Zoltán Szabó: Data Science Seminar organizer (see also our departmental archive). 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]