Previous Seminars
Adversarial Training Should Be Cast as a Non-Zero-Sum Game
Volkan Cevher - Associate Prof. EPFL, Switzerland
Spectral Methods and Generative Modeling: A Unifying Perspective
Jiaxin Shi - Research Scientist, DeepMind, UK
Robust and Conjugate Gaussian Process Regression
François-Xavier Briol - Associate Prof., UCL, UK
Non-linear Latent Force Models
Mauricio Álvarez - Senior Lecturer, Univ. of Manchester, UK
Addressing Bias and Copyright in Generative AI: Preference Matching and Fair Compensation
Weijie Su - Professor, University of Pennsylvania
Conservation Laws for Gradient Flows
Gabriel Peyré - CNRS researcher| DMA/ENS, France
Physics-informed machine learning as a kernel method
Francis Bach - Researcher at Inria
Learning Dynamics of Overparametrized Neural Networks
René Vidal - Rachleff University Professor, University of Pennsylvania, USA
Causal Effect Estimation with Context and Confounders
Arthur Gretton - Professor, UCL, UK
Robust and Efficient AI Alignment
Ilija Bogunovic - Assistant Professor, UCL, UK
Multi-objective optimization with societal considerations: a study of RCTs in the presence of competing treatments
Ana-Andreea Stoica - Research Group Leader in the Social Foundations of Computation Department, Max Planck Institute, Germany
Resurrecting Recurrent Neural Networks
Razvan Pascanu - Research Scientist, Google DeepMind, UK
Models That Prove Their Own Correctness
Orr Paradise - PhD student at the Theory of Computation group at UC Berkeley, UK
Theoretical Foundations Of Self Consuming Generative Models
Josey Bose - Postodoctoral Fellow, University of Oxford, UK
Subtractive Mixture Models: Representation, Learning and Inference
Dr. Antonio Vergari - Reader (Associate Professor), University of Edinburgh
Optimal Tuning of Hamiltonian Monte Carlo on ReLU-based Neural Networks
Dr. Cuong V. Nguyen - Assistant Professor, Durham University
Beyond the curse of dimensionality with hyper-kernel ridge regression
Prof. Lorenzo Rosasco - Professor, Universita' di Genova/MIT
Quantifying and Estimating Epistemic Uncertainty in LLMs through Iterative Prompting
Ilja Kuzborskij - Research Scientist, Google DeepMind
Feature Learning and computational limitations in learning with multi-index models
Dr. Bruno Loureiro - ENS/CNRS
Learning Dynamics in Multiplayer Games
Tatjana Chavdarova - Visiting Professor in the Department of Electronics, Information, and Bioengineering (DEIB) at Politecnico di Milano (Polimi)
Generalization for Diffusion Models: An Algorithmic-Dependent Framework Based on Stability
Patrick Rebeschini - Professor of Statistics and Machine Learning, University of Oxford, UK
Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning
Changchun Chi - Associate professor, London School of Economics and Political Science, UK
Variational Uncertainty Decomposition for In-Context Learning
Yingzen Li - Senior Lecturer, Imperial College, UK
Differentially private M-estimation via noisy optimization
Po-Ling Loh - Professor, University of Cambridge UK
Learning in the Age of LLMs: Theoretical Insights into Knowledge Distillation and Test-Time-Training
Marco Mondelli - Professor, Institute of Science and Technology, Austria
Learning with Nonlinear Expectations
Dr. Krikamol Muandet - Chief scientist and Tenure-track Faculty (fast track) at CISPA
Learning a Stackelberg Leader's Incentives from Optimal Commitments
Dr. Yurong Chen - Postdoc at INRIA, Paris
Imprecise Probabilistic Machine Learning -- Being Precise about Imprecision
Dr. Michele Caprio - Lecturer (Assistant Professor) at The University of Manchester