(photo credit: Peter Richtárik)
Zoltán Szabó
Department of Statistics, LSE [local time]
),
grant (
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lecturing (
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organizing (
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paper (
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service (
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software (
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talk (
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TR (
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visit(or) (
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workshop (
).
| June - Aug. |
Service: Senior Area Chair @ NeurIPS-2025
|
| May 6-9 |
Organizing: Uncertainty in multivariate, non-Euclidean, and functional spaces: theory and practice workshop @ Representing, calibrating & leveraging prediction uncertainty from statistics to machine learning (Isaac Newton Institute), with Alessandra Menafoglio, David Ginsbourger, Florence d’Alché-Buc, Judith Rousseau, Neil Lawrence. |
| Apr. 13-16 |
At: DALI-2025
|
| Apr. 7-8 |
Organizing: LSE Statistics Research Showcase
|
| Feb. - Apr. |
Service: AC @ UAI-2025, ICML-2025
|
| Winter Term (Feb. 10) |
Lecturing: Foundations of Machine Learning: Kernel Methods
|
| Jan. 22 |
Paper: 'Nyström Kernel Stein Discrepancy' accepted at AISTATS-2025 [paper (arXiv)] = Nyström-based accelerated computation of kernel Stein discrepancy (KSD); convergence rate of the classical quadratic-time KSD & the Nyström KSD estimator |
| Winter Term (Jan. - Apr.) |
Lecturing: Graph Data Analytics and Representation Learning
|
| Nov. - Dec. |
Service: Senior Area Chair @ AISTATS-2025
|
| Nov. 27 |
TR: Keep it Tighter – A Story on Analytical Mean Embeddings [paper (arXiv)] = tighter concentration of semi-explicit MMD estimation in 1d, minimax lower bound for the unbounded exponential kernel, 3 financial applications |
| Sept. 27 |
Lecturing (mini-course): Linux – The Operating System of Freedom [abstract, slides] |
| Sept. 25 |
Paper: 'The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels' accepted at NeurIPS-2024 [paper, paper (arXiv)] = minimax rate for HSIC estimation on Rd |
| Aug. 28 |
Paper: 'Random Fourier Signature Features' @ SIAM Journal on Mathematics of Data Science [paper, paper (arXiv), code] = large-scale, GPU-accelerated signature kernel estimators |
| June - Aug. |
Service: Senior Area Chair @ NeurIPS-2024
|
| July 3 |
TR: To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learning [paper (arXiv)] = flexible policy switching framework for offline RL, balancing between long-term return maximization and the cost of switching |
| July 1 |
TR: Forward and Backward State Abstractions for Off-policy Evaluation [paper (arXiv), code] = two-step procedure for dimensionality reduction in off-policy evaluation |
| June 20-21 |
Organizing: LSE Statistics Research Showcase
|
| June - |
Service: DTS Management Board
|
| June 13 |
TR: Nyström Kernel Stein Discrepancy [paper (arXiv), code] = Nyström-based accelerated computation of kernel Stein discrepancy |
| June 11 |
Grant: LSE Global Research Fund,
joint work with Bharath Sriperumbudur &
Florian Kalinke.
|
| Mar. - Apr. |
Service: AC @ ICML-2024, SPC @ COLT-2024
|
| Mar. 13 |
TR: The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels [paper, paper (arXiv)] = minimax rate for HSIC estimation on Rd |
| Feb. - Apr. |
Service: AC @ UAI-2024
|
| Feb. 12 |
Talk @ Computer Science Colloquium, University of Warwick [abstract, slides] |
| Winter Term |
Lecturing: Graph Data Analytics and Representation Learning
|
| Winter Term (Feb. 5) |
Lecturing: Foundations of Machine Learning: Support Vector Machines
|
| Jan. - | Start working with Tao Ma (PhD student) |
| Dec. 18 |
Talk @ CMStatistics-2023: Economic Data Analysis and Statistical Inference to Unfold Uncertainty session [slides] |
| Dec. 17 |
Talk @ CMStatistics-2023: Statistical Machine Learning with Kernels and Non-linear Transformations session [slides] |
| Dec. 16 |
Talk @ CMStatistics-2023: Advances in Kernel Methods and Gaussian Processes session [slides] |
| Nov. 22 |
TR: Random Fourier Signature Features [paper (arXiv), code] = large-scale, GPU-accelerated signature kernel estimators |
| Nov. - Dec. |
Service: Senior Area Chair @ AISTATS-2024
|
| Sept. 22 |
Lecturing (mini-course): Linux – The Operating System of Freedom [abstract, slides] |
| Sept. 21 |
Paper: 'Kernelized Cumulants: Beyond Kernel Mean Embeddings' @ NeurIPS-2023 [paper (NeurIPS), paper (arXiv), spotlight, poster, code] = higher-degree generalization of MMD and kernel Lancaster interaction; applications: environmental and traffic data analysis |
| Sept. - | Working with Xiaoyi Wen (visiting PhD student) |
| Sept. - |
Service: Turing Academic Liaison
|
| Jun. - Aug. |
Service: Area Chair @ NeurIPS-2023
|
| June 26-30 |
Talk @ Lifting Inference with Kernel Embeddings (LIKE23) [slides] |
| June 10-14 |
Plenary Talk @ ACDL-2023 [slides-1, slides-2] |
| June 5-6 |
Organizing: LSE Statistics Research Showcase
|
| May 23 |
Lecturing (mini-course): Linux – The Operating System of Freedom [slides] |
| May 8 |
Paper: 'Nyström M-Hilbert-Schmidt Independence Criterion' @ UAI-2023 [paper, paper (UAI), supplement (UAI), paper (arXiv), code] = consistent estimation of HSIC for ≥ 2 components using the Nyström technique; applications: weather causal discovery, dependency testing of media annotations |
| Mar. - Apr. |
Service: SPC @ COLT-2023, AC @ ICML-2023, UAI-2023
|
| Mar. 2- |
Service: Senior Associate Editor @ ACM Transactions on Probabilistic Machine Learning
|
| Feb. 20 |
TR: Nyström M-Hilbert-Schmidt Independence Criterion [paper (arXiv), code] = consistent estimation of HSIC for ≥ 2 components using the Nyström technique |
| Jan. 31 |
TR: Kernelized Cumulants: Beyond Kernel Mean Embeddings [paper (arXiv), code] = higher-degree generalization of MMD and HSIC; applications: environmental and traffic data analysis |
| Lent Term |
Lecturing: Graph Data Analytics and Representation Learning
|
| Nov. - Dec. |
Service: Senior Area Chair @ AISTATS-2023
|
| Oct. 26 |
Paper: @ JMLR [paper, paper (JMLR), code] = hard affine SDP shape constraints in vector-valued RKHSs; applications: shape optimization, safety-critical control, robotics, econometrics |
| Oct. - Dec. |
Service: Area Chair @ ICLR-2023
|
| Michaelmas Term |
Lecturing: Artificial Intelligence
|
| Sept. 29 |
Talk @ CGO Seminar [abstract, slides] |
| Sept. 21 |
Talk @ Data Science Research Lightning Talks event (DSI) [slides] |
| Sept. 8 |
Talk @ BIRS workshop on New Interfaces of Stochastic Analysis and Rough Paths [abstract, slides] |
| Sept. - Dec. | Working with Florian Kalinke (visiting PhD student) |
| Sept.- |
Service: Programme Director of MSc Data Science
|
| Sept. | Welcome to & start working with Sakina Hansen (PhD student ) and Pingfan Su (PhD student) |
| July 28 |
TR: Handling Hard Affine SDP Shape Constraints in RKHSs (extended and simpler proof, new application in robotics) [paper (arXiv)] = hard affine SDP shape constraints in vector-valued RKHSs; applications: shape optimization, robotics, econometrics |
| Jun. - Aug. |
Service: Area Chair @ NeurIPS-2022
|
| June 23 |
Paper: 'Discussion of `Multiscale Fisher's Independence Test for Multivariate Dependence'' @ Biometrika [paper (arXiv), paper (Biometrika)] |
| June 14-15 |
Organizing: LSE Statistics Research Showcase
|
| June 4 |
Talk @ EcoSta [abstract, slides] |
| May 26 |
Talk @ DataSig Seminar [abstract, slides] |
| May 14 |
Paper: 'Functional Output Regression with Infimal Convolution: Exploring the Huber and Epsilon-Insensitive Losses'
accepted @ ICML-2022 [paper, paper (arXiv), code, presentation (video)] = functional output regression with sparsity-inducing and robust loss; applications: neuroimaging, speech analysis |
| Apr. - May |
Service: Area Chair @ UAI-2022
|
| Feb. - Apr. |
Service: Area Chair @ ICML-2022
|
| Mar. - Apr. |
Service: SPC @ COLT-2022
|
| Jan. 26 |
Talk @ Gatsby Unit [abstract, slides] |
| Jan. 12 |
Talk @ Lifting Inference with Kernel Embeddings (LIKE22)
winter school and workshop [slides] |
| Dec. 19 |
Talk @ CMStatistics-2021 [abstract, slides] |
| Dec. 13 |
Talk @ Data Science Institute [slides] |
| Nov. - Dec. |
Service: Area Chair @ AISTATS-2022
|
| Oct. - Dec. |
Service: Area Chair @ ICLR-2022
|
| Nov. 4 |
Talk @ Data Science Seminar at Eurecom [abstract, slides] |
| Oct. 20 |
TR: Kernel Minimum Divergence Portfolios [paper (arXiv)] = analytic mean embeddings, better concentration of the resulting MMD estimators, portfolio optimization |
| Oct. 14 |
Talk @ LSE Statistics Open House [slides-1, slides-2] |
| Oct.- |
Organizing: Data Science Seminars (local-, departmental archive)
|
| Sept.- |
Service: DSI Management Committee
|
| Michaelmas Term |
Lecturing: Artificial Intelligence
|
| Sept. | Starting at LSE! |
| June - Sept. |
Service: Area Chair @ NeurIPS-2021
|
| Aug. 31 |
At: Linda's PhD defense
|
| July 8 |
Talk @ EUROPT-2021 [slides] |
| July 7 |
At: Alex's PhD defense
|
| July 5 |
At: Pierre-Cyril's PhD defense
|
| May 20 (morning) |
Talk @ LIS, Aix-Marseille University [abstract, slides] |
| May 18-21 |
At: RESIM-2021
|
| Mar. 24 |
Lecturing: Mini-Course on Independence Measures and Testing
|
| Mar. - Apr. |
Service: Area Chair @ ICML-2021
|
| Mar. - Apr. |
Service: SPC @ UAI-2021 &
COLT-2021
|
|
Service: reviewing grants @ Israel Science Foundation (ISF)
|
|
| Mar. 4 |
Talk @ Department of Statistics, LSE
|
| Feb. - Mar. |
Service: Area Chair @ IJCAI-2021
|
| Feb. 12 |
Talk @ Texas A&M University: Department of Statistics [abstract, slides] |
| Feb. 4 |
TR: Emotion Transfer Using Vector-Valued Infinite Task Learning [paper, paper (arXiv), demo (video), code] = emotion/style transfer with operator-valued kernels |
| Jan. 6-8 |
Organizing: I am Program Chairing DS3-2020 (postponed to Jan 2021 due to COVID-19)
|
| Jan. 6 |
TR: Handling Hard Affine SDP Shape Constraints in RKHSs [paper (arXiv), paper (HAL)] = hard affine SDP shape constraints in vector-valued RKHSs; applications: shape optimization, safety-critical control, econometrics |
| Dec. 15 |
Talk @ Meeting on Mathematical
Statistics (MMS) [abstract, slides] |
| Dec. 6-12 |
At: NeurIPS-2020 [paper, slides, spotlight video, code] |
| Nov. - Dec. |
Service: Area Chair @ AISTATS-2021
|
| Nov. 30 - Dec. 1 |
Organizing: StressTest-2020 workshop
with Stefano De Marco and
Emmanuel Gobet
|
| Oct. - Nov. |
Service: Area Chair @ ICLR-2021
|
| Sept. 25 |
Paper: 'Hard Shape-Constrained Kernel Machines' accepted @ NeurIPS-2020 [paper, paper (NeurIPS), paper (arXiv), paper (HAL), slides, code] = SVMs with hard affine shape constraints on derivatives; applications: joint quantile regression, economics, analysis of aircraft trajectories |
| Sept.- |
Organizing: I have joined to the organizing board of the
Statistics Seminars (CREST-CMAP).
|
| Sept. 7 |
Talk @ SMAI-MODE (Pierre-Cyril) [abstract, slides] |
| June - Aug. |
Service: Area Chair @ NeurIPS-2020
|
| July 27-31 |
Poster: 'Hard Shape-Constrained Kernel Regression' @ SPIGL [abstract, poster] |
| July 11-17 |
Talk @ IFAC-WC (Pierre-Cyril) [slides, talk (video)] |
| July 14-15 |
Service: Newcomers' Mentoring @ ICML-2020
|
| June- |
Service: Editorial Board Member @ JMLR
|
| June 11 |
Paper: Orlicz Random Fourier Features @ JMLR [paper, JMLR: paper, HAL: paper] = tight uniform guarantees for random Fourier features under mild conditions for arbitrary order derivatives |
| May 27 |
TR: Hard Shape-Constrained Kernel Machines [arXiv: paper; HAL: paper] = SVMs with hard affine shape constraints on derivatives |
| May 18 - Aug. 18 | Welcome to & start working with Bechir Trabelsi (M.Sc. intern). |
| Apr. 23- |
Organizing: SIMPAS Group Meeting
|
| Apr. 6 |
Grant: Europlace Institute of Finance (EIF),
joint work with Dino Sejdinovic &
Olivier Derollez.
|
| Apr. 1 |
Service: Recruitment Committee Member (M.Sc. @ Data Science for Business)
|
| Mar. - Apr. |
Service: SPC @ UAI-2020
|
| Feb. - Apr. |
Service: Area Chair @ ICML-2020
|
| Feb. - Mar. |
Service: SPC @ IJCAI-2020
|
| Mar. 5 |
Talk @ ML journal club [slides] |
| Feb. 27 |
Paper: 'Kernel Regression for Vehicle Trajectory Reconstruction under Speed and Inter-vehicular Distance Constraints'
accepted @ IFAC World Congress (IFAC WC) [paper] = application of shape-constrained SVMs for trajectory reconstruction from noisy GPS measurements |
|
Service: External reviewer of Luigi Carratino's PhD thesis
|
|
| Jan. 30 |
Paper: 'Kernel Regression with Hard Shape Constraints' accepted @ SMAI-MODE 2020 [slides] |
| Jan 21 |
Talk @ D. E. Shaw Group
|
| Jan 9-11 |
Talk @ International Conference on Modern Mathematical Methods and High Performance Computing in Science & Technology (M3HPCST-2020) [abstract, slides] |
| Dec. 29- |
Service: Associate Editor @ Mathematical Foundations of Computing
|
| Dec. 26-30 |
Talk @ International Indian Statistical Association Conference (IISA-2019) [abstract, slides] |
| Dec 20 |
TR: Orlicz Random Fourier Features [paper; HAL: paper] = fast uniform approximation of arbitrary-order kernel derivatives with random Fourier features under mild (alpha-exponential Orlicz spectrum) assumption |
| Dec. 16 | HDR with distinction. |
| Nov. 19 |
At: Workshop on Regularisation for Inverse Problems and Machine Learning
|
| Nov. - Dec. |
Service: Area Chair @ AISTATS-2020
|
| Sept. 23 |
Talk @ EPFL [abstract, slides] |
| Sept. 2-5 |
At: DALI-2019 (San Sebastian, Spain) [poster] |
| July - Aug. |
Service: Senior Area Chair @ NeurIPS-2019
|
| July 15-17 |
Lecturing @ Summer School on
Data Science for Document Analysis and Understanding [slides] |
| July 11-13 |
Talk @ Gatsby 21st Birthday Symposium [slides] |
| June 24-28 |
Organizing: I am Program Chairing DS3-2019.
|
| June 19-23 |
Talk @ Third International Conference on Mathematics of Data Science
(MathoDS 3) [abstract, slides, code] |
| June 9-15 |
At: ICML-2019 [paper, slides, poster, code] |
| May 30- |
Service: arXiv Statistics Advisory Committee Member
|
| May 29 |
Paper: 'A Functional Extension of Multi-Output Learning' will be presented @ AMTL-2019 [paper] |
| May 28-29 |
At: Stress Test Workshop
|
| May 27 |
Service: Recruitment Committee Member (M.Sc. @ Data Science for Business)
|
| May 17 |
Paper: 'Infinite Task Learning in RKHSs' will be presented @ CAp-2019
|
| May 7 & 10 |
Lecturing: Data for Management Certificate @ HEC Paris
|
| Apr. 22 |
Paper: 'MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means' accepted @ ICML-2019 [preprint on arXiv: paper] = new MMD and mean embedding estimators: with optimal sub-Gaussian rate & excessive resistance to contamination |
| Apr. 16-18 |
At: AISTATS-2019 [paper-1, poster-1, paper-2, poster-2] |
| Apr. 15 |
Talk @ RIKEN AIP workshop [abstract, slides, code] |
| Apr. |
Service: reviewer @ SPARS-2019 & ICANN-2019
|
| Mar. 25 - July 31 |
Service: referent professor @ Nicolas Bonnet's internship, Atos India.
|
| Spring |
Lecturing: Advanced Machine Learning
|
| Spring |
Lecturing: Structured Data: Learning, Prediction, Dependency, Testing
|
| Mar. - Apr. |
Service: SPC @ IJCAI-2019
|
| Mar. 7 |
Visitor: Guillaume Perrin is
visiting us and gives an external seminar.
|
| Feb. - Mar. |
Service: Area Chair @ ICML-2019
|
| Feb. 15 |
At: PASADENA workshop [slides] |
| Feb. 12 - Mar. 12 |
Service: For one month I also serve (in addition to stat.ML) as the cs.LG moderator on arXiv, replacing Thomas Dietterich.
|
| Feb. 8 |
Service: Recruitment Committee Member (M.Sc. @ Data Science for Business)
|
| Feb. 7 |
Visitor: Anne Sabourin is
visiting us and gives an external seminar.
|
| Jan. - Feb. |
Service: Program Committee Member @
ICML-2019 workshops
|
| Jan. 3-5 |
At: DALI-2019 [poster] |
| Dec. 23 |
Paper: 2 papers accepted @ AISTATS-2019 [preprints on arXiv: paper-1, paper-2] |
| Dec. 19 | I am being interviewed to the film Mind (topic: AI & Brain). |
| Dec. 2-8 |
At: NeurIPS-2018
|
| Nov. 29, Dec. 13; Jan. 10 (2019) |
Visitor: Stéphane Girard is
visiting us and gives a mini course.
|
| Nov. 21 |
Service: Recruitment Committee Member (M.Sc. @ Data Science for Business)
|
| Oct. - Dec. |
Service: SPC @ AISTATS-2019
|
| Fall |
Lecturing: Statistics
|
| Fall |
Lecturing: Introduction to Machine Learning
|
| Oct. 31 |
Visitor: Lilian Besson is visiting us and gives a seminar.
|
| Oct. 26 |
Talk @ Statistical Seminar in Rennes [abstract, slides] |
| Oct. 11 |
TR: On Kernel Derivative Approximation with Random Fourier Features [arXiv: paper, HAL: paper] = random Fourier features can be as efficient for kernel derivative approximation as for kernel values; tool: unbounded empirical processes |
| Oct. |
Service: reviewer @ CiML-2018
|
| Sept. - Oct. |
Service: reviewer @ ICLR-2019
|
| Sept. 17-20 |
At: Polish-Italian Mathematical Conference: Challenges and Methods of Modern Statistics [abstract, slides] |
| Sept. 10 |
Service: Committee Member @ X-HEC (M.Sc.): internship defense
|
| Sept. 4 |
Talk @ B.Sc. Day at CMAP [slides] |
| Aug. 30 |
Paper: Infinite-Task Learning: accepted @ JDSE-2018 [paper, poster, slides] |
| Aug. 28- |
Service: I am the moderator of statistical machine learning (stat.ML) on arXiv.
|
| Aug. 2 |
Paper: Characteristic and Universal Tensor Product Kernels @ JMLR [paper] = characterization of when HSIC is an independence measure |
|
Service: reviewing grants @ European Research Council (ERC)
|
|
| June - Aug. |
Service: Area Chair @ NIPS-2018
|
| July 18 & 20 |
Lecturing @ Summer School on Data Science for Document Analysis and Understanding [slides] |
| July 10-15 |
At: ICML-2018
|
| June 25 |
Paper: Characteristic and Universal Tensor Product Kernels (accepted to JMLR). [paper; arXiv: paper, HAL: paper; +details @ Aug. 2] |
| June 25-29 |
Organizing: I am Program Chairing DS3-2018.
|
| June 19 |
Visitor: Subhadeep Mukhopadhyay is visiting us and gives a seminar.
|
| June |
Service: reviewer @ Cambridge University Press
|
| June 11-15 |
At: Conference of the International Society for Non-Parametric Statistics (ISNPS) [abstract-1, slides-1; abstract-2, slides-2] |
| June 5 |
Visitor: Martin Wainwright is visiting us and gives a seminar.
|
| May 28 - June 1 |
At: JdS-2018 [slides] |
| May. 24 |
TR: Infinite-task learning with vector-valued RKHSs [arXiv: paper, HAL: paper; code] = learning continuum number of tasks jointly; examples: cost-sensitive classification, joint quantile regression, density level set estimation; tool: operator-valued kernels. |
| May 17-20 |
At: Hangzhou International Conference on Frontiers of Data Science [abstract, slides] |
| Apr. 10 |
Visitor: Claire Monteleoni is visiting us and gives a seminar.
|
| Apr. 3-5 |
At: DALI-2018 [poster] |
| Apr. | Welcome to & start working with Meyer Scetbon (M.Sc. intern). |
| March |
Service: reviewer @ COLT-2018
|
| Mar. 23 |
Talk @ Sertis (Wittawat) [slides] |
| Mar. 22 |
Service: Committee Member @ M.Sc. defense: Statistical Models in Biology and Physics.
|
| Mar. 13-14 |
At: PGMO lecture series by Sébastien Bubeck on Bandit Convex Optimization
|
| Mar. 6 |
Visitor: Alessandro Rudi is visiting us and gives a seminar.
|
| Mar.- | Member of the French Statistical Society (SFdS) |
| Feb. - Mar. |
Service: Area Chair @ ICML-2018
|
| Feb. 28 |
Talk @ Laboratory for Information and Inference Systems, EPFL [abstract, slides] |
| Feb. 26 |
Talk @ Machine Learning & Computational Biology Lab, D-BSSE, ETH Zürich [slides] |
| Feb. 20 |
Workshop: Workshop on Functional Inference and Machine Intelligence [slides, code] |
| Feb. 14 |
TR: MONK – Outlier-Robust Mean Embedding Estimation by Median-of-Means [arXiv: paper, HAL: paper] = consistent outlier-robust mean embedding & MMD estimation, with optimal rates. |
| Feb. 13 |
Talk @ Tao Seminar, INRIA Saclay [abstract, slides] |
| Feb. 2 |
At: CentraleSupélec & ICM workshop
|
| Jan. 24 | Interview at TWiML & AI (YouTube, SoundCloud) on our NIPS-2017 Best Paper Award is up. |
| Jan. 23 |
Visitor: Marco Cuturi is visiting us and gives a seminar.
|
| Jan. | Welcome to & start working with Linda Chamakh (PhD). |
| Spring |
Lecturing: Structured Data: Learning, Prediction, Dependency, Testing
|
| Spring |
Lecturing: Advanced Machine Learning
|
| Dec. 11-15 |
Visit @ Department of Statistics, Pennsylvania State University.
Talk: slides
|
| Dec. 4-9 |
At: NIPS-2017. Our submission got one of the 3 Best Paper Awards! (out of 3240 submissions) [paper, paper (NIPS website), poster, slides, talk (video), slides @ MLTrain workshop, interview at TWiML & AI (YouTube, SoundCloud), code] = adaptive linear-time nonparametric goodness-of-fit test |
| Dec. 8 |
Organizing: Learning on Distributions, Functions, Graphs and Groups workshop @ NIPS-2017.
|
| Dec. 1 |
Talk @ Google Brain, Mountain View [abstract, slides] |
| Nov. - Dec. |
Service: Area Chair @ AISTATS-2018
|
| Nov. 29 |
Visit @ Department of Statistics, Columbia University
|
| Nov. 28 |
Talk @ Advanced Methods Group, Cubist Systematic Strategies [abstract, slides] |
| Nov. 28 |
Talk @ Yahoo Research, New York [abstract, slides] |
| Nov. 27 |
Guest Lecturing @ Machine Learning Department, Carnegie Mellon University. [slides, course] |
| Nov. 14 |
At: Random matrix advances in large dimensional statistics and machine learning day
|
| Nov. 3 |
Talk @ Research Seminar, SfS, ETH Zürich [abstract, slides] |
|
Service: reviewing grants @ Swiss National Science Foundation (SNF)
|
|
| Oct. - Nov. |
Service: reviewer @ ICLR-2018
|
| Oct. 11 |
At: Le Cam Data Science Colloquium @ EDF Lab, Paris-Saclay
|
| Oct. 9 |
Talk @ CREST Statistics Seminar, ENSAE [abstract, slides] |
| Oct. | Welcome to & start working with Gaspar Massiot (postdoc), Romain Brault (postdoc), Alex Lambert (PhD student), Moussab Djerrab (PhD student). |
| Sept. 27 |
Service: Committee Member @ Data Science Master: internship defense (École Polytechnique - morning, Télécom ParisTech - afternoon)
|
| Sept. 9 |
Organizing: Our Learning on Distributions, Functions, Graphs and Groups workshop proposal with Florence,
Krikamol & Bharath @ NIPS-2017
got accepted.
|
| Sept. 4-5 |
Service: Committee Member @ Data Science Master: internship defense
|
| Sept. 4 |
Paper: A Linear-Time Kernel Goodness-of-Fit Test. to appear @ NIPS-2017 , see 'Dec. 4-9'. |
| Aug. 28 - Sept. 1 |
Organizing: I am Program Chairing DS3-2017.
|
| Aug 28 |
TR: Characteristic and Universal Tensor Product Kernels [arXiv: paper, HAL: paper] |
| Aug 9 |
Paper @ ICML-2017 [slides, poster; further details @ 'May 12'] |
| July 27 |
Lecturing @ Summer School on Mathematical and Computational Methods for Life Sciences [slides] |
| July 14-17 |
At: Greek Stochastics Workshop - Model Determination; details @ 'Apr. 17' [slides] |
| July 3-7 |
Visitor: Bharath Sriperumbudur is visiting us and gives seminars.
|
| July 3 |
Service: PhD committee member @ Romain Brault's defense
|
| June - July |
Service: reviewer @ NIPS-2017
|
| June 28 |
Workshop: UCL Workshop on the Theory of Big Data [abstract, slides, code] |
| June 22-23 |
Visitor: Barnabás Póczos is visiting us and gives seminars.
|
| June 21 |
Visitor: Florence d'Alché-Buc & Romain Brault
are visiting us and give seminars.
|
| June 19-20 |
At: Structured Regularization Summer School
|
| June 14 |
At: Le Cam Data Science Colloquium @ Digiteo LABS
|
| May - June |
Service: SPC @ UAI-2017
|
| May 22 |
TR: A Linear-Time Kernel Goodness-of-Fit Test [arXiv: paper, HAL: paper; code] = adaptive linear-time nonparametric goodness-of-fit test |
| May 17 |
Talk @ Télécom ParisTech: PASADENA Seminar [abstract, slides, code] |
| May 12 |
Paper: An Adaptive Test of Independence with Analytic Kernel Embeddings [paper, paper (ICML website), preprint on arXiv; code] accepted @ ICML-2017 = adaptive linear-time nonparametric independence test |
| May 9 |
At: ParisBD-2017
|
| May 4 |
Talk @ Machine learning journal club [slides] |
| Apr. - May |
Service: Area Chair @ ICML-2017
|
| Apr. 24 - Sept. 29 |
Service: referent professor @ Camille Jandot's internship
|
| Apr. 27 |
Visitor: Kirthevasan Kandasamy is visiting us & gives a seminar.
|
| Apr. 17-20 |
At: DALI-2017 [poster] |
| Apr. 17 |
Workshop: A Fast Goodness-of-Fit Test with Analytic Kernel Embeddings [abstract, code] accepted @ Greek Stochastics Workshop - Model Determination |
| Apr. 11 |
Visitor: David Lopez-Paz is visiting us & gives a seminar.
|
| March |
Service: reviewer @ COLT-2017
|
| Mar. 29 |
Visitor: Ming Yuan is visiting us & gives a seminar.
|
| Mar. 27 |
Talk @ Henri Poincaré Institute: Parisian Statistics Seminar [abstract, slides, code] |
| Mar. 24 |
Talk @ Marseilles: Signal Processing and Machine Learning Seminar [abstract, slides, code] |
| Mar. 16 |
Talk @ Orsay: Probability and Statistics Seminar [abstract, slides, code] |
| Spring |
Lecturing: Structured Data: Learning, Prediction, Dependency, Testing
|
| Feb. 27 |
Grant: Labex DigiCosme, joint work with Florence d'Alché-Buc & Arthur Tenenhaus
|
| Feb. 24 |
Workshop: Probabilistic Graphical Model Workshop [slides, code] |
| Feb. 2 |
Talk @ Télécom ParisTech: Machine Learning Seminar [abstract, slides, code] |
| Feb.- |
Organizing: Machine learning journal club
|
| Jan. 31 |
Visitor: Lorenzo Rosasco is visiting us & gives a seminar.
|
| - Jan. |
Service: SPC @ AISTATS-2017
|
| Dec. 3-11 |
At:
NIPS-2016: our 3-minute spotlight video, slides, poster, code; workshop
|
| Nov. 27 - Dec. 2 |
At: New Directions for Learning with Kernels and Gaussian Processes Dagstuhl Seminar [slides, code, Dagstuhl report] |
| Nov. 22 |
Talk @ CMAP seminar [abstract, slides, code] |
| Nov. 21 |
Talk @ Facebook AI Research [abstract, slides, code] |
| Nov. 18 |
Software: ITE in Python released. = several information theoretical estimators |
| Oct. 18 |
TR: An Adaptive Test of Independence with Analytic Kernel Embeddings [paper, code] |
| Oct. 5 |
Talk @ 'Statistics with coffee' seminar [slides] |
| Fall |
Lecturing: Functional Data Analysis
|
| Sept. 29 |
Paper: Learning Theory for Distribution Regression [paper, code] appeared @ JMLR = minimax optimal regression on probability distributions |
| Sept. | Starting at École Polytechnique! |
|
Organizing: Adaptive and Scalable Nonparametric Methods in ML workshop
@ NIPS-2016
|
|
| Aug. 24 |
Talk @ Realeyes [slides, code] |
| Aug. 12 |
Paper: Interpretable Distribution Features with Maximum Testing Power [paper, 3-minute spotlight video, poster, code] to appear @ NIPS-2016 (full oral paper = top 1.84%) = adaptive linear-time nonparametric two-sample test |
| July 10 |
Workshop: Kernel methods for adaptive Monte Carlo [abstract, slides] presented @ Greek Stochastics Workshop on Big Data and Big Models = kernel based fast sampling from Bayesian posteriors (big data regime) |
| June 29 |
Workshop: eResearch Domain launch event (London) [poster] |
| June 22 |
Talk @ PRNI-2016 [abstract, slides] |
| June 11-16 |
At:
ISNPS-2016; details @ 'Mar. 17'
|
| May 6 |
Workshop: Distinguishing Distributions with Interpretable Features [paper, spotlight, poster, code] accepted @ ICML-2016: Data-Efficient ML |
| Apr. 25 |
Talk @ UCSD [slides, code] |
|
Service: SPC @ UAI-2016
|
|
| Mar. 17 |
Workshop: Minimax-Optimal Distribution Regression [abstract, slides, code] accepted @ ISNPS-2016 |
| Mar. 16 |
Talk @ MPI, Tübingen: Special Symposium on Intelligent Systems [abstract, slides, code] |
| Mar. 14 |
Talk @ École Polytechnique [abstract, slides] |
| Mar. 9 |
Talk @ Imperial College London [abstract, slides] |
