Notes
- Triplet Loss
- Multidimensional Mental Representations of Natural Objects
- Testing a PA model
- AI for Health
- Monopoly in Tech
- One Stock to Rule Them All
- Complexity Theory
- Stewardship of Global Collective Beahvior
- Dynamic Graph Models
- Explainable Trees
- A Universal Law of Robustness via Isoperimetry
- Troubles with AI in insurtech
- Siamese Network
- Unsupervised Language Translation
- The Language of Animals
- Pediatric Transfer Learning
- Learning as the Unsupervised Alignment of Conceptual Systems
- Working From Home
- Loftus and Memory
- Rotation Dynamics in Neurons
- The Asymmetry of Bitcoin
- Securities Law and Insurance
- /r/wallstreetbets
- Reflexivity
- Neural Code for Faces
- Linguistic Neuroscience
- We
- The Perils of Explainability
- Relational Learning and Word Embeddings
- Judicial Demand for xAI
- The Search for Meaning
- New Medium
- Robustness of Facial Embeddings
- Grand Theory of Social Networks
- Death of Value Investing
- Communist Index Funds
- Language Biases in Pediatric Emergency Department
- Framework for Fairness
- On Single Point Forecasts for Fat Tailed Variables
- Control Theory
- Noisy Networks
- Fractals
- Experimental Logs for MovieLens
- Efficient Markets and Data
- Openendedness
- Dataset Bias
- Implicit Regularization
- System 1 and 2
- Envisioning the Future
- Fast Weights
- GPT-3
- Experimental Logs for Matrix Completion
- Matrix Completion Optimization
- Calculus for Brain Computation
- Invariant Risk Minimization
- Next Steps for Deep Learning
- Bitter Lesson
- Two Cultures
- On Optimization
- Exponential Learning Rates
- Debiasing Word Embeddings
- Explaining Word Embeddings
- Alone
- Learning DAGs
- The Unreasonable Effectiveness of Adam
- Transformers
- Precision/Recall
- Transfer Learning
- Meta Learning
- Signed Word Embeddings
- Does Learning Require Memorization?
- Dyadic Imbalance in Networks
- Implicit Self Regularization in Deep Neural Networks
- Benign Overfitting in Linear Regression
- ↩︎ toread
- SOTA Collaborative Filtering
- Problems with Machine Learning Scholarship
- Discretization of Gradient Flow
- Michael Jordan Plenary Talk
- Graph Neural Networks
- Graph Network as Arbitrary Inductive Bias
- Network Pruning
- Market for Lemons
- Matrix Factorization to Linear Model
- Next Steps for Penalty Paper
- Meta Analysis vs Preregistration
- Overparameterized Regression
- On the Optimization of Deep Networks
- Troubling Trends in Machine Learning Scholarship
- Concurrent Face and Word Embeddings
- Parameter Estimation in SBM
- Nonparametric Testing on Graphs
- The Form of the Loss in Matrix Completion
- Rethinking Generalization
- Pseudo-inverses and SGD
- Linear Networks via GD Trajectory
- Why Greatness Cannot be Planned
- Honduras Face Project
- Statistics vs ML
- Project Penalty
- Project Fairness
- ★ Master Paper List
- ↩︎ idea
- Matrix Completion Experiments
- Matrix Completion Optimal Rates
- Power Tower
- New Balance Theory
- Animal Crossing
- AB Testing in Networks
- New Linear Algebra
- Extending the Penalty
- Effectiveness of Normalized Quantities
- Personalized Art
- Peloton
- Episode with Ilya
- Neural Tangent Kernels
- Project Interpolation
- Next Steps for Interpolation
- Project Misinformation
- A Snide Comment about Certain Types of Research
- How to Take Smart Notes
- Path To Zettelkasten
- Language Generation