
The author explores the use of transfer and meta-learning to improve weak supervision searches by reducing the amount of signal required for training neural networks.


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Improving-Weak-Supervision-Searches-with-Transfer-and-Meta-Learning


Improving Weak Supervision Searches with Transfer and Meta-Learning


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The author proposes a novel approach to training neural networks using monotone variational inequality, demonstrating faster convergence and improved performance compared to traditional methods.


an-alternative-approach-to-train-neural-networks-using-monotone-variational-inequality


An Alternative Approach to Train Neural Networks Using Monotone Variational Inequality
