Upcoming Events

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Events Archive

Barks, Bubbles and Brownies!

Barks, Bubbles and Brownies!

We will have therapy dogs available to help calm you, bubble tea to hydrate you and brownies to assist with that chocolate fix.

RSVP not necessary but first come, first serve for the bubble tea!

Location: 26 Prospect Ave

Machine Learning for the Sciences

Machine Learning for the Sciences

Taking place every other Friday. Lunch will be provided.

Location: 26 Prospect Ave, Auditorium 103
Tags: ML for the Sciences

Grad Students: Interested in Data Science?

Grad Students: Interested in Data Science?

Center for Statistics and Machine Learning is holding an informal graduate information session about its certificate program.

Lunch will be served!

Location: 26 Prospect Ave

Recent Advances in Non-Convex Distributed Optimization and Learning

Recent Advances in Non-Convex Distributed Optimization and Learning
We consider a class of distributed non-convex optimization problems, in which a number of agents are connected by a communication network, and they collectively optimize a sum of (possibly non-convex and non-smooth) local objective functions. This type of problem has gained some recent popularities, especially in the application of distributed...
Location: B205 Engineering Quadrangle
Speaker(s):
Mingyi Hong
University of Minnesota
Tags: CSML Seminar Series

Diving into TensorFlow 2.0

Diving into TensorFlow 2.0

Description: Please join us for this 90-minute workshop, taught at an intermediate level. We will briefly introduce TensorFlow 2.0, then dive in to writing a few flavors of neural networks. Attendees will need a laptop and an internet connection.

Location: Lewis Science Library 138
Speaker(s):
Josh Gordon
Google
Diving in to TensorFlow 2.0
Tags: Research Computing Workshop

Can learning theory resist deep learning?

Can learning theory resist deep learning?
Machine learning algorithms are ubiquitous in most scientific, industrial and personal domains, with many successful applications. As a scientific field, machine learning has always been characterized by the constant exchanges between theory and practice, with a stream of algorithms that exhibit both good empirical performance on real-world...
Location: CS 105
Speaker(s):
Francis Bach
INRIA
Tags: CSML Seminar Series

Machine Learning for the Sciences

Machine Learning for the Sciences

Taking place every other Friday. Lunch will be provided.

Location: 26 Prospect Ave, Auditorium 103
Tags: ML for the Sciences

Convergence Rates of Stochastic Algorithms in Nonsmooth Nonconvex Optimization

Convergence Rates of Stochastic Algorithms in Nonsmooth Nonconvex Optimization
Stochastic iterative methods lie at the core of large-scale optimization and its modern applications to data science. Though such algorithms are routinely and successfully used in practice on highly irregular problems (e.g. deep neural networks), few performance guarantees are available outside of smooth or convex settings. In this talk, I will...
Location: B205 Engineering Quadrangle
Speaker(s):
Dmitriy Drusvyatskiy
University of Washington
Convergence Rates of Stochastic Algorithms in Nonsmooth Nonconvex Optimization
Tags: CSML Seminar Series

Exploration by Optimization in Partial Monitoring

Exploration by Optimization in Partial Monitoring

In many real-world problems learners cannot directly observe their own rewards but can still infer whether some particular action is successful. How should a learner take actions to balance its need of information while maximizing their reward in this setting? Partial monitoring is a framework introduced a few decades ago to model learning...

Location: Sherrerd 101
Speaker(s):
Csaba Szepesvari
Professor of Computing Science, University of Alberta
Tags: CSML Seminar Series

Randomized Methods for Low-Rank Tensor Decomposition in Unsupervised Learning

Randomized Methods for Low-Rank Tensor Decomposition in Unsupervised Learning
Tensor decomposition discovers latent structure in higher-order data sets and is the higher-order analogue of the matrix decomposition.
Location: 214 Fine Hall
Speaker(s):
Tamara Kolda
Sandia National Laboratories
Tags: CSML Seminar Series

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