Search for tag: "data set"

REU presentation Tuesday 7/14/2020

Zoom Recording ID: 96251374359 UUID: z8AUYGlzQ/qWUEvVGtXAJQ== Meeting Time: 2020-07-14T13:47:26Z

From  James Overhiser 17 plays

Milstein Invited Lecture - Keyon Vafa

Zoom Recording ID: 96610307248 UUID: Ulr/E83kRWGGHY19KZmk9A== Meeting Time: 2020-06-25T23:47:07Z

From  Tapan Parikh 56 plays

Milstein Invited Lecture - Josh Blumenstock

Zoom Recording ID: 96610307248 UUID: ZKt8uGHKTia/xxR8qjMqjg== Meeting Time: 2020-06-11T23:48:57Z

From  Tapan Parikh 17 plays

Giles Hooker's Zoom Meeting

From  Giles Hooker 76 plays

ORIE Colloquium, 3/18/2020 - Ashia Wilson

“Variational Perspectives on Machine Learning: Algorithms, Inference, and Fairness”Machine learning plays a key role in shaping the decisions made by a growing number of institutions.…

From  E. Cornelius 178 plays

20191030_CIDA Keynote_Noah Snavely_Reconstructing the 3D World from Images of Everything

From  Matt Gorney 26 plays

20191030_CIDA Presentation_2019 Hatch Grant Awardees.mp4

From  Matt Gorney 7 plays

20191030_CIDA Presentation_2017 Hatch Grant Awardees

From  Matt Gorney 12 plays

Electron Tomography - Practical Aspects

2017 PARADIM SUMMER SCHOOL Practical Tomography Robert Hovden

From  James Overhiser 49 plays

Core Loss EELS, EDX

2017 PARADIM Core loss EELS Lena Kourkoutis

From  James Overhiser 109 plays

CUFF - 201901250 - Greg Morrisett - What is CIS?

From  Marshall Perryman 37 plays

Privacy-Protecting Smart Contracts at Scale -- Noah Johnson

From  Steven Gallow 125 plays

ORIE 9000 Colloquium - Madeleine Udell: Generalized Low Rank Models

Principal components analysis (PCA) is a well-known technique for approximating a data set represented by a matrix by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets…

From  E. Cornelius 5 plays

ORIE Colloquium on 1/29/2015 - Jason Lee: Selective Inference via the Condition on Selection Framework: Applications to Inference After Variable Selection

Selective Inference is the problem of testing hypotheses that are chosen or suggested by the data. Inference after variable selection in high-dimensional linear regression is a common example of…

From  E. Cornelius 5 plays

ORIE Colloquium on 2/4/2014 - John Duchi: Machine Learning: a Discipline of Resource Tradeoffs

Tuesday, February 4, 2014 at 4:15pm Upson Hall, B17 ORIE Colloquium: John Duchi (UC Berkeley) - Machine Learning: a Discipline of Resource Tradeoffs Joint colloquium with Computer Science. How…

From  E. Cornelius 88 plays

CAM Colloquium, 2017-02-10 - Damek Davis: A SMART Stochastic Algorithm for Nonconvex Optimization with Applications to Robust Machine Learning

Abstract: In this talk, we show how to transform any optimization problem that arises from fitting a machine learning model into one that (1) detects and removes contaminated data from the…

From  E. Cornelius 14 plays