Social And Emotional Learning Courses

Institute for Advanced Study

Instance-Hiding Schemes for Private Distributed Learning

Explore private distributed learning techniques, including instance-hiding schemes, cryptographic methods, and data augmentation, with insights on privacy laws and practical applications.

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

Institute for Advanced Study

The Challenges of Model-Based Reinforcement Learning and How to Overcome Them - Csaba Szepesvári

Explore challenges in model-based reinforcement learning, including modeling errors and efficient planning, and discover strategies to overcome them in complex environments.

• YouTube
• 1 hour 39 minutes
• Self-Paced
• Free Video

Institute for Advanced Study

Learning Probability Distributions - What Can, What Can't Be Done - Shai Ben-David

Explore probability distribution learning, its possibilities and limitations. Shai Ben-David discusses density estimation, sample compression schemes, and challenges in statistical learning theory.

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

Institute for Advanced Study

Steps Towards More Human-Like Learning in Machines - Josh Tenenbaum

Explore how machines can achieve more human-like learning through probabilistic programming, intuitive psychology, and simulation engines. Discover insights on core knowledge and one-shot learning in AI.

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

Institute for Advanced Study

Meta-Learning - Why It’s Hard and What We Can Do - Ke Li

Explore meta-learning challenges and solutions with Ke Li, covering optimization, model selection, and program induction in this theoretical machine learning seminar.

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

Institute for Advanced Study

Interpolation in Learning - Steps Towards Understanding When Overparameterization Is Harmless, When It Helps, and When It Causes Harm

Explore overparameterization in machine learning, its benefits, potential harm, and the double descent phenomenon. Gain insights into interpolation regimes and matrix intuition.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

Institute for Advanced Study

Re-Imagining the Social Sciences in the Age of AI - March 4, 2020

Explore the intersection of AI and social sciences through expert talks on mate selection decision-making and human behavior as AI's next frontier, followed by a moderated discussion and audience Q&A.

• YouTube
• 1 hour 30 minutes
• Self-Paced
• Free Video

Institute for Advanced Study

Deep Reinforcement Learning in the Real World - Sergey Levine

Explore deep reinforcement learning applications in real-world scenarios, focusing on off-policy methods, model-free and model-based approaches, and their practical implementations in robotics and manipulation tasks.

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

Institute for Advanced Study

Toward a Causal Analysis of Generalization in Deep Learning - Behnam Neyshabur

Explore causal factors behind deep learning generalization, examining measures like path norm, flatness, and gradient noise to predict and understand model performance.

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

Institute for Advanced Study

Provably Efficient Reinforcement Learning with Linear Function Approximation - Chi Jin

Explore efficient reinforcement learning with linear function approximation, covering key concepts like sample efficiency, value-based algorithms, and exploration in multi-armed bandits and linear MDPs.

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

Institute for Advanced Study

Learning Representations Using Causal Invariance - Leon Bottou

Explore causal invariance in machine learning representations, focusing on stable properties, extrapolation, and robust supervised learning techniques for improved model performance and generalization.

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

Institute for Advanced Study

From Classical Statistics to Modern ML - The Lessons of Deep Learning - Mikhail Belkin

Explore the transition from classical statistics to modern machine learning, focusing on deep learning's impact, interpolation methods, and the "double descent" phenomenon in generalization theory.

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

Institute for Advanced Study

Energy-Based Approaches to Representation Learning - Yann LeCun

Explore energy-based approaches to representation learning with Yann LeCun, covering self-supervised learning, video prediction, and sparse modeling in high-dimensional spaces.

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

Institute for Advanced Study

PAC-Bayesian Approaches to Understanding Generalization in Deep Learning - Gintare Dziugaite

Explore PAC-Bayesian approaches for understanding generalization in deep learning, covering risk bounds, optimal priors, and data-dependent techniques for neural networks.

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

Institute for Advanced Study

Is Optimization the Right Language to Understand Deep Learning? - Sanjeev Arora

Explore deep learning optimization, generalization, and neural tangent kernels with Sanjeev Arora. Gain insights into training wide networks and matrix completion techniques.

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