Optimization algorithms and methods
The Bregman-Lagrangian framework permits a systematic understanding of the matching rates associated with higher-order gradient methods in discrete and continuous time. (Wikipedia).
Meditation, violin, by Maria Lan
Jan 31, 2015. Maria Lan Bressan
From playlist Music by Maria Lan Bressan
Haim Brezis - 21 September 2016
Brezis, Haim "Another triumph for De Giorgi’s Gamma convergence"
From playlist A Mathematical Tribute to Ennio De Giorgi
Maria Lan Bressan, Piano performance in Padova, Italy
Maria Lan Bressan, 1st prize winner of the International Piano Competition " Premio Città di Padova ", (category B), Padova, Italy, June 2014. Performing Beethoven and Berkovic piano solo pieces.
From playlist Music by Maria Lan Bressan
Stanley Osher: "Compressed Sensing: Recovery, Algorithms, and Analysis"
Graduate Summer School 2012: Deep Learning, Feature Learning "Compressed Sensing: Recovery, Algorithms, and Analysis" Stanley Osher, UCLA Institute for Pure and Applied Mathematics, UCLA July 20, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/graduate-summe
From playlist GSS2012: Deep Learning, Feature Learning
Dynamical, symplectic and stochastic perspectives on optimization – Michael Jordan – ICM2018
Plenary Lecture 20 Dynamical, symplectic and stochastic perspectives on gradient-based optimization Michael Jordan Abstract: Our topic is the relationship between dynamical systems and optimization. This is a venerable, vast area in mathematics, counting among its many historical threads
From playlist Plenary Lectures
Lagrange Bicentenary - Jacques Laskar's conference
Lagrange and the stability of the Solar System
From playlist Bicentenaire Joseph-Louis Lagrange
Michael Jordan: "Optimization & Dynamical Systems: Variational, Hamiltonian, & Symplectic Perspe..."
High Dimensional Hamilton-Jacobi PDEs 2020 Workshop II: PDE and Inverse Problem Methods in Machine Learning "Optimization and Dynamical Systems: Variational, Hamiltonian, and Symplectic Perspectives" Michael Jordan - University of California, Berkeley (UC Berkeley) Abstract: We analyze t
From playlist High Dimensional Hamilton-Jacobi PDEs 2020
Stanley Osher: "Linearized Bregman Algorithm for L1-regularized Logistic Regression"
Graduate Summer School 2012: Deep Learning, Feature Learning "Linearized Bregman Algorithm for L1-regularized Logistic Regression" Stanley Osher, UCLA Institute for Pure and Applied Mathematics, UCLA July 20, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/g
From playlist GSS2012: Deep Learning, Feature Learning
Bach violin (double) concerto, by Maria Lan
Jan 31, 2015. Maria Lan Bressan
From playlist Music by Maria Lan Bressan
Lieven Vandenberghe: "Bregman proximal methods for semidefinite optimization."
Intersections between Control, Learning and Optimization 2020 "Bregman proximal methods for semidefinite optimization." Lieven Vandenberghe - University of California, Los Angeles (UCLA) Abstract: We discuss first-order methods for semidefinite optimization, based on non-Euclidean projec
From playlist Intersections between Control, Learning and Optimization 2020
Stanley Osher - Variational Methods for Computational Microscopy - IPAM at UCLA
Recorded 14 September 2022. Stanley Osher of the University of California, Los Angeles, presents "Variational Methods for Computational Microscopy" at IPAM's Computational Microscopy Tutorials. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/computational-microscopy-tutor
From playlist Tutorials: Computational Microscopy 2022
Anthony Yezzi: "Accelerated Optimization in the PDE Framework"
High Dimensional Hamilton-Jacobi PDEs 2020 Workshop II: PDE and Inverse Problem Methods in Machine Learning "Accelerated Optimization in the PDE Framework" Anthony Yezzi - Georgia Institute of Technology Institute for Pure and Applied Mathematics, UCLA April 22, 2020 For more informatio
From playlist High Dimensional Hamilton-Jacobi PDEs 2020
What Sparsity and l1 Optimization Can Do For You
Sparsity and compressive sensing have had a tremendous impact in science, technology, medicine, imaging, machine learning and now, in solving multiscale problems in applied partial differential equations. l1 and related optimization solvers are a key tool in this area. The special nature o
From playlist Complete lectures and talks: slides and audio
Bregman persistence homology [Hana Dal Poz Kouřimská]
In this tutorial you will learn about what Bregman Divergences are and how to use them to generalize persistence homology. There are few formulas and lots of pictures :) !!! There is a mistake in the video in the definition of the Bregman divergence (minute 2:08). As the last condition, i
From playlist Tutorial-a-thon 2021 Spring
Vivaldi - Gloria NATIONAL CHAMBER ORCHESTRA OF ARMENIA Art director V. Martirosyan NATIONAL CHAMBER CHOIR OF ARMENIA Art director R. Mlkeyan soprano M. Galoyan soprano H. Harutyunova mezzo-soprano N. Ananikyan conductor R. Mlkeyan http://armchoir.com
From playlist Classical performances
Sebastian Bubeck: Chasing small sets
I will present an approach based on mirror descent (with a time-varying multiscale entropy functional) to chase small sets in arbitrary metric spaces. This could in particular resolve the randomized competitive ratio of the layered graph traversal problem introduced by Papadimitriou and Ya
From playlist Workshop: Continuous approaches to discrete optimization
Maria Lan Bressan playing Mendelssohn violin concert
Studio recital of Max Zorin, June 27, 2019. State College. Maria Lan Bressan playing Mendelssohn violin concert 1st met.
From playlist Music by Maria Lan Bressan