Artificial Intelligence
Comprehensive exploration of AI concepts, algorithms, and techniques, covering search strategies, optimization methods, game playing, planning, constraint satisfaction, and knowledge-based systems.
Stereo Vision and Depth Perception in Computer Vision - Lecture 16
Explore stereo vision techniques, including shape reconstruction, rectification, correspondence, and correlation methods for depth perception in computer vision applications.
The Traveling Salesman Problem - When Good Enough Beats Perfect
Explore heuristic approaches and optimization techniques for the Traveling Salesman Problem, including nearest neighbor, greedy, Christofides, local search, simulated annealing, and ant colony optimization.
Estimating Human Motion: Past, Present, and Future
Explore the evolution of human motion estimation techniques, from early computer vision approaches to modern 3D body modeling, with insights on challenges and future directions.
Interacting Particle Systems for Expectation Maximization in Latent Variable Models
Explore a novel interacting particle system for EM optimization in latent variable models, featuring Langevin diffusion analysis and non-asymptotic concentration bounds for maximum likelihood estimation.
Collie - Finding Performance Anomalies in RDMA Subsystems
Discover a tool for uncovering performance anomalies in RDMA subsystems, exploring its design, implementation, and effectiveness in finding and addressing hardware-related issues.
Turtles! Hill Climbing! Hammers! Paper Bags!
Explore optimization techniques through turtle graphics, from hill climbing to simulated annealing, laying the groundwork for understanding neural networks and machine learning concepts.
Distributed Parametric Optimization with the Geneva Library
Explore Geneva, an open-source library for distributed optimization algorithms, leveraging Boost libraries to solve large-scale parametric problems on multi-core systems, clusters, and cloud environments.
Simulated Annealing - The Most Metal Algorithm Ever
Explore simulated annealing, a metallurgy-inspired algorithm for near-optimal solutions in constrained optimization problems, and learn to implement it using the Annealing gem in Ruby.
Simulated Annealing: The Most Metal Algorithm Ever - Lecture
Explore simulated annealing algorithm for near-optimal solutions in constrained optimization problems, inspired by metallurgy and applicable to Ruby apps.