lamsade

Machine Learning

Machine Learning

Florian Yger

HCERES Visit, 10/24/17

Florian Yger Machine Learning

lamsade

Machine Learning

Themes of the project

Overall aimHow to learn optimal decisions from large amounts of data in achanging context ?

Scientific challenges - at the cross-road between pole 1 and pole 3

Representation learning (and invariance design)Learning for decision making under uncertainty

Florian Yger Machine Learning

lamsade

Machine Learning

Themes of the project

Scientific challenges - at the cross-road between pole 1 and pole 3

Representation learning (and invariance design)Learning for decision making under uncertainty

Florian Yger Machine Learning

lamsade

Machine Learning

Themes of the project

Scientific challenges - at the cross-road between pole 1 and pole 3

Representation learning (and invariance design)Learning for decision making under uncertainty

Florian Yger Machine Learning

lamsade

Machine Learning

Themes of the project

Scientific challenges - at the cross-road between pole 1 and pole 3

Representation learning (and invariance design)Learning for decision making under uncertainty

ApplicationsGamesBiomedical signal processingRecommender systems,...

Florian Yger Machine Learning

lamsade

Machine Learning

Human resources

Permanent staff

J. Atif (PU, 100%) - 2014T. Cazenave (PU, 50%) - 2009Y. Chevaleyre (PU, 100%) - 2017R. Laraki (DR, 20%) - 2013B. Negrevergne (MCF, 100%) - 2016F. Yger (MCF, 100%) - 2015

Florian Yger Machine Learning

lamsade

Machine Learning

Human resources

International collaborations with: Google Brain NY, Riken AIP, KU Leuven, etc

Florian Yger Machine Learning

lamsade

Machine Learning

Human resources

Non-permanent staffM. Cornu (2013 - , MESR)F. Labernia (2014-2017, MESR)S. Hadikhanloo (2014 - , AD/CEREMADE)A. Morvan (2015 - , CEA)C. Béji (2016 - , MESR)B. Doux (2017 - , MESR)R. Pinot (2017 - , CEA)Y. Laurin (2017 - , ENS)S. Nicolet (2017 - , PRAG)P. Meriguet (2017 - , Cifre Smith detection/CEREMADE)A. Araujo (2017 - , Cifre Wavestone)N. Carion (2017 - , Cifre Facebook)T. Sohm-Quéron (2017 - , Cifre Brabham gardens)K. Osanlou (2017 - , Cifre Safran)G. Sileno (2016 - , postdoc fellow)M. Bon (2017 - , industrial associate)

Florian Yger Machine Learning

lamsade

Machine Learning

Human resources

Selection of thesis topicsF. Labernia, Modelisation, learning and preference prediction,(J. Atif)C. Beji, Uplift modelling and causal inference, (J. Atif, F. Yger)R. Pinot, Online sketching of structured data for machinelearning under differential privacy, (J. Atif, F. Yger)A. Araujo, Dynamical optimization of machine learningapplications, (J. Atif, B. Negrevergne)B. Doux, Detecting and understanding salient events in videogame data, (T. Cazenave, B. Negrevergne)S. Hadikhanloo, Learning in Mean Field Games, (R. Laraki)

Florian Yger Machine Learning

lamsade

Machine Learning

Other resources

Academic projects:national level

ANR Logima (2014-2017), 72 Keuros, Partner, Consortium:TPT, ECP, Univ. Dauphine.ANR ESIGMA (2017-2021), 141Keuros, Partner, Consortium:École polytechnique, Dauphine, Univ. Montpellier.PEPS-JCJC ADDICTED (2017), 10Keuros

international levelANR STAP (2017-2021, 137K), Partner, Consortium: TPT,Univ. Dauphine, IME Brazil

Industrial projects:Adway (2015-2016) (2017- ) 25Keuros/yearCIFRE (Brabham gardens, Facebook, Safran, Smith detection,Wavestone)CEA (thesis fundings)

Florian Yger Machine Learning

lamsade

Machine Learning

Some achievements

Representation learning

Y. Isaac, Q. Barthélemy, C. Gouy-Pailler, M. Sebag, J. Atif.Multi-dimensional signal approximation with sparse structured priors usingsplit bregman iterations. Signal Processing, 2017.

M. Bojarski, A. Choromanska, K. Choromanski, F. Fagan, C. Gouy-Pailler,A. Morvan, N. Sakr, T. Sarlos, J. Atif. Structured adaptive and randomspinners for fast machine learning computations. In AISTATS 2017.

A. Lecoutre, B. Negrevergne, F. Yger. Recognizing Art StyleAutomatically in painting with deep learning, ACML, 2017

Selection among 20 international journal articles and38 international conference articles.

Florian Yger Machine Learning

lamsade

Machine Learning

Some achievements

Learning and decision under uncertainty

T. Cazenave. Generalized rapid action value estimation. IJCAI, 2015.

J. Flesch, R. Laraki, V. Perchet. Online learning and blackwellapproachability in quitting games. COLT 2016.

B. Negrevergne, T. Cazenave. Distributed nested rollout policy for samegame. In Computer Games Workshop at IJCAI. 2017.

Selection among 20 international journal articles and38 international conference articles.

Florian Yger Machine Learning

lamsade

Machine Learning

Some achievements

Representation to cope with non-stationarity /changing contexts

F. Labernia, B. Zanuttini, B. Mayag, F. Yger, J. Atif. Online learning ofacyclic conditional preference networks from noisy data, IEEE ICDM2017.

T. Cazenave. Residual networks for computer go. IEEE Transactions onComputational Intelligence and AI in Games, 2017.

I. Horev, F. Yger, and M. Sugiyama. Geometry-aware stationary subspaceanalysis. ACML, 2016.

Selection among 20 international journal articles and38 international conference articles.

Florian Yger Machine Learning

lamsade

Machine Learning

Perspectives and scientific challenges

Summaryrecent project in rapid expansion,great quality and quantity of international collaborations andpublications.

Participation to society’s next challengesincorporation of privacy constraintsexplainability of the decisions

Directions for 2017-2022reinforcement of the transversality of the projectwithin LAMSADE, Dauphine, PSLcapitalization on the existing collaborations (national andinternational)

Florian Yger Machine Learning