Machine Learning Street Talk (MLST) Robert Lange on NN Pruning and Collective Intelligence
Jul 8, 2020
In a fascinating conversation, Robert Lange, a PhD student at Technical University Berlin, delves into the realms of multi-agent reinforcement learning and cognitive science. He shares insights on the intersection of economics and machine learning, exploring how behavior influences decision-making. Robert also discusses his groundbreaking work on neural network pruning, highlighting the lottery ticket hypothesis and innovative strategies for optimizing networks. With a knack for making complex ideas accessible, he reflects on the nature of intelligence and the future of AI.
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Robert Lange's Background
- Robert Lange studied economics, data science, and machine learning at various universities.
- He's currently pursuing a PhD in multi-agent reinforcement learning, combining diverse fields like cognitive science and complex swarm dynamics.
Effective Note-Taking
- Robert Lange finds that note-taking is most effective when notes are visually appealing and concise.
- His visual note-taking approach, inspired by Natalia Vélez, helps him learn and contribute to the community.
Economics and Machine Learning
- Economics effectively describes social phenomena but struggles to address them practically.
- Machine learning, particularly reinforcement learning, offers a data-driven approach to enhance economic decision-making and policy.