Paul G. Allen School Courses

2019 ADSI Summer Workshop- Algorithmic Foundations of Learning and Control, Yinyu Ye

Explore advancements in online linear programming and learning, focusing on resource allocation, competitive ratios, and dynamic learning applications in control systems.

• YouTube
• 46 minutes
• On-Demand
• Free Video

2019 ADSI Summer Workshop- Algorithmic Foundations of Learning and Control

Explore advanced techniques in reinforcement learning, focusing on randomized value functions and their applications in exploration strategies for complex decision-making problems.

• YouTube
• 50 minutes
• On-Demand
• Free Video

ADSI Summer Workshop: Algorithmic Foundations of Learning and Control - Emma Brunskill

Explore batch/counterfactual reinforcement learning techniques to optimize decision-making with minimal data, focusing on policy evaluation, generalization bounds, and applications in healthcare simulations.

• YouTube
• 50 minutes
• On-Demand
• Free Video

ADSI Summer Workshop- Algorithmic Foundations of Learning and Control, Pablo Parrilo

Explore advanced Gaussian kernel factorization techniques and their applications in machine learning and control systems, with insights from approximation theory.

• YouTube
• 51 minutes
• On-Demand
• Free Video

ADSI Summer Workshop- Algorithmic Foundations of Learning and Control

Explore model-based control for physical systems, covering inverse dynamics, optimization techniques, and automated discovery methods for advanced robotics and control applications.

• YouTube
• 49 minutes
• On-Demand
• Free Video

2019 ADSI Summer Workshop- Algorithmic Foundations of Learning and Control, Vikash Kumar

Explore algorithmic foundations of learning and control in robotics, covering model-based approaches, skill dynamics, and real-world applications with Google Brain researcher Vikash Kumar.

• YouTube
• 57 minutes
• On-Demand
• Free Video

ADSI Summer Workshop- Algorithmic Foundations of Learning and Control

Explore stable and efficient reinforcement learning algorithms with Csaba Szepesvári's presentation on Politex, focusing on generalization and pseudo regret in online learning and linear prediction.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Wireless Network System Capstone

Explore student projects showcasing innovative wireless network systems, from enhanced e-readers to collaborative tools and vision-based applications.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Deep Learning - Joan Bruna NYU

Explore deep learning concepts, including lazy regime, relative scale, and practical applications in this comprehensive lecture by Joan Bruna from NYU.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Deep Learning II - Joan Bruna NYU

Explore advanced deep learning concepts including symmetry, transformations, and geometric stability in neural networks with NYU professor Joan Bruna.

• YouTube
• 1 hour
• On-Demand
• Free Video

Reinforcement Learning - Emma Brunskill - Stanford University

Explore reinforcement learning fundamentals, applications, and challenges with Stanford's Emma Brunskill, covering AI planning, machine learning, and decision-making processes.

• YouTube
• 1 hour
• On-Demand
• Free Video

Deep Learning I - Joan Bruna NYU

Explore supervised learning, empirical risk, and fundamental theorems in deep learning with NYU professor Joan Bruna's comprehensive lecture on neural network foundations.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Convex Optimization V - Sebastien Bubeck - Microsoft Research

Explore advanced optimization techniques with Sebastien Bubeck, covering telescopic sums, continuous time analysis, and variance reduction in convex optimization.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Convex Optimization IV - Sebastien Bubeck, Microsoft Research

Explore advanced concepts in convex optimization, including gradient flow, comparison techniques, and optimal algorithms with Sebastien Bubeck from Microsoft Research.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

Convex Optimization III - Sebastien Bubeck - Microsoft Research

Explore advanced concepts in convex optimization, including gradient oracles, minimax principles, and efficient algorithms for solving complex optimization problems.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video