TFML Talk: The algorithmic foundations of online learning

Title

TFML Talk: The algorithmic foundations of online learning

Speaker

Nicolò Cesa-Bianchi - Università degli Studi di Milano

This talk is part of the TFML PhD School, but open to everyone interested. You can view the full program below.

Abstract

Online Convex Optimization is the mathematical framework underlying the design and analysis of online learning algorithms. In online learning, models are sequentially trained on data streams. For this reason, this paradigm is well suited in applications where new data is being generated all the time. In this tutorial I will describe the main algorithmic tools of online convex optimization, derive mathematical guarantees on their performance, and show connections to other related areas.

Bio

Nicolò Cesa-Bianchi is a professor of Computer Science at Università degli Studi di Milano and holds a joint appointment at Politecnico di Milano. His main research interests are the design and analysis of machine learning algorithms for online learning, sequential decision-making, and graph analytics. He is co-author of the monographs "Prediction, Learning, and Games" and "Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems". He served as President of the Association for Computational Learning and co-chaired the program committees of some of the most important machine learning conferences, including NeurIPS, COLT, and ALT. He is the recipient of a Google Research Award, a Xerox Foundation Award, a Criteo Faculty Award, a Google Focused Award, and an IBM Research Award. He is ELLIS fellow, member of the ELLIS board, and co-director of the ELLIS program on Interactive Learning and Interventional Representations. He is a corresponding member of the Italian Academy of Sciences.

When

Wednesday June 25th, 14:00

Where

Room 509, UniGe DIBRIS/DIMA, Via Dodecaneso 35