Upcoming Events

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JARROD MCCLEAN - Google Quantum Artificial Intelligence Lab

JARROD MCCLEAN - Google Quantum Artificial Intelligence Lab
Thu, Sep 30, 2021, 4:00 pm
JARROD MCCLEAN

Google Quantum Artificial Intelligence Lab

Website Jarrod McClean Website

Thursday, Sep. 30, 2021
4:00pm

Zoom Meeting

Host - Haw Yang

More information and abstract forthcoming.

Location: Virtual Seminar
Speaker(s):
JARROD MCCLEAN
Google
TBA
Tags: Featured Event, Seminars

CSML Poster Session Event

CSML Poster Session Event
Mon, May 2, 2022, 8:00 am

The annual CSML Poster Session event will be held in person or virtually. Watch this space for further details.

Published date of event is subject to change.

Due date for independent work posters and papers TBA. Please check your email for details.

Tags: Featured Event, Undergrad Certificate
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Events Archive

Bilevel Learning for Inverse Problems

Bilevel Learning for Inverse Problems
Variational regularization techniques are dominant in the field of inverse problems. A drawback of these techniques is that they are dependent on a number of parameters which have to be set by the user. This issue can be approached by machine learning where we estimate these parameters from data. This is known as "Bilevel Learning" and has been...
Location: https://zoom.us/j/91342019907
Speaker(s):
Matthias Ehrhardt
University of Bath
Tags: Featured Event

Variational models and gradient flows for graph clustering

Variational models and gradient flows for graph clustering
Discrete graph-based variants of the Allen--Cahn and total variation variational models have proven to be successful tools for clustering and classification on graphs. In this talk we will study these models and the gradient flows that are derived from them. We will see deep connections between the various discrete gradient flows as well as...
Speaker(s):
Yves van Gennip
Delft University of Technology
Variational models and gradient flows for graph clustering
Tags: Featured Event

Real-Time Remote Sensing and Fusion Plasma Control: A Reservoir Computing Approach

Real-Time Remote Sensing and Fusion Plasma Control: A Reservoir Computing Approach
Nuclear fusion power is a potential source of safe, non-carbon-emitting and virtually limitless energy. The tokamak is a promising approach to fusion based on magnetic plasma confinement, constituting a complex physical system with many control challenges. However, plasma instabilities pose an existential threat to a reactor, which has not yet...
Location: Virtual
Speaker(s):
Azarakhsh Jalalvand
Ghent University-imec
Real-Time Remote Sensing and Fusion Plasma Control: A Reservoir Computing Approach
Tags: Featured Event, Seminars

Convergence of Stochastic Gradient Descent for analytic target functions

Convergence of Stochastic Gradient Descent for analytic target functions
In this talk we discuss almost sure convergence of Stochastic Gradient Descent in discrete and continuous time for a given twice continuously-differentiable target function F. In a first step we give assumptions on the step-sizes and perturbation size to ensure convergence of the target value F and gradient f=DF assuming that f is locally Hölder-...
Speaker(s):
Sebastian Kassing
University of Münster
Tags: Featured Event

Accelerate Your Code at the Princeton GPU Hackathon, June 2, 8-10, 2021

Accelerate Your Code at the Princeton GPU Hackathon, June 2, 8-10, 2021

Graphics Processing Units (GPUs) offer high performance and massive parallelization, but learning how to program GPUs for scientific applications can be daunting.

Location: Virtual Seminarl
Tags: Featured Event, Special Talks

Smooth bilevel programming for sparse regularisation

Smooth bilevel programming for sparse regularisation
Nonsmooth regularisers are widely used in machine learning for enforcing solution structures (such as the l1 norm for sparsity or the nuclear norm for low rank). State of the art solvers are typically first order methods or coordinate descent methods which handle nonsmoothness by careful smooth approximations and support pruning. In this work, we...
Speaker(s):
Tags: Featured Event, Seminars

Transport information Bregman divergences

Transport information Bregman divergences
In this talk, we talk about a joint intersection between optimal transport and information geometry. We study Bregman divergences in probability density space embedded with the Wasserstein-2 metric. Several properties and dualities of transport Bregman divergences are provided. In particular, we derive the transport Kullback-Leibler (KL)...
Speaker(s):
Wuchen Li
University of South Carolina
Tags: Featured Event

Princeton Research Day 2021

Princeton Research Day 2021
Princeton’s celebration of early-career research and creative work is back in an all-online format.
Tags: Featured Event

The efficiency of kernel methods on structured datasets

The efficiency of kernel methods on structured datasets
Inspired by the proposal of tangent kernels of neural networks (NNs), a recent research line aims to design kernels with a better generalization performance on standard datasets. Indeed, a few recent works showed that certain kernel machines perform as well as NNs on certain datasets, despite their separations in specific cases implied by...
Speaker(s):
Song Mei
Department of Statistics at UC Berkeley
The efficiency of kernel methods on structured datasets
Tags: CSML Seminar Series, Featured Event

CSML Poster Session Event

CSML Poster Session Event

The annual CSML Poster Session event will be held in person or virtually. Watch this space for further details.

Due date for independent work posters and papers TBA. Please check your email for details.

Tags: Featured Event, Undergrad Certificate

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