Period of Parent Sine Function
From playlist Trigonometry TikToks
From playlist Trigonometry TikToks
From playlist Trigonometry TikToks
Area of a Regular Polygon: Quick Demo
From playlist Geometry TikToks
[Quiz] Regularization in Deep Learning, Lipschitz continuity, Gradient regularization
Regularization, Lipschitz continuity, Gradient regularization, Adversarial Defense, Gradient Penalty, were all topics of our daily Quiz questions! Tim Elsner @daidailoh (Twitter) jumped in again to do Ms. Coffee Bean’s Job in explaining these concepts that were part of the AI Coffee Break
From playlist AI Coffee Break Quiz question answers
Jean-Pierre Florens: Inverse problems in econometrics - Lecture 2/4
Recording during the thematic month on statistics - Week 2 : "Mathematical statistics and inverse problems" the 9 February, 2016 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide
From playlist Probability and Statistics
Jean-Pierre Florens: Inverse problems in econometrics - Lecture 3/4
Recording during the thematic month on statistics - Week 2 : "Mathematical statistics and inverse problems" the 10 February, 2016 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide
From playlist Probability and Statistics
Structured Regularization Summer School - L. Rosasco - 3/4 - 22/06/2017
Lorenzo Rosasco (Genova and MIT): Regularization Methods for Large Scale Machine Learning Abstract: Regularization techniques originally developed to solve linear inverse problems can be extended to derive nonparametric machine learning methods. These methods perform well in practice and
From playlist Structured Regularization Summer School - 19-22/06/2017
Implicit regularization for general norms and errors - Lorenzo Rosasco, MIT
Implicit regularization refers to the property of optimization methods to bias the search of solutions towards those with some small norm and ensure stability of the estimation process. While this idea is classic when considering Euclidean norms and quadratic error, much less is known for
From playlist Statistics and computation
Deep Learning Lecture 9.3 - Parameter penalization and sharing
Regularization methods: - Penalizing parameter values (L1, L2/weight decay) - Parameter sharing (e.g., ConvNets) - Multitask learning
From playlist Deep Learning Lecture
Iterative regularization via dual diagonal descent - Villa - Workshop 3 - CEB T1 2019
Silvia Villa (Università di Genova) / 01.04.2019 Iterative regularization via dual diagonal descent. In this talk I wlll consider iterative regularization methods for solving linear inverse problems. An advantage of iterative regularization strategies with respect to Tikhonov regulariza
From playlist 2019 - T1 - The Mathematics of Imaging
From playlist Trigonometry TikToks
Jean-Pierre Florens: Inverse problems in econometrics - Lecture 4/4
Recording during the thematic month on statistics - Week 2 : "Mathematical statistics and inverse problems" the 10 February, 2016 at the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide
From playlist Probability and Statistics
Arnaud Münch : Inverse problems for linear PDEs using mixed formulations
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Control Theory and Optimization
Simplify a trig expression by multiplying a cosine
👉 Learn how to simplify trigonometric expressions by factoring, expansion, and re-grouping. To simplify a trigonometric identity means to reduce the identity to the simplest form it can take which may be a number or a simple trigonometric function. This can be achieved by various means i
From playlist How to Simplify Trigonometric Expressions by Multiplying
The mother of all representer theorems for inverse problems & machine learning - Michael Unser
This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data science” — brings together leading researchers in the general fields of mathematics, statistics, computer science and engineering. About the event The workshop ai
From playlist Mathematics of data: Structured representations for sensing, approximation and learning