Special year seminar - Math

Aug 27 2020

To Be Announced

Speaker: Inderjit Dhillon
3:00pm | Remote Access Only - see link below
Aug 25 2020

To Be Announced

Speaker: Piotr Indyk
12:30pm | Remote Access Only - see link below
Aug 20 2020

To Be Announced

Speaker: Jason Eisner
3:00pm | Remote Access Only - see link below
Aug 18 2020

To Be Announced

Speaker: Li Deng
12:30pm | Remote Access Only - see link below
Aug 13 2020

Latent State Discovery in Reinforcement Learning

Speaker: John Langford
3:00pm | Remote Access Only - see link below
There are three core orthogonal problems in reinforcement learning: (1) Crediting actions (2) generalizing across rich observations (3) Exploring to discover the information necessary for learning. Good solutions to pairs of these problems are fairly well known at this point, but solutions for...
Aug 11 2020

Statistical Learning Theory for Modern Machine Learning

Speaker: John Shawe-Taylor
12:30pm | Remote Access Only - see link below
Probably Approximately Correct (PAC) learning has attempted to analyse the generalisation of learning systems within the statistical learning framework. It has been referred to as a ‘worst case’ analysis, but the tools have been extended to analyse cases where benign distributions mean we can...
Aug 06 2020

A Blueprint of Standardized and Composable Machine Learning

Speaker: Eric Xing
3:00pm | Remote Access Only - see link below
In handling wide range of experiences ranging from data instances, knowledge, constraints, to rewards, adversaries, and lifelong interplay in an ever-growing spectrum of tasks, contemporary ML/AI research has resulted in thousands of models, learning paradigms, optimization algorithms, not...
Aug 04 2020

Nonlinear Independent Component Analysis

Speaker: Aapo Hyvärinen
12:30pm | Remote Access Only - see link below
Unsupervised learning, in particular learning general nonlinear representations, is one of the deepest problems in machine learning. Estimating latent quantities in a generative model provides a principled framework, and has been successfully used in the linear case, e.g. with independent...
Jul 30 2020

Efficient Robot Skill Learning via Grounded Simulation Learning, Imitation Learning from Observation, and Off-Policy Reinforcement Learning

Speaker: Peter Stone
3:00pm | Remote Access Only - see link below
For autonomous robots to operate in the open, dynamically changing world, they will need to be able to learn a robust set of skills from relatively little experience. This talk begins by introducing Grounded Simulation Learning as a way to bridge the so-called reality gap between simulators and...
Jul 28 2020

Generalized Energy-Based Models

Speaker: Arthur Gretton
12:30pm | Remote Access Only - see link below
I will introduce Generalized Energy Based Models (GEBM) for generative modelling. These models combine two trained components: a base distribution (generally an implicit model), which can learn the support of data with low intrinsic dimension in a high dimensional...

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