Mutual feedback on ICML papers.
Catch up meeting.
Seminar, unusual day! Erik.
Reading group. Qi Qian, Hao Li, Juhua Hu: “Efficient Kernel Transfer in Knowledge Distillation”. [Paper]
Seminar. Peter, Thomas. Uncertainty estimation for Bayesian Neural Networks using infinite-width nets.
Pre-ICLR paper discussion.
Reading group. Ben Recht: “A Tour of Reinforcement Learning: The View from Continuous Control”. [Paper]
Team work review for the past 4 months. Siddarth’s talk on functional regularization on the memorable past. [Paper]
Unusual day and time! Dimitri Meunier: “Meta Learning meets Variational Inference. Learning priors with guarantees”.
Feedback discussion on the new team webpage.
Show all reading group meetings
Research chat and virtual breakfast/lunch/dinner in gather.town.
Siddharth Swaroop: A survey on federated learning.
Lab members project overview and discussion.
Pierre’s grant presentation rehearsal and feedback.
Reading group. “Gradient descent for wide two-layer neural networks”. [Blog post]
Reading group. “Generalized Variational Inference: Three arguments for deriving new posteriors”. [Paper]
Reading group. “On the measure of intelligence”. [Paper]
Whole week: comments on ICML tutorials and talks.
Pre-ICML paper discussion.
Talk by Evgenii Egorov. “Involutive MCMC: one way to derive them all”. [Paper]
Talk by Giulia Denevi on Efficient Lifelong Learning Algorithms: Regret Bounds and Statistical Guarantees.
Internal kickoff meeting.
Talk by Peter Nickl on “Variational Bayes for Infinite Mixtures of Local Regressors with Robotics Applications”. [Thesis]
Feedback discussion on our NeurIPS submissions.
Talk by Evgenii Egorov on MaxEntropy Pursuit Variational Inference. [Paper]
Reading Group. “Continual Deep Learning by Functional Regularisation of the Memorable Past”. [Paper]
Reading Group. Shalev-Shwartz: “Introduction to online learning”, Chapter 2 (end). [Paper]
Reading Group. Shalev-Shwartz: “Introduction to online learning”, Chapter 2. [Paper]
Reading Group. Shalev-Shwartz: “Introduction to online learning”, Chapter 1. [Paper]