Learning
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Revealing the Utilized Rank of Subspaces of Learning in Neural Networks
In this work, we study how well the learned weights of a neural network utilize the space available to them.…
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Branch-and-Merge Method: Enhancing Language Adaptation in AI Models by Mitigating Catastrophic Forgetting and Ensuring Retention of Base Language Capabilities while Learning New Languages
Language model adaptation is a crucial area in artificial intelligence, focusing on enhancing large pre-trained language models to work effectively…
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Reinforcement Learning, Part 5: Temporal-Difference Learning | by Vyacheslav Efimov | Jul, 2024
Intelligently synergizing dynamic programming and Monte Carlo algorithms 15 min read · 18 hours ago Reinforcement learning is a domain…
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What are Bias and Variance in Machine Learning?
Machine learning deserves more scrutiny than ever due to the growing adoption of ML applications. The development and assessment of…
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Microsoft’s Comprehensive Four-Stage AI Learning Journey: Empowering Businesses with Skills for Effective AI Integration and Innovation
Microsoft has unveiled an extensive AI learning journey designed to deal with the diverse needs of various personas within a…
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Advancements in Protein Sequence Design: Leveraging Reinforcement Learning and Language Models
Protein sequence design is crucial in protein engineering for drug discovery. Traditional methods like evolutionary strategies and Monte-Carlo simulations often…
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Policy Learning with Large World Models: Advancing Multi-Task Reinforcement Learning Efficiency and Performance
Reinforcement Learning (RL) excels at tackling individual tasks but struggles with multitasking, especially across different robotic forms. World models, which…
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Explainability, Interpretability and Observability in Machine Learning | by Jason Zhong | Jun, 2024
Explainability has no standard definition, but rather is generally accepted to refer to “the movement, initiatives, and efforts made in…
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A New Machine Learning Research from UCLA Uncovers Unexpected Irregularities and Non-Smoothness in LLMs’ In-Context Decision Boundaries
Recent language models like GPT-3+ have shown remarkable performance improvements by simply predicting the next word in a sequence, using…
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What is the Process of Machine Learning (ML) Development?
Machine learning has spurred a formidable revolution in technology by enabling interactions between humans and machines. The common assumption about…
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