Zoltán Szabó: machine learning journal club @ CMAP, mini courses / external talks (Chair Stress Test; 2018, Nov.-). The event takes place every 2nd week (2020, Apr. 23-) in turn with the SIMPAS group meeting.
| Date | Presenter | Title | Paper |
|---|---|---|---|
| Apr. 15 | Margaux Zaffran | Conformalized Quantile Regression | paper |
| Apr. 1 | Costanza Tortú | Machine learning algorithms tailored for causal inference studies | |
| Mar. 18 | Marc Chataigner | Nowcasting Networks | paper |
| Feb. 18 | Charu Shardul | A Reinforcement Learning approach for mean-variance portfolio selection problem | link1, link2 |
| Feb. 4 | David Métivier | A mean field view of the landscape of two-layer neural networks | paper |
| Date | Presenter | Title | Paper |
|---|---|---|---|
| Nov. 26 | Bouazza Saadeddine | Deep XVAs | |
| Nov. 12 | Linda Chamakh | Statistical Optimal Transport posed as Learning Kernel Mean Embedding | paper |
| Oct. 15 | Costanza Tortú | Heterogeneous Treatment and Spillover Effects Under Clustered Network Interference | paper |
| July 23 | Linda Chamakh | Portfolio Optimization: Distribution Targeting with Kernel-based Divergence | |
| July 9 | David Barrera | Efficient Parameter Estimation of Sampled Random Fields | paper |
| June 25 | Bouazza Saadeddine | Probabilistic Line Searches for Stochastic Optimization | paper |
| June 11 | Marc Chataigner | Deep Local Volatility | paper |
| May 14 | Wei Jiang | Integrating multi-source block-wise missing data in model selection | paper |
| Mar. 5 | Zoltán Szabó (me) | Shape-Constrained Estimation in Reproducing Kernel Hilbert Spaces | paper |
| Apr. 30 | Michael Allouche | Variational Autoencoder: a Bayesian Approach for Generative Models with Neural Networks | paper |
| Apr. 16 | Maud Thomas (external seminar) | Concentration Results in Extreme Value Theory | |
| Apr. 9 | Bouazza Saadeddine | Gradient Boosting Neural Networks: GrowNet | paper |
| Apr. 2 | Anne Sabourin (external talk) | Exploratory analysis for high dimensional extremes: Support identification, Anomaly detection, Principal component analysis | |
| Mar. 19 | Chiara Amorino (external seminar) | Invariant adaptive density estimation for ergodic SDE with jumps over anisotropic classes | |
| Mar. 12 | Hideatsu Tsukahara (external talk) | Mini course on 'Statistics of Risk Measures: Estimation and Backtesting' | |
| Mar. 9 | Hideatsu Tsukahara (external talk) | A copula approach to spatial econometrics with applications to finance | |
| Feb. 27 | Dorinel Bastide (external talk) | Calculation of Credit Provision to CCP Exposures Using Expected Loss Approach | |
| Feb. 27 | Cyril Benezet | Deep Learning Approximations of Stochastic Control Problems and PDEs in High Dimension | paper (link-1), paper (link-2) |
| Feb. 13 | James Brice Scoggins | Uniformly accurate machine learning-based hydrodynamic models for kinetic equations | paper (link-1), paper (link-2) |
| Jan. 30 | Bruno Loureiro (external talk) | Are Generative Models the New Sparsity? |
| Date | Presenter | Title | Paper |
|---|---|---|---|
| Nov. 28 | Siragan Gailus (external talk) | Homogenization and Fluctuations for Diffusions with Standard and Fractional Brownian Motion | |
| Nov. 28 | Linda Chamakh | How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network? | paper |
| Nov. 21 | Jerome Stenger (external talk) | Optimal Uncertainty Quantification of a Risk Measurement on a Moment Class | |
| Nov. 21 | Alex Lambert | Learning function-valued functions in RKHSs: application to integral losses | |
| Nov. 7 | Gwladys Toulemonde (external talk) | Stochastic modelling and simulation of extreme rainfalls | |
| Nov. 7 | Bouazza Saadeddine | Multi-Task Learning as Multi-Objective Optimization | paper |
| Oct. 24 | Rodrigo Targino (external talk) | Understanding the Economic Policy Uncertainty Index Using Semi-Automatic News Classification | |
| Oct. 24 | Michael Allouche | Enriching Financial Datasets with GAN | paper |
| Oct. 17 | Rodrigo Targino (external talk) | Elements of risk management and the allocation problem | |
| Oct. 10 | Pierre-Cyril Aubin-Frankowski | Finding Mixed Nash Equilibria of Generative Adversarial Networks | paper, supplement |
| Oct. 3 | Philippe Durand (external talk) | Financial Crisis and its Evaluation | |
| June 13 | Clément Dombry (external talk) | The coupling method in extreme value theory | |
| June 13 | Imke Mayer: homepage, LinkedIn | Invariant Causal Prediction for Nonlinear Models | paper |
| June 6 | Marcos Carreira | Learning Interest Rate Interpolation | |
| May 16 | Kaitong Hu | Mean field Langevin dynamic and its applications to neural network | |
| May 9 | Antoine Usseglio-Carleve (external talk) | Estimation of conditional extreme risk measures from heavy-tailed elliptical random vector | paper |
| May 9 | Linda Chamakh | On the Margin Theory of Feedforward Neural Networks | paper |
| Apr. 24 & 25 | Jean-David Fermanian (external talk) | Copulas | |
| Apr. 4 | Arnaud Guyader (external talk) | Introduction to rare event simulation methods | |
| Apr. 4 | Bouazza Saadeddine | Online natural gradient as a Kalman filter | paper |
| Mar. 28 | Frédéric Loge Munerel | Deep Knockoffs | paper |
| Mar. 21 | Gildas Mazo (external talk) | An optimal balance between explorations and repetitions in sensitivity analysis | |
| Mar. 14 | Marc Chataigner | How well can generative adversarial network learn densities : A nonparametric view | paper |
| Mar. 7 | Guillaume Perrin (external talk) | Exploiting code structure for statistical learning | |
| Mar. 7 | Aude Sportisse | Variational Inference for Stochastic Block Models from Sampled Data | paper |
| Feb. 21 | James Brice Scoggins | The Power of Deeper Networks for Expressing Natural Functions | paper |
| Feb. 14 | Wei Jiang | A Modern Maximum-Likelihood Theory for High-dimensional Logistic Regression | paper |
| Feb. 7 | Anne Sabourin (external talk) | Binary Classification in Extreme Regions | paper |
| Jan. 31 | David Barrera | Two strong consistency theorems for nonparametric regression over independent samplings | paper |
| Jan. 24 | Geneviève Robin | Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues | paper |
| Jan. 10 | Stéphane Girard (external talk) | Mini course on 'Introduction to extreme-value analysis' (part-3) |
| Date | Presenter | Title | Paper |
|---|---|---|---|
| Dec. 13 | Stéphane Girard (external talk) | Mini course on 'Introduction to extreme-value analysis' (part-2) | |
| Dec. 13 | Imke Mayer: LinkedIn, homepage | Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications | paper, supplement |
| Dec. 6 | Rémi Besson | Safe and Efficient Off-Policy Reinforcement Learning | paper |
| Nov. 29 | Stéphane Girard (external talk) | Mini course on 'Introduction to extreme-value analysis' (part-1) | |
| Nov. 29 | Nicolas Prost | GAIN: Missing Data Imputation using Generative Adversarial Nets | paper |
| Nov. 22 | Kaitong Hu | Mean Field Analysis of Neural Networks | paper |
| Nov. 8 | Othmane Mounjid | Gradient Descent Provably Optimizes Over-parameterized Neural Networks | paper |
| Oct. 25 | Aude Sportisse | Why are Big Data Matrices Approximately Low Rank? | paper |
| Oct. 18 | Frédéric Loge Munerel | Bias and variance approximation in value function estimates | paper |
| Oct. 11 | Giulio Gori | New Approaches in Turbulence and Transition Modeling Using Data-driven Techniques | paper |
| Sept. 27 | Francois Sanson | Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling | DOI |
| June 14 | Juliette Chevallier | A Bayesian mixed-effects model to learn trajectories of changes for repeated manifold-valued observations | paper |
| June 7 | Frédéric Loge Munerel | A Distributional Perspective on Reinforcement Learning | paper, supplement |
| May 24 | Jaouad Mourtada | Progressive mixture rule are deviation suboptimal | paper |
| Apr. 26 | Geneviève Robin | Optimal algorithms for smooth and strongly convex distributed optimization in networks | paper, supplement |
| Apr. 5 | Maryan Morel | Determinantal point processes for machine learning | paper |
| Mar. 15 | Cédric Rommel | Soft-DTW: a Differentiable Loss Function for Time-Series | paper |
| Mar. 8 | Belhal Karimi | A Universal Catalyst for First-Order Optimization | paper |
| Feb. 22 | Manon Michel | Understanding deep learning requires rethinking generalization | paper |
| Date | Presenter | Title | Paper |
|---|---|---|---|
| Nov. 23 | Alain Virouleau | Online rules for control of False Discovery Rate and False Discovery Exceedance | link |
| Nov. 16 | Othmane Mounjid | Rainbow: Combining Improvements in Deep Reinforcement Learning | link |
| Nov. 9 | Kaitong Hu | Solving Imperfect Information Games Using Decomposition. Regret Minimization in Games with Incomplete Information | paper |
| Oct. 26 | Martin Royer | Adaptive Clustering through Semidefinite Programming (NIPS preview) | link |
| Oct. 19 | Gaspar Massiot | Influence Function and Robust Variant of Kernel Canonical Correlation Analysis | link |
| Oct. 12 | Rémi Besson | Failures of Gradient-Based Deep Learning | link-1, link-2 |
| Oct. 5 | Elodie Vernet | Uncertainty Quantification for the Horseshoe | link |
| Sept. 28 | Wei Jiang | The Stochastic Topic Block Model for the Clustering of Vertices in Networks with Textual Edges | link-1, link-2 (arXiv) |
| Sept. 21 | Marcos Carreira | Discovering Latent Network Structure in Point Process Data | link |
| July 6 | Bharath Sriperumbudur (external talk) | Statistical Consistency of Kernel PCA with Random Features | link |
| June 29 | Frédéric Loge Munerel | The statistical performance of collaborative inference | link |
| June 22 | Barnabás Póczos (external talk) | Density Functional Estimation | |
| June 8 | Martin Bompaire (on LinkedIn, ResearchGate) | ASAGA: Asynchronous Parallel SAGA | paper, supplement |
| June 1 | Wei Jiang | Post-selection inference for l1-penalized likelihood models | link-1, link-2 (arXiv) |
| May 23 | Gustaw Matulewicz | Lasso, fractional norm and structured sparse estimation using a Hadamard product parametrization. | link |
| May 18 | Massil Achab (on LinkedIn, ResearchGate) | Operator Variational Inference | link |
| May 11 | David Barrera | Online Learning with Markov Sampling. | link |
| May 4 | Zoltán Szabó (me) | Examples are not enough, learn to criticize! Criticism for Interpretability | link |
| Apr. 27 | Kirthevasan Kandasamy (external talk) | Bandit Optimisation with Approximations | link1, link2, link3 |
| Apr. 13 | Nicolas Brosse | Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling | link |
| Apr. 6 | Joon Kwon | Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization | link |
| Mar. 23 | Alain Virouleau | Panning for gold: Model-free knockoffs for High-dimensional controlled variable selection | link |
| Mar. 16 | Jaouad Mourtada | Second-Order Quantile Methods for Experts and Combinatorial Games | link |
| Mar. 9 | Geneviève Robin | Random matrix theory in statistics: A review | link |
| Mar. 2 | Joon Kwon | An Ultimate Unification of Gradient and Mirror Descent (aka "Nesterov's acceleration: the simplest proof ever") | link |
| Feb. 23 | Cédric Rommel | A Consistent Regularization Approach for Structured Prediction | link |
| Feb. 16 | Belhal Karimi | Consistent Kernel Mean Estimation for Functions of Random Variables | link |