Zoltán Szabó: Data Science Seminar organizer. The time information is meant in London sense. Francesca Panero has joined the organizing board (Sept., 2022).

Marco Scutari. Achieving fairness with a simple ridge penalty.
[abstract, slides; 2pm-, June 12]

Marta Blangiardo. Can we use spatio-temporal wastewater data to battle COVID-19?
[abstract; 2pm-, May 15]

Yeganeh Alimohammadi. The Power of a Few Local Samples for Predicting Epidemics.
[abstract, slides; 4pm-, Mar. 27]

Patrick Loiseau. Statistical discrimination in selection and matching.
[abstract, slides; 2pm-, Mar. 20]

Erwan Scornet. Is interpolation benign for random forests?
[abstract, slides; 2pm-, Feb. 27]

David Ginsbourger. On Gaussian Process multiple-fold cross-validation.
[abstract, slides; 2pm-, Jan. 30]

Anastasia Borovykh. Towards explainable and privacy-preserving machine learning.
[abstract, slides; 2pm-, Nov. 21]

Vladimir Vovk. Applications of e-values to multiple hypothesis testing.
[abstract, slides; 2pm-, Nov. 14]

Caroline Uhler. From Interventions to Causality using Over-Parameterized Neural Networks.
[abstract, slides; 2pm-, Oct. 17]

Florence d'Alché-Buc. Learning to predict complex outputs: a kernel view.
[abstract, slides; 2pm-, June 13]

Lester Mackey. Kernel Thinning and Stein Thinning.
[abstract, slides; 2pm-, May 30]

Rémi Flamary. Modeling Graphs with Optimal Transport.
[abstract, slides; 2pm-, May 23]

Krishnakumar Balasubramanian. Unified RKHS Methodology and Analysis for Functional Linear and Single-Index Models.
[abstract, slides; 4pm-, May 16]

Dino Sejdinovic. Recent Developments at the Interface Between Kernel Embeddings and Gaussian Processes.
[abstract, slides; 2pm-, Mar. 7]

Silvia Villa. Iterative regularization for low complexity regularizers.
[abstract, slides; 2pm-, Feb. 21]

Volkan Cevher. Optimization challenges in adversarial machine learning.
[abstract; 2pm-, Feb. 14]

Joseph Salmon. Implicit differentiation for fast hyperparameter selection in non-smooth convex learning.
[abstract, slides; 2pm-, Feb. 7]

Cynthia Rudin. Scoring Systems: At the Extreme of Interpretable Machine Learning.
[abstract, slides; 2pm-, Jan. 31]

Negar Kiyavash. Database alignment: fundamental limits and efficient algorithms.
[abstract; 1pm-, Dec. 6]

Vitaliy Kurlin. Mathematical Data Science for solid crystalline materials.
[abstract, slides; 2pm-, Nov. 22]

Po-Ling Loh. A modern take on Huber regression.
[abstract, slides; 3:30pm-, Nov. 15]

Suvrit Sra. Do we understand how to find critical points in nonsmooth optimization?
[abstract; 3pm-, Nov. 8]

Rada Mihalcea. TextRank: Bringing Order Into Texts (Revisited).
[abstract; 2pm-, Oct. 18]