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The way to Encode Constraints to the Output of Neural Networks If one shot doesn’t work, try multiple shots Perhaps… Let’s learn the constraints? One more interesting perspective: Solving a convex optimization problem For non-convex problems: Which gradient approximation do you favor? Self-promotion time: Projection without solving optimization A fast example How does LinSAT work? Afterword
Artificial Intelligence

The way to Encode Constraints to the Output of Neural Networks If one shot doesn’t work, try multiple shots Perhaps… Let’s learn the constraints? One more interesting perspective: Solving a convex optimization problem For non-convex problems: Which gradient approximation do you favor? Self-promotion time: Projection without solving optimization A fast example How does LinSAT work? Afterword

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Top Data Analytics Books to Read in 2024
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Top Data Analytics Books to Read in 2024

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Quantifying the Complexity and Learnability of Strategic Classification Problems References
Artificial Intelligence

Quantifying the Complexity and Learnability of Strategic Classification Problems References

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The Way forward for Neural Network Training: Empirical Insights into μ-Transfer for Hyperparameter Scaling
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The Way forward for Neural Network Training: Empirical Insights into μ-Transfer for Hyperparameter Scaling

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Constructing a RAG chain using LangChain Expression Language (LCEL) The Setup RAG Development Retrieving intermediate variables Why use LCEL? Resources
Artificial Intelligence

Constructing a RAG chain using LangChain Expression Language (LCEL) The Setup RAG Development Retrieving intermediate variables Why use LCEL? Resources

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Google AI Introduces CodecLM: A Machine Learning Framework for Generating High-Quality Synthetic Data for LLM Alignment
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Google AI Introduces CodecLM: A Machine Learning Framework for Generating High-Quality Synthetic Data for LLM Alignment

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The Current State of AI in Marketing 2024
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The Current State of AI in Marketing 2024

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This Study by UC Berkeley and Tel Aviv University Enhances Task Adaptability in Computer Vision Models Using Internal Network Task Vectors
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This Study by UC Berkeley and Tel Aviv University Enhances Task Adaptability in Computer Vision Models Using Internal Network Task Vectors

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How I Self-Study Data Science
Artificial Intelligence

How I Self-Study Data Science

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This AI Paper from Meta and MBZUAI Introduces a Principled AI Framework to Examine Highly Accurate Scaling Laws Concerning Model Size Versus Its Knowledge Storage Capability
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This AI Paper from Meta and MBZUAI Introduces a Principled AI Framework to Examine Highly Accurate Scaling Laws Concerning Model Size Versus Its Knowledge Storage Capability

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