Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Semidefinite Programming: Formulations and Applications
Graph Chatbot
Related lectures (53)
Nonconvex Optimization: Challenges and Strategies
Explores nonconvex optimization challenges and strategies, including blind image deconvolution and SDP relaxations.
Primal-dual Optimization II
Explores primal-dual optimization methods, focusing on Lagrangian approaches and various methods like penalty, augmented Lagrangian, and splitting techniques.
Minimum Spanning Trees: Prim's Algorithm
Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.
Primal-dual Optimization III: Lagrangian Gradient Methods
Explores primal-dual optimization methods, emphasizing Lagrangian gradient techniques and their applications in data optimization.
Graph Algorithms: Ford-Fulkerson and Strongly Connected Components
Discusses the Ford-Fulkerson method and strongly connected components in graph algorithms.
Algorithms: Union Find and Minimum Spanning Trees
Discusses Union-Find data structures and Minimum Spanning Trees, covering algorithms and their applications in network design and optimization.
Spectral Clustering: Theory and Applications
Explores spectral clustering theory, eigenvalue decomposition, Laplacian matrix, and practical applications in identifying clusters.
Linear Programming: Weighted Bipartite Matching
Covers linear programming, weighted bipartite matching, and vertex cover problems in optimization.
Graph Coloring: Random vs Symmetrical
Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.
The Hidden Convex Optimization Landscape of Deep Neural Networks
Explores the hidden convex optimization landscape of deep neural networks, showcasing the transition from non-convex to convex models.
Graph Models and Brain Connectomics
Explores graph theory in brain connectomics, MRI applications, network analysis relevance, and individual fingerprinting.
Graph Algorithms II: Traversal and Paths
Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.
Flow Networks: Understanding Flows and Cuts in Algorithms
Covers flow networks, focusing on flows, cuts, and their applications in algorithms.
Max Sum Diversification
Log in to Mediaspace to watch this video
Explores maximizing diversity in document selection, graph clique determination, theorems on negative type, and convex optimization.
Relations Between Events
Log in to Mediaspace to watch this video
Explores relations between events, disjunctive constraints, and modeling with binary variables in optimization problems.
Network clustering
Log in to Mediaspace to watch this video
Explores network clustering, spectral clustering, k-means algorithm, eigenvalue properties, block model estimation, and structural similarity measurement.
Graph Theory Basics
Log in to Mediaspace to watch this video
Introduces induced flows, basis matrices, and tree solutions in graph theory.
Dijkstra's Algorithm Overview
Log in to Mediaspace to watch this video
Demonstrates the iterative process of applying Dijkstra's algorithm to find optimal paths.
Differentiable Functions and Lagrange Multipliers
Log in to Mediaspace to watch this video
Covers differentiable functions, extreme points, and the Lagrange multiplier method for optimization.
Graph Theory and Network Flows
Log in to Mediaspace to watch this video
Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.
Previous
Page 1 of 3
Next
