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Meta-Learning Algorithms
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Classroom Contents
AI-Generating Algorithms - A Unique Opportunity
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- 1 Intro
- 2 Manual Path to AI
- 3 Clear Machine Learning Trend: Hand-designed pipelines are ultimately outperformed by learned solutions
- 4 Al-Generating Algorithms
- 5 Synthetic Petri Dish A Novel Surrogate Model for Rapid Architecture Search
- 6 Meta-learn learning algorithms
- 7 Meta-Learning Algorithms
- 8 Pillar 2: Meta-Learning
- 9 Catastrophic Forgetting
- 10 Proposal: Use meta-learning to learn to continually learn
- 11 Traditional Neuromodulation
- 12 Learned Sparsity
- 13 ANML Implications
- 14 Pillar 2: Meta-learn learning algorithm
- 15 A Paradox
- 16 Key for Science & Technological Innovation: Generating Problems, Goal Switching
- 17 Qualitatively Different
- 18 Intrinsic Motivation
- 19 Derailment
- 20 Avoids Detachment By Remembering Promising Exploration Stepping Stones
- 21 Results on Montezuma's Revenge
- 22 Pitfall
- 23 Go-Explore: Implications
- 24 What's missing?
- 25 Traditional ML
- 26 Paired Open-Ended Trailblazer (POET)
- 27 Task: Obstacle Courses
- 28 Direct Path Curriculum Fails
- 29 Enhanced POET
- 30 POET: Future Work
- 31 Overall Conclusions
