Supply chain Master Planning and Network Optimization
More info and download - https://www.anylogistix.com/downloads/ This video will show you how to perform a network optimization in anyLogistix. The purpose of ...
anyLogistix
Network Optimization - Min Cost Flow
Dr. Zubair Mohamed
Python project on Optimization - Network Optimization - Solving an airlines optimization problem
https://github.com/tanmoyie/Operations-Research https://www.kaggle.com/tanmoyie/network-optimization-example-airlines ...
Tanmoy IE
Using Excel Solver for Network Optimization
Supply Chain Analytics
Chapter 9 - Network Optimization
Chapter 9 - Network Optimization.
Arthur Salmon
3.4: Linear Regression with Gradient Descent - Intelligence and Learning
In this video I continue my Machine Learning series and attempt to explain Linear Regression with Gradient Descent. My Video explaining the Mathematics of ...
The Coding Train
IBM ILOG LogicNet Plus XE Demo for Network Optimization
This is a demonstration of traditional supply chain network modeling using IBM's ILOG LogicNet Plus XE decision support solution. IBM ILOG LogicNet Plus XE ...
IBMILOGOPTISCM
How to Setup & Solve Linear Programming Transportation Optimization with Excel Solver
excel #solver #minimize Linear Programming - Transportation Problem - Network Problem Please SUBSCRIBE: ...
Matt Macarty
Mod-05 Lec-07 HEN optimization
Process Integration by Dr. B. Mohanty,Department of Chemical Engineering,IIT Roorkee.For more details on NPTEL visit http://nptel.ac.in.
nptelhrd
Webinar: Supply Chain Constraint-based Planning and Network Optimization
anyLogistix is the supply chain analytics tool that enables users to mirror the uniqueness of a supply chain in its digital replica and see how limitations affect ...
anyLogistix
SciPy Beginner's Guide for Optimization
Scipy.Optimize.Minimize is demonstrated for solving a nonlinear objective function subject to general inequality and equality constraints. Source code is ...
APMonitor.com
Matus Telgarsky (UIUC) -- Gradient Descent Aligns the Layers of Deep Linear Networks
MIFODS - Workshop on Non-convex optimization and deep learning Cambridge, US January 27-20, 2019.
MIFODS
Optimization Landscape and Two-Layer Neural Networks - Rong Ge
Seminar on Theoretical Machine Learning Topic: Optimization Landscape and Two-Layer Neural Networks Speaker: Rong Ge Affiliation: Duke University ...
Institute for Advanced Study
Stochastic Gradient Descent, Clearly Explained!!!
Even though Stochastic Gradient Descent sounds fancy, it is just a simple addition to "regular" Gradient Descent. This video sets up the problem that Stochastic ...
StatQuest with Josh Starmer
DIMACS Networking Workshop: Victor Heorhiadi - Simplifying Network Optimization for SDN Deployment
Victor Heorhiadi of the University of North Carolina presents his talk "Simplifying Network Optimization for SDN Deployment" at the DIMACS Workshop on ...
Rutgers University
DIMACS Networking Workshop: Vahab Mirrokni - Network Optimization for Search
Vahab Mirrokni of Google Research presents their his "Network Optimization for Search via Consistent Hashing and Balanced Partitioning" at the DIMACS ...
Rutgers University
Parameter Optimization Loop
How to select the best parameters when training a machine learning model? We could use the parameter optimization loop. Parameter Optimization loop is a ...
KNIMETV
Network Optimization - Maximal Flow
Dr. Zubair Mohamed
How optimization for machine learning works, part 1
Part of the End-to-End Machine Learning School course library at http://e2eml.school See these concepts used in an End to End Machine Learning project: ...
Brandon Rohrer
Network Design - Facility Location & Capacity Allocation Optimization Models
Provides theory and examples about network design. Includes facility location & capacity allocation optimization models. Next video: https://goo.gl/VNEu7G First ...
Dr. Bharatendra Rai
Session 11 Network Optimization Min Cost Flow Model
Charles Noon
Soledad Villar: "Graph neural networks for combinatorial optimization problems"
Machine Learning for Physics and the Physics of Learning 2019 Workshop IV: Using Physical Insights for Machine Learning "Graph neural networks for ...
Institute for Pure & Applied Mathematics (IPAM)
24. Linear Programming and Two-Person Games
MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang View the complete course: ...
MIT OpenCourseWare
Multi-Echelon Inventory Optimization
Multi-echelon takes a bird's eye view of entire supply chain and considers the whole network as a single unit. Through strategically allocating inventories across ...
INFORM GmbH
Resource Allocation in Wireless Networks Under Uncertainties: A Stochastic Optimization Framework
Emerging wireless networks operate using dynamic and uncertain resources that render them susceptible to severe performance degradation. Managing ...
Wireless @ Virginia Tech
Hyperparameter Optimization - The Math of Intelligence #7
Hyperparameters are the magic numbers of machine learning. We're going to learn how to find them in a more intelligent way than just trial-and-error. We'll go ...
Siraj Raval
Networking in UE4: Server Optimizations | Live Training | Unreal Engine
This week we'll be joined by Ryan Gerleve and Dave Ratti to discuss general server optimization in UE4, as well as techniques and solutions to improve your ...
Unreal Engine
Anna Nicanorova: Optimizing Life Everyday Problems Solved with Linear Programing in Python
PyData NYC 2015 Linear Optimization can be a very powerful tool to enable mathematical decision-making under constrains. This tutorial is designed on how to ...
PyData
Approximation Algorithms for Discrete Stochastic Optimization Problems
We will survey recent work in the design of approximation algorithms for several discrete stochastic optimization problems, with a particular focus on 2-stage ...
Microsoft Research
11.3 Linear Programming | 11 Optimization | Pattern Recognition Class 2012
The Pattern Recognition Class 2012 by Prof. Fred Hamprecht. It took place at the HCI / University of Heidelberg during the summer term of 2012. Website: ...
UniHeidelberg
Lec-20 Shortest Path Problem
Lecture series on Advanced Operations Research by Prof. G.Srinivasan, Department of Management Studies, IIT Madras. For more details on NPTEL visit ...
nptelhrd
Convex Optimization with Abstract Linear Operators, ICCV 2015 | Stephen P. Boyd, Stanford
We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user ...
Preserve Knowledge
15. Linear Programming: LP, reductions, Simplex
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, ...
MIT OpenCourseWare
Model Predictive Control
This lecture provides an overview of model predictive control (MPC), which is one of the most powerful and general control frameworks. MPC is used extensively ...
Steve Brunton
Wireless Network Coding for Multiple Unicast Sessions [1/9]
A recent approach, COPE, for improving the throughput of unicast traffic in wireless multi-hop networks exploits the broadcast nature of the wireless medium ...
Microsoft Research
Oracle SNO - Strategic Network Optimization - Automatização do sistema
Apresentação simples e básica de como automatizar a rotina em modelos de programação linear no Oracle SNO - Strategic Network Optimization.
Marcelo Carvalho dos Anjos
SAS Optimization 8.2
http://www.sas.com/optimization Evaluate alternative actions and scenarios with a powerful array of optimization modeling capabilities and solution techniques.
SAS Software
On Expressiveness and Optimization in Deep Learning - Nadav Cohen
Members' Seminar Topic: On Expressiveness and Optimization in Deep Learning Speaker: Nadav Cohen Affiliation: Member, School of Mathematics Date: April ...
Institute for Advanced Study
IBM ILOG CPLEX Optimization Studio Overview
Take decision-making capabilities to new levels with the power to run complex models with large data sets, factor in business rules and constraints, rapidly find ...
IBM Data and AI
James McCaffrey: Swarm Intelligence Optimization using Python
PyData Seattle 2015 Swarm intelligence (SI) algorithms mimic the collective behavior of groups such as flocks of birds and schools of fish. This session ...
PyData
Dimitri P. Bertsekas - Optimization Society Prize
INFORMS
Uncapacitated network flow - Integer Linear Programming 101
Uncapacitated network flow problem with integer requirements. Video created with Doce Nos http://bitly.com/Lx8UdN and iMovie.
mathapptician
