Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Hedging for LPs
Graph Chatbot
Related lectures (29)
Approximation Algorithms
Covers approximation algorithms for optimization problems, LP relaxation, and randomized rounding techniques.
Generalization Error
Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.
Sparsest Cut: Bourgain's Theorem
Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.
Distributions and Derivatives
Covers distributions, derivatives, convergence, and continuity criteria in function spaces.
Sparsest Cut: ARV Theorem
Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.
Caratheodory Bounds: Integer Programming
Covers Caratheodory bounds for integer programming, focusing on linear programming and the existence of optimal solutions.
Sparsest Cut: Leighton-Rao Algorithm
Covers the Leighton-Rao algorithm for finding the sparsest cut in a graph, focusing on its steps and theoretical foundations.
Exponential Family: Maximum Entropy Distributions
Covers exponential families and maximum entropy distributions under moment constraints.
Semi-Definite Programming
Covers semi-definite programming and optimization over positive semidefinite cones.
Stable Laws and Limit Theorems
Explores stable laws, limit theorems, and random variable properties.
Information Measures: Entropy and Information Theory
Explains how entropy measures uncertainty in a system based on possible outcomes.
Cartesian Product and Induction
Introduces Cartesian product and induction for proofs using integers and sets.
Composition of Applications in Mathematics
Explores the composition of applications in mathematics and the importance of understanding their properties.
Multivariate Statistics: Wishart and Hotelling T²
Explores the Wishart distribution, properties of Wishart matrices, and the Hotelling T² distribution, including the two-sample Hotelling T² statistic.
Set Cover: Integrality Gap
Explores the integrality gap concept in set cover and multiplicative weights algorithms.
Graph Sketching: Connected Components
Covers the concept of graph sketching with a focus on connected components.
Fourier Inversion Formula
Covers the Fourier inversion formula, exploring its mathematical concepts and applications, emphasizing the importance of understanding the sign.
Compression: Kraft Inequality
Explains compression and Kraft inequality in codes and sequences.
Convergence of Random Walks
Explores the convergence of random walks on graphs and the properties of weighted adjacency matrices.
Weak Derivatives: Definition and Properties
Covers weak derivatives, their properties, and applications in functional analysis.
Previous
Page 1 of 2
Next