Simons Institute Courses

Finding Large Cliques in Random and Semi-Random Graphs

Explore algorithms for finding large cliques in graphs, including constructive arguments, polynomial-time proofs, and paradigms for tackling this NP-hard problem.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Locally Testable Codes with Constant Rate, Distance, and Locality

Explore breakthroughs in locally testable codes, focusing on constant rate, distance, and locality. Irit Dinur discusses high-dimensional expanders, Tanner codes, and local testability proofs.

• YouTube
• 1 hour 7 minutes
• Self-Paced
• Free Video

Computational Barriers in Statistical Estimation and Learning

Explore statistical estimation challenges, information theory, and computational barriers in high-dimensional settings with Stanford's Andrea Montanari in this Richard M. Karp Distinguished Lecture.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Optimal Gradient-Based Algorithms for Non-Concave Bandit Optimization

Explore optimal gradient-based algorithms for non-concave bandit optimization, covering stochastic problems, low-rank linear rewards, and high-order polynomials with applications to reinforcement learning.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Optimal Transport and PDE - Gradient Flows in the Wasserstein Metric

Explore gradient flows in Wasserstein metric, continuity equations, and aggregation dynamics. Learn about two-layer neural networks and chi-squared divergence in optimization and sampling.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Crash Course on Optimal Transport

Explore optimal transport theory, its applications, and key concepts like cost formulation, optimal coupling, and transport maps in this comprehensive lecture.

• YouTube
• 1 hour 2 minutes
• Self-Paced
• Free Video

Sampling Crash Course

Explore geometric methods in optimization and sampling, covering direct methods, Markov chain Monte Carlo, and probabilistic approaches for efficient algorithm design and analysis.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Optimization Crash Course

Explore geometric methods in optimization and sampling, covering key topics like convexity, optimality, and gradient descent with expert insights from MIT's Ashia Wilson.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

Approximate Message Passing Algorithms

Explore Approximate Message Passing algorithms, their applications in statistical inference, and theoretical foundations including state evolution, convergence, and joint distribution analysis.

• YouTube
• 1 hour 7 minutes
• Self-Paced
• Free Video

An Almost Constant Lower Bound of the Isoperimetric Coefficient in the KLS Conjecture

Explore the KLS Conjecture's isoperimetric coefficient, its implications for MC sampling, and recent breakthroughs in establishing a near-constant lower bound.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Decoding Nonhuman Communication - Polylogues

Explore cutting-edge research on decoding nonhuman communication, from sperm whale vocalizations to plant acoustic responses, using machine learning and natural language processing techniques.

• YouTube
• 42 minutes
• Self-Paced
• Free Video

Quantum Algorithms for Optimization - Quantum Colloquium

Explore quantum algorithms for optimization, including discrete and continuous problems, with insights on potential speedups and limitations in quantum computing applications.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video

Formal Languages and Automata for Reward Function Specification and Efficient Reinforcement Learning

Explore formal languages and automata for specifying reward functions in reinforcement learning, focusing on Linear Temporal Logic and Reward Machines to address real-world RL challenges.

• YouTube
• 1 hour 24 minutes
• Self-Paced
• Free Video

Using Program Synthesis to Build Compilers

Explore program synthesis techniques for building efficient compilers, focusing on syntax-driven compilation, verification, and evaluation methods.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Classical Shadows of Quantum States - Quantum Colloquium

Explore quantum state representation, shadow tomography, and machine learning applications in quantum many-body problems with John Preskill's insightful lecture on classical shadows.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video