In geometry, the nonconvex great rhombicosidodecahedron is a nonconvex uniform polyhedron, indexed as U67. It has 62 faces (20 triangles, 30 squares and 12 pentagrams), 120 edges, and 60 vertices. It is also called the quasirhombicosidodecahedron. It is given a SchlΓ€fli symbol rr{5β3,3}. Its vertex figure is a crossed quadrilateral. This model shares the name with the convex great rhombicosidodecahedron, also known as the truncated icosidodecahedron. (Wikipedia).
Using the pythagorean theorem to a rhombus
π Learn how to solve problems with rhombuses. A rhombus is a parallelogram such that all the sides are equal. Some of the properties of rhombuses are: all the sides are equal, each pair of opposite sides are parallel, each pair of opposite angles are equal, the diagonals bisect each other,
From playlist Properties of Rhombuses
Applying the properties of a rhombus to determine the length of a diagonal
π Learn how to solve problems with rhombuses. A rhombus is a parallelogram such that all the sides are equal. Some of the properties of rhombuses are: all the sides are equal, each pair of opposite sides are parallel, each pair of opposite angles are equal, the diagonals bisect each other,
From playlist Properties of Rhombuses
Using the properties of a rhombus to determine the missing value
π Learn how to solve problems with rhombuses. A rhombus is a parallelogram such that all the sides are equal. Some of the properties of rhombuses are: all the sides are equal, each pair of opposite sides are parallel, each pair of opposite angles are equal, the diagonals bisect each other,
From playlist Properties of Rhombuses
How to find the missing angle of a rhombus
π Learn how to solve problems with rhombuses. A rhombus is a parallelogram such that all the sides are equal. Some of the properties of rhombuses are: all the sides are equal, each pair of opposite sides are parallel, each pair of opposite angles are equal, the diagonals bisect each other,
From playlist Properties of Rhombuses
Determining a missing length using the properties of a rhombus
π Learn how to solve problems with rhombuses. A rhombus is a parallelogram such that all the sides are equal. Some of the properties of rhombuses are: all the sides are equal, each pair of opposite sides are parallel, each pair of opposite angles are equal, the diagonals bisect each other,
From playlist Properties of Rhombuses
What are the properties that make up a rhombus
π Learn how to solve problems with rhombuses. A rhombus is a parallelogram such that all the sides are equal. Some of the properties of rhombuses are: all the sides are equal, each pair of opposite sides are parallel, each pair of opposite angles are equal, the diagonals bisect each other,
From playlist Properties of Rhombuses
Yuxin Chen: "The Effectiveness of Nonconvex Tensor Completion: Fast Convergence & Uncertainty Qu..."
Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop IV: Efficient Tensor Representations for Learning and Computational Complexity "The Effectiveness of Nonconvex Tensor Completion: Fast Convergence and Uncertainty Quantification" Yuxin Chen - Princeto
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Using a set of points determine if the figure is a parallelogram using the midpoint formula
π Learn how to determine the figure given four points. A quadrilateral is a polygon with four sides. Some of the types of quadrilaterals are: parallelogram, square, rectangle, rhombus, kite, trapezoid, etc. Each of the types of quadrilateral has its properties. Given four points that repr
From playlist Quadrilaterals on a Coordinate Plane
Xiadong Li: Phase Retrieval from Convex to Nonconvex Methods
Xiadong Li: Phase Retrieval from Convex to Nonconvex Methods Abstract: In phase retrieval, one aims to recover a signal from magnitude measurements. In the literature, an effective SDP algorithm, referred to as PhaseLift, was proposed with numerical success as well as strong theoretical g
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"
Robert Luce: Local and global solution of nonconvex quadratic problems
We review some of the key techniques Gurobi uses to solve nonconvex quadratic optimization problems to global optimality. In particular we will discuss the McCormick relaxation, powerful cutting planes in this context, and local heuristics.
From playlist Workshop: Continuous approaches to discrete optimization
MIT 6.849 Geometric Folding Algorithms: Linkages, Origami, Polyhedra, Fall 2012 View the complete course: http://ocw.mit.edu/6-849F12 Instructor: Erik Demaine This class introduces the pita form and Alexandrov-Pogorelov Theorem. D-forms are discussed with a construction exercise, followed
From playlist MIT 6.849 Geometric Folding Algorithms, Fall 2012
Class 16: Vertex & Orthogonal Unfolding
MIT 6.849 Geometric Folding Algorithms: Linkages, Origami, Polyhedra, Fall 2012 View the complete course: http://ocw.mit.edu/6-849F12 Instructor: Erik Demaine This class reviews covers topologically convex vertex-ununfoldable cases and unfolding for orthogonal polyhedra, including the app
From playlist MIT 6.849 Geometric Folding Algorithms, Fall 2012
Fifth Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk
Date: Wednesday, November 1, 10:00am EDT Speaker: Xiaoqun Zhang, Shanghai Jiao Tong University Title: Stochastic primal dual splitting algorithms for convex and nonconvex composite optimization in imaging Abstract: Primal dual splitting algorithms are largely adopted for composited optim
From playlist Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series
Masterclass for optimisation - Professor Coralia Cartis, University of Oxford
Bio Coralia Cartis (BSc Mathematics, Babesh-Bolyai University, Romania; PhD Mathematics, University of Cambridge (2005)) has joined the Mathematical Institute at Oxford and Balliol College in 2013 as Associate Professor in Numerical Optimization. Previously, she worked as a research scien
From playlist Data science classes
Worst-case complexity and optimality of methods for smooth optimization β P. Toint β ICM2018
Control Theory and Optimization Invited Lecture 16.5 Worst-case evaluation complexity and optimality of second-order methods for nonconvex smooth optimization Philippe Toint Abstract: We establish or refute the optimality of inexact second-order methods for unconstrained nonconvex optimi
From playlist Control Theory and Optimization
Using the properties of a rhombus to determine the side of a rhombus
π Learn how to solve problems with rhombuses. A rhombus is a parallelogram such that all the sides are equal. Some of the properties of rhombuses are: all the sides are equal, each pair of opposite sides are parallel, each pair of opposite angles are equal, the diagonals bisect each other,
From playlist Properties of Rhombuses
How to use proportions for an isosceles triangle
π Learn how to solve with similar triangles. Two triangles are said to be similar if the corresponding angles are congruent (equal). Note that two triangles are similar does not imply that the length of the sides are equal but the sides are proportional. Knowledge of the length of the side
From playlist Similar Triangles
Adaptive, Gain-Scheduled and Nonlinear Model Predictive Control | Understanding MPC, Part 4
This video explains the type of MPC controller you can use based on your plant model, constraints, and cost function. - Model Predictive Control Toolbox: http://bit.ly/2xgwWvN- - What Is Model Predictive Control Toolbox?: http://bit.ly/2xfEe2M The available options include the linear ti
From playlist Understanding Model Predictive Control
Orthocenters exist! | Universal Hyperbolic Geometry 10 | NJ Wildberger
In classical hyperbolic geometry, orthocenters of triangles do not in general exist. Here in universal hyperbolic geometry, they do. This is a crucial building block for triangle geometry in this subject. The dual of an orthocenter is called an ortholine---also not seen in classical hyperb
From playlist Universal Hyperbolic Geometry