Computing Limits from a Graph with Infinities
In this video I do an example of computing limits from a graph with infinities.
From playlist Limits
Dominating Sets and Domination Number of Graphs | Graph Theory
A vertex is said to dominate itself and its neighbors. Then, a dominating set of a graph G is a vertex subset S of G such that every vertex in G is dominated by some vertex in S. This means every vertex in G-S is adjacent to some vertex in S. A dominating set of minimum cardinality is a mi
From playlist Graph Theory
👉 Learn all about the Limit. In this playlist, we will explore how to evaluate the limit of an equation, piecewise function, table and graph. We will explore continuity as well as discontinuities such as holes, asymptotes and jumps and how they relate to the limit. We will evaluate the g
From playlist Evaluate Limits from a Graph
Graphing a linear system of linear inequalities
👉 Learn how to graph a system of inequalities. A system of inequalities is a set of inequalities which are collectively satisfied by a certain range of values for the variables. To graph a system of inequalities, each inequality making up the system is graphed individually with the side of
From playlist Solve a System of inequalities by Graphing | Standard Form
Daniel Kral: Parametrized approach to block structured integer programs
Integer programming is one of the most fundamental problems in discrete optimization. While integer programming is computationally hard in general, there exist efficient algorithms for special instances. In particular, integer programming is fixed parameter tractable when parameterized by
From playlist Workshop: Parametrized complexity and discrete optimization
Lecture 9 | Convex Optimization II (Stanford)
Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd concludes his lecture on primal and dual decomposition methods. This course introduces topics such as subgradient, cutting-plane, and ellipsoid method
From playlist Lecture Collection | Convex Optimization
Aaron Sidford: Introduction to interior point methods for discrete optimization, lecture II
Over the past decade interior point methods (IPMs) have played a pivotal role in mul- tiple algorithmic advances. IPMs have been leveraged to obtain improved running times for solving a growing list of both continuous and combinatorial optimization problems including maximum flow, bipartit
From playlist Summer School on modern directions in discrete optimization
Product Rules in Semidefinite Programming - Rajat Mittal
Rajat Mittal March 22, 2010 Semidefinite programming bounds are widely used in combinatorial optimization, quantum computing and complexity theory. The first semidefinite programming bound to gain fame is the so-called theta number developed by Lov\'asz to compute the Shannon capacity of
From playlist Mathematics
Graphing the system of two linear inequalities with two horizontal line
👉 Learn how to graph a system of inequalities. A system of inequalities is a set of inequalities which are collectively satisfied by a certain range of values for the variables. To graph a system of inequalities, each inequality making up the system is graphed individually with the side of
From playlist Solve a System of Inequalities by Graphing
Rico Zenklusen, Vera Traub: Bridging the Gap Between Tree and Connectivity Augmentation
Full title: Bridging the Gap Between Tree and Connectivity Augmentation: Unified and Stronger Approaches The Connectivity Augmentation Problem (CAP) is one of the most basic survivable network design problems. The task is to increase the edge-connectivity of a graph G by one unit by adding
From playlist Workshop: Continuous approaches to discrete optimization
Nexus Trimester - Sudipto Guha (University of Pennsylvania)
Convex Programming in Small Space Sudipto Guha (University of Pennsylvania) March 09, 2016 Abstract: I plan to talk about solving convex programs in small space - focusing on applications in streaming algorithms and distributed computing, in problems such as maximum matching and correlati
From playlist 2016-T1 - Nexus of Information and Computation Theory - CEB Trimester
Nexus Trimester - Mehdi Molkaraie (UPF)
Efficient Monte Carlo Methods for the Potts Model at Low Temperature Mehdi Molkaraie (UPF) March 17, 2016 Abstract: We consider the problem of estimating the partition function of the ferromagnetic q-state Potts model. We propose an importance sampling algorithm in the dual of the normal
From playlist 2016-T1 - Nexus of Information and Computation Theory - CEB Trimester
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
Aaron Sidford: Introduction to interior point methods for discrete optimization, lecture I
Over the past decade interior point methods (IPMs) have played a pivotal role in mul- tiple algorithmic advances. IPMs have been leveraged to obtain improved running times for solving a growing list of both continuous and combinatorial optimization problems including maximum flow, bipartit
From playlist Summer School on modern directions in discrete optimization
How to determine the solution of a system of linear inequalities by graphing
👉 Learn how to graph a system of inequalities. A system of inequalities is a set of inequalities which are collectively satisfied by a certain range of values for the variables. To graph a system of inequalities, each inequality making up the system is graphed individually with the side of
From playlist Solve a System of inequalities by Graphing | Standard Form
Graphing a system of inequalities when one inequality is a vertical boundary line
👉 Learn how to graph a system of inequalities. A system of inequalities is a set of inequalities which are collectively satisfied by a certain range of values for the variables. To graph a system of inequalities, each inequality making up the system is graphed individually with the side of
From playlist Solve a System of Inequalities by Graphing
An SDCA-powered inexact dual augmented Lagrangian method(...) - Obozinski - Workshop 3 - CEB T1 2019
Guillaume Obozinski (Swiss Data Science Center) / 02.04.2019 An SDCA-powered inexact dual augmented Lagrangian method for fast CRF learning I'll present an efficient dual augmented Lagrangian formulation to learn conditional random field (CRF) models. The algorithm, which can be interpr
From playlist 2019 - T1 - The Mathematics of Imaging
Evaluate a limit at infinity with a radical in denominator
👉 We will explore how to evaluate the limit at infinity. When evaluating the limit at infinity or negative infinity we are interested to know where is the graph going right and left. This is also commonly explored as end behavior of the graph. Most of the examples we will look at will incl
From playlist Evaluate Limits at Infinity