Ola Svensson: Learning-Augmented Online Algorithms and the Primal-Dual Method
The design of learning-augmented online algorithms is a new and active research area. The goal is to understand how to best incorporate predictions of the future provided e.g. by machine learning algorithms that rarely come with guarantees on their accuracy. In the absence of guarantees, t
From playlist Workshop: Continuous approaches to discrete optimization
17. Complexity: Approximation Algorithms
MIT 6.046J Design and Analysis of Algorithms, Spring 2015 View the complete course: http://ocw.mit.edu/6-046JS15 Instructor: Srinivas Devadas In this lecture, Professor Devadas introduces approximation algorithms in the context of NP-hard problems. License: Creative Commons BY-NC-SA More
From playlist MIT 6.046J Design and Analysis of Algorithms, Spring 2015
Intro to Graph Search Animation - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Find the Strangers - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Lecture with Ole Christensen. Kapitler: 00:00 - Intro To Approximation Theory; 10:00 - Remarks On Vectorspaces In Mat4; 13:30 - Def.: Dense Subset; 19:15 - Dense Subspace Of The Sequence Spaces L^p; 24:45 - Dense Subspace Of The Function Spaces L^p; 35:15 - Weierstrass Approximation Theore
From playlist DTU: Mathematics 4 Real Analysis | CosmoLearning.org Math
Bridge Edges - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Approximating Functions in a Metric Space
Approximations are common in many areas of mathematics from Taylor series to machine learning. In this video, we will define what is meant by a best approximation and prove that a best approximation exists in a metric space. Chapters 0:00 - Examples of Approximation 0:46 - Best Aproximati
From playlist Approximation Theory
Mean Solution - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms
Minimax Approximation and the Exchange Algorithm
In this video we'll discuss minimax approximation. This is a method of approximating functions by minimisation of the infinity (uniform) norm. The exchange algorithm is an iterative method of finding the approximation which minimises the infinity norm. FAQ : How do you make these animatio
From playlist Approximation Theory
NIPS 2011 Sparse Representation & Low-rank Approximation Workshop: Online Spectral...
Sparse Representation and Low-rank Approximation Workshop at NIPS 2011 Invited Talk: Online Spectral Identification of Dynamical Systems by Byron Boots, Carnegie Mellon University
From playlist NIPS 2011 Sparse Representation & Low-rank Approx Workshop
Hanbaek Lyu - Mesoscale reconstruction of images and networks using tensor decomposition
Recorded 28 November 2022. Hanbaek Lyu of the University of Wisconsin-Madison presents "Mesoscale reconstruction of images and networks using tensor decomposition" at IPAM's Multi-Modal Imaging with Deep Learning and Modeling Workshop. Abstract: We provide a unified framework of reconstruc
From playlist 2022 Multi-Modal Imaging with Deep Learning and Modeling
Curiosity, unobserved rewards and function Approximation in RL - Csaba Szepesvari
Workshop on New Directions in Reinforcement Learning and Control Topic: Curiosity, unobserved rewards and function Approximation: On recent progress in building solid foundations for RL Speaker: Csaba Szepesvari Affiliation: DeepMind & University of Alberta Date: November 7, 2019 For mo
From playlist Mathematics
Complexity Coarse - Graining in the Black Hole Information Problem - Netta Engelhardt
IAS It from Qubit Workshop Workshop on Spacetime and Quantum Information Tuesday December 6, 2022 Wolfensohn Hall Engelhardt-2022-12-06
From playlist IAS It from Qubit Workshop - Workshop on Spacetime and Quantum December 6-7, 2022
Lightning Talks - Chi Jin, Lin Yang, Alec Koppel, Karan Singh, Nataly Brukhim
Workshop on New Directions in Reinforcement Learning and Control Topic:Lightning Talks Speaker: Chi Jin, Lin Yang, Alec Koppel, Karan Singh, Nataly Brukhim Date: November 8, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
MFEM Workshop 2022 | Reduced Order Modeling for FE Simulations with MFEM & libROM
The LLNL-led MFEM (Modular Finite Element Methods) project provides high-order mathematical calculations for large-scale scientific simulations. The project’s second community workshop was held on October 25, 2022, with participants around the world. Learn more about MFEM at https://mfem.o
From playlist MFEM Community Workshop 2022
Deep Learning Approaches in Inverse Problems (Lecture 1) by Deep Ray
DISCUSSION MEETING WORKSHOP ON INVERSE PROBLEMS AND RELATED TOPICS (ONLINE) ORGANIZERS: Rakesh (University of Delaware, USA) and Venkateswaran P Krishnan (TIFR-CAM, India) DATE: 25 October 2021 to 29 October 2021 VENUE: Online This week-long program will consist of several lectures by
From playlist Workshop on Inverse Problems and Related Topics (Online)
Rahul Mazumder - Discrete Optimization-aided Structured Learning at Scale - IPAM at UCLA
Recorded 03 March 2023. Rahul Mazumder of the Massachusetts Institute of Technology presents "Discrete Optimization-aided Structured Learning at Scale" at IPAM's Artificial Intelligence and Discrete Optimization Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/ar
From playlist 2023 Artificial Intelligence and Discrete Optimization
Approximation & Estimation | Numbers | Maths | FuseSchool
An approximation is anything that is similar, but not exactly the same as something else. For example, if you were to say a 57 minute journey would take “about an hour”, you would be approximating. A value can be approximated by rounding, usually to a value that it is easier to work with
From playlist MATHS: Numbers
Scott Field - Gravitational Wave Parameter Estimation with Compressed Likelihood Evaluations
Recorded 17 November 2021. Scott Field of the University of Massachusetts Dartmouth presents "Gravitational Wave Parameter Estimation with Compressed Likelihood Evaluations" at IPAM's Workshop III: Source inference and parameter estimation in Gravitational Wave Astronomy. Abstract: One of
From playlist Workshop: Source inference and parameter estimation in Gravitational Wave Astronomy