Local feature size

Unit 1 - unconstrained optimization part 6

From playlist Courses and Series

JAVA Defining Variable Scope

More videos like this online at http://www.theurbanpenguin.com Understanding variable scope in Java. We take a quick look at Class, Instance and Local variables and see how scope affects their access.

From playlist Java

Determine the Domain of Various Functions

This video explains how to determine the domain of various functions including linear, quadratic, square root, cube root, cubic, absolute value, and rational functions. http://mathispower4u.com

From playlist The Properties of Functions

Find the domain of a function #shorts

From playlist #Shorts

4.3 Maxima and Minima

OpenStax Calculus Volume 1

From playlist Calculus 1

Determine the domain, range and if a relation is a function

👉 Learn how to determine whether relations such as equations, graphs, ordered pairs, mapping and tables represent a function. A function is defined as a rule which assigns an input to a unique output. Hence, one major requirement of a function is that the function yields one and only one r

From playlist What is the Domain and Range of the Function

Using parent graphs to understand the left and right hand limits

👉 Learn how to evaluate the limit of an absolute value function. The limit of a function as the input variable of the function tends to a number/value is the number/value which the function approaches at that time. The absolute value function is a function which only takes the positive val

From playlist Evaluate Limits of Absolute Value

Learn how to evaluate left and right hand limits of a function

👉 Learn how to evaluate the limit of an absolute value function. The limit of a function as the input variable of the function tends to a number/value is the number/value which the function approaches at that time. The absolute value function is a function which only takes the positive val

From playlist Evaluate Limits of Absolute Value

Dynamics in many-body localized system by Soumya Bera

DISCUSSION MEETING NOVEL PHASES OF QUANTUM MATTER ORGANIZERS: Adhip Agarwala, Sumilan Banerjee, Subhro Bhattacharjee, Abhishodh Prakash and Smitha Vishveshwara DATE: 23 December 2019 to 02 January 2020 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Recent theoretical and experimental

From playlist Novel Phases of Quantum Matter 2019

CS231n Lecture 8 - Localization and Detection

ConvNets for spatial localization Object detection

From playlist CS231N - Convolutional Neural Networks

DeepMind x UCL | Deep Learning Lectures | 3/12 | Convolutional Neural Networks for Image Recognition

In the past decade, convolutional neural networks have revolutionised computer vision. In this lecture, DeepMind Research Scientist Sander Dieleman takes a closer look at convolutional network architectures through several case studies, ranging from the early 90's to the current state of t

From playlist Learning resources

Didong Li

From playlist Plenary talks One World Symposium 2020

Deep InfoMax: Learning deep representations by mutual information estimation and maximization | AISC

For more details including paper and slides, visit https://aisc.a-i.science/events/2019-04-11/ Discussion lead/coauthor: Karan Grewal Abstract Building agents to interact with the web would allow for significant improvements in knowledge understanding and representation learning. Howev

From playlist Natural Language Processing

Recommender Systems - Graphs for Recommendation Systems - Session 15

Importance of graphs for recommenders Information from graphs Node2Vec Node2Vec difficulties Graph choices

From playlist Recommenders Systems (Hands-on)

Vadim Gorin: Tilings and non-intersecting paths beyond integrable cases

Abstract: The talk is about a class of systems of 2d statistical mechanics, such as random tilings, noncolliding walks, log-gases and random matrix-type distributions. Specific members in this class are integrable, which means that available exact formulas allow delicate asymptotic analysi

From playlist Probability and Statistics

17b Machine Learning: Convolutional Neural Networks

Accessible lecture on convolutional neural networks. The Python demonstrations are here: - operators demo - https://git.io/JkqV9 - CNN demo - https://git.io/JksEJ I hope this is helpful, Michael Pyrcz (@GeostatsGuy)

From playlist Machine Learning

Finding the smallest and the largest value at the same time. #shorts

From playlist Shorts

John Harer (10/7/14): Topological Data Analysis and Machine Learning

From playlist AATRN 2014

The Frustration of being Odd: Universal area law violation in local systems by Fabio Franchini

PROGRAM: INTEGRABLE SYSTEMS IN MATHEMATICS, CONDENSED MATTER AND STATISTICAL PHYSICS ORGANIZERS: Alexander Abanov, Rukmini Dey, Fabian Essler, Manas Kulkarni, Joel Moore, Vishal Vasan and Paul Wiegmann DATE : 16 July 2018 to 10 August 2018 VENUE: Ramanujan Lecture Hall, ICTS Bangalore

From playlist Integrable​ ​systems​ ​in​ ​Mathematics,​ ​Condensed​ ​Matter​ ​and​ ​Statistical​ ​Physics

Square Root Functions: Domain, Range

Two examples of finding the domain and range for square root functions using graphs and algebra.

From playlist Domain and Range of Functions