Simons Institute Courses

The Importance of Better Models in Stochastic Optimization

Explore stochastic optimization models, focusing on robustness, stability, and asymptotic minimax theory. Learn about weak convexity, sharp growth problems, and practical experiments.

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

Robust List Decoding of Spherical Gaussians

Explore robust list decoding of spherical Gaussians, covering algorithms, error identification, and computational challenges in high-dimensional statistics.

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

Mathematical Theories of Communication - Old and New

Explore mathematical theories of communication, from Shannon's foundational work to modern interactive coding schemes and semantic communication, with applications to real-world scenarios.

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

The AI Trinity - Data + Algorithms + Infrastructure

Explore the AI trinity: data, algorithms, and infrastructure. Learn about named entity recognition, active learning, crowdsourcing, data augmentation, and neural rendering models.

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

Subspace Clustering Using Ensembles of K-Subspaces

Explore subspace clustering techniques, focusing on K-Subspaces ensembles. Learn about applications, results, and comparisons with other algorithms in this insightful talk by Laura Balzano.

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

Advanced Techniques for Low-Rank Matrix Approximation

Explore cutting-edge methods for low-rank matrix approximation, including randomized algorithms and factorizations, with insights on efficiency and accuracy comparisons.

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

Randomized Numerical Linear Algebra - Overview

Explore randomized numerical linear algebra techniques for efficient matrix computations, covering sampling methods, error bounds, and applications to least-squares problems and SVD.

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

Randomized Least Squares Regression - Combining Model- and Algorithm-Induced Uncertainties

Explore randomized least squares regression, combining model and algorithm uncertainties for improved statistical analysis and numerical linear algebra applications.

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

Emerging Trends & Applications in Communication Networks

Explore cutting-edge networking trends with experts discussing crypto, fake news, privacy, and social networks, offering insights into the future of communication technology.

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

The Future of Wireless and What It Will Enable

Explore the future of wireless technology, its potential, and innovative approaches like millimeter waves, small cells, and software-defined networks to overcome current limitations.

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

The Future Quantum Internet - Challenges

Explore challenges in quantum internet development, including performance, control, and routing entanglement flows. Learn about qubits, superposition, and long-distance entanglement in quantum networks.

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

Data Streams I

Explore network statistics and graph streaming models, focusing on linear sketches and connectivity algorithms for efficient data analysis in large-scale networks.

• YouTube
• 1 hour 6 minutes
• Self-Paced
• Free Video

Statistical Inference I

Explore statistical inference fundamentals, including models, estimation, minimax risk, and Bayesian approaches, with UC Berkeley's Will Fithian.

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

Sampling for Linear Algebra, Statistics, and Optimization I

Explore randomized numerical linear algebra techniques for efficient data analysis, covering sampling methods, matrix multiplication, and regression algorithms.

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

First-Order Stochastic Optimization

Explore first-order stochastic optimization techniques for machine learning, covering gradient descent, adaptive learning, and convergence rates in data science applications.

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