Searching and Sorting Algorithms (part 4 of 4)
Introductory coverage of basic searching and sorting algorithms, as well as a rudimentary overview of Big-O algorithm analysis. Part of a larger series teaching programming at http://codeschool.org
From playlist Searching and Sorting Algorithms
Function Comparision - 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
From playlist Algorithms 1
PMSP - Computational pseudo-randomness and extractors II - Russell Impagliazzo
Russell Impagliazzo Institute for Advanced Study June 14, 2010 For more videos, visit http://video.ias.edu
From playlist Mathematics
Niv Buchbinder: Deterministic Algorithms for Submodular Maximization Problems
Randomization is a fundamental tool used in many theoretical and practical areas of computer science. We study here the role of randomization in the area of submodular function maximization. In this area most algorithms are randomized, and in almost all cases the approximation ratios obtai
From playlist HIM Lectures 2015
Find the Shortest Path - 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
Probabilistic Numerics — moving BayesOpt expertise to the inner loop by Philipp Hennig
A Google TechTalk, presented by Philipp Hennig, 2022/02/08 ABSTRACT: BayesOpt Speaker Series. Bayesian Optimization experts are Gaussian process experts. And there is much more to do for Gaussian inference in the algorithmic space beyond outer-loop optimization. Using simulation — the solu
From playlist Google BayesOpt Speaker Series 2021-2022
ML Tutorial: Probabilistic Numerical Methods (Jon Cockayne)
Machine Learning Tutorial at Imperial College London: Probabilistic Numerical Methods Jon Cockayne (University of Warwick) February 22, 2017
From playlist Machine Learning Tutorials
Build a Heap - 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
ML Tutorial: Probabilistic Dimensionality Reduction, Part 1/2 (Neil Lawrence)
Machine Learning Tutorial at Imperial College London: Probabilistic Dimensionality Reduction, Part 1/2 Neil Lawrence (University of Sheffield) March 11, 2015
From playlist Machine Learning Tutorials
Fellow Short Talks: Dr Charles Sutton, Edinburgh University
Charles Sutton is a Reader (equivalent to Associate Professor: http://bit.ly/1W9UhqT) in Machine Learning at the University of Edinburgh. He has over 50 publications in a broad range of applications of probabilistic machine learning. His work in machine learning for software engineering ha
From playlist Short Talks
Nonlinear Independent Component Analysis - Aapo Hyvärinen
Seminar on Theoretical Machine Learning Topic: Nonlinear Independent Component Analysis Speaker: Aapo Hyvärinen Affiliation: University of Helsinki Date: August 4, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
Semantic models for higher-order Bayesian inference - Sam Staton, University of Oxford
In this talk I will discuss probabilistic programming as a method of Bayesian modelling and inference, with a focus on fully featured probabilistic programming languages with higher order functions, soft constraints, and continuous distributions. These languages are pushing the limits of e
From playlist Logic and learning workshop
On The Complexity of Circuit Satisfiability - Ramamohan Paturi
Ramamohan Paturi University of California at San Diego October 12, 2009 We present a gap theorem regarding the complexity of the circuit satisfiability problem. We prove that the success probability of deciding Circuit Satisfiability for deterministic circuits with n variables and size m
From playlist Mathematics
Seminar on Applied Geometry and Algebra (SIAM SAGA): Sonja Petrović
Date: Tuesday, January 12, 2021 at 11:00am EST (5:00pm CET) Speaker: Sonja Petrović, Illinois Institute of Technology Title: Random Monomial Ideals Abstract: Joint work with Jesus A. De Loera, Lily Silverstein, Despina Stasi, Dane Wilburne. Inspired by the study of random graphs and sim
From playlist Seminar on Applied Geometry and Algebra (SIAM SAGA)
O'Reilly Webcast: Probabilistic Data Structures and Breaking Down Big Sequence Data
Presented by Dr. C. Titus Brown. Many data analysis problems are not easily parallelizable, often because the relevant analyses require an all-by-all analysis step. Applying heuristics often requires approximation, which introduces errors, noise, and bias. Recently, in confronting the sequ
From playlist Strata 2011
Professor Mark Girolami: "Probabilistic Numerical Computation: A New Concept?"
The Turing Lectures: The Intersection of Mathematics, Statistics and Computation - Professor Mark Girolami: "Probabilistic Numerical Computation: A New Concept?" Click the below timestamps to navigate the video. 00:00:09 Introduction by Professor Jared Tanner 00:01:38 Profess
From playlist Turing Lectures
Probabilistic logic programming and its applications - Luc De Raedt, Leuven
Probabilistic programs combine the power of programming languages with that of probabilistic graphical models. There has been a lot of progress in this paradigm over the past twenty years. This talk will introduce probabilistic logic programming languages, which are based on Sato's distrib
From playlist Logic and learning workshop
Martin Lotz: A blind spot in the probabilistic complexity analysis of algorithms
Martin Lotz: A blind spot in the probabilistic complexity analysis of algorithms Abstract: The lecture was held within the framework of the Hausdorff Trimester Program Mathematics of Signal Processing. It is a well-established fact that, in practical settings, iterative numerical algorit
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"