISBA)
Organizer(s): Maria De Iorio, University College London
Chair(s): Maria De Iorio, University College London
1:05 PM Bayesian Dynamic Modeling and Forecasting of Count Time Series
Lindsay Berry, Berry Consultants
1:30 PM Machine Learning Using Approximate Inference: Variational and Sequential Monte Carlo Methods
Christian Andersson Naesseth, Columbia University
1:55 PM Recent Advances in Bayesian Probabilistic Numerical Integration
Francois-Xavier Briol, University College London
2:20 PM Factor regression for dimensionality reduction and data integration techniques with applications to cancer data
Alejandra Avalos Pacheco, Harvard Medical School
2:45 PM Floor Discussion

Laplace’s Demon [coming home!]

Posted in Kids, Linux, pictures, Statistics, University life with tags , , , , , , , , , , , , , on May 11, 2020 by xi'an

A new online seminar is starting this week, called Laplace’s Demon [after too much immersion in His Dark Materials, lately, ather than Unix coding, I first wrote daemon!] and concerned with Bayesian Machine Learning at Scale. Run by Criteo in Paris (hence the Laplace filiation, I presume!). Here is the motivational blurb from their webpage

Machine learning is changing the world we live in at a break neck pace. From image recognition and generation, to the deployment of recommender systems, it seems to be breaking new ground constantly and influencing almost every aspect of our lives. In this seminar series we ask distinguished speakers to comment on what role Bayesian statistics and Bayesian machine learning have in this rapidly changing landscape. Do we need to optimally process information or borrow strength in the big data era? Are philosophical concepts such as coherence and the likelihood principle relevant when you are running a large scale recommender system? Are variational approximations, MCMC or EP appropriate in a production environment? Can I use the propensity score and call myself a Bayesian? How can I elicit a prior over a massive dataset? Is Bayes a reasonable theory of how to be perfect but a hopeless theory of how to be good? Do we need Bayes when we can just A/B test? What combinations of pragmatism and idealism can be used to deploy Bayesian machine learning in a large scale live system? We ask Bayesian believers, Bayesian pragmatists and Bayesian skeptics to comment on all of these subjects and more.

The seminar takes places on the second Wednesday of the month, at 5pm (GMT+2) starting ill-fatedly with myself on ABC-Gibbs this very Wednesday (13 May 2020), followed by Aki Vehtari, John Ormerod, Nicolas Chopin, François Caron, Pierre Latouche, Victor Elvira, Sara Filippi, and Chris Oates. (I think my very first webinar was a presentation at the Deutsche Bank, New York, I gave from CREST videoconference room from 8pm till midnight after my trip was cancelled when the Twin Towers got destroyed, on 07 September 2001…)

assistant/associate professor position in statistics/machine-learning at ENSAE

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , on March 10, 2020 by xi'an

ENSAE (my Alma Mater) is opening a new position for next semester in statistics or/and machine-learning. At the Assistant Professor level, the position is for an initial three-year term, renewable for another three years, before the tenure evaluation. The school is located on the Université Paris-Saclay campus, only teaches at the Master and PhD levels, and the deadline for application is 31 March 2020. Details and contacts on the call page.