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Artificial Intelligence
The Rise of Mixture-of-Experts for Efficient Large Language Models
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March 22, 2024
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Artificial Intelligence
Navigating Cost-Complexity: Mixture of Thought LLM Cascades Illuminate a Path to Efficient Large Language Model Deployment
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March 7, 2024
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Artificial Intelligence
LoRa, QLoRA and QA-LoRA: Efficient Adaptability in Large Language Models Through Low-Rank Matrix Factorization
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October 24, 2023
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Artificial Intelligence
Machine-learning system based on light could yield more powerful, efficient large language models
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August 23, 2023
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Artificial Intelligence
Implementing math in deep learning papers into efficient PyTorch code: SimCLR Contrastive Loss
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July 8, 2023
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Artificial Intelligence
Empowering Efficient BO Transfer with Neural Acquisition Process (NAP) General Objectives & Results: From Bayesian Optimisation to Meta-Bayesian Optimisation: Neural Acquisition Processes (NAP): Cool Properties:
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June 7, 2023
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Artificial Intelligence
Empowering Efficient BO Transfer with Neural Acquisition Process (NAP) General Objectives & Results: From Bayesian Optimisation to Meta-Bayesian Optimisation: Neural Acquisition Processes (NAP): Cool Properties:
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June 7, 2023
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Artificial Intelligence
XGBoost: How Deep Learning Can Replace Gradient Boosting and Decision Trees — Part 1 XGBoost is extremely efficient, but… Constructing Decision Trees just isn’t a differentiable process Feature selection regularization Introducing a threshold Next steps
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June 1, 2023
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Artificial Intelligence
LLAMA: Open and efficient foundation language. | by Roopal jain | May, 2023
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June 1, 2023
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Artificial Intelligence
XGBoost: How Deep Learning Can Replace Gradient Boosting and Decision Trees — Part 1 XGBoost is very efficient, but… Constructing Decision Trees shouldn’t be a differentiable process Feature selection regularization Introducing a threshold Next steps
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May 31, 2023
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