🏢 California Institute of Technology
Universality in Transfer Learning for Linear Models
·1460 words·7 mins·
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AI Generated
Machine Learning
Transfer Learning
🏢 California Institute of Technology
Linear model transfer learning achieves universal generalization error improvements, depending only on first and second-order target statistics, and defying Gaussian assumptions.
Understanding Model Selection for Learning in Strategic Environments
·394 words·2 mins·
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Machine Learning
Reinforcement Learning
🏢 California Institute of Technology
Larger machine learning models don’t always mean better performance; strategic interactions can reverse this trend, as this research shows, prompting a new paradigm for model selection in games.
Practical Bayesian Algorithm Execution via Posterior Sampling
·2028 words·10 mins·
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AI Generated
Machine Learning
Active Learning
🏢 California Institute of Technology
PS-BAX, a novel Bayesian algorithm execution method using posterior sampling, efficiently selects evaluation points for complex tasks, outperforming existing methods in speed and scalability.
Mini-Sequence Transformers: Optimizing Intermediate Memory for Long Sequences Training
·2712 words·13 mins·
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Natural Language Processing
Large Language Models
🏢 California Institute of Technology
MINI-SEQUENCE TRANSFORMER (MST) drastically reduces memory usage in LLM training by processing mini-sequences iteratively, enabling training with 12-24x longer sequences than conventional methods with…