AI
Deep Learning
Deep Networks Are Kernel Machines
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Frank
- February 18, 2021
- AI
- artificial intelligence
- Arxiv
- data representations
- Deep Learning
- deep neural networks
- explained
- kernel machines
- kernel trick
- learning theory
- Linear Regression
- Machine Learning
- machine learning theory
- math proof
- nearest neighbor
- Neural Networks
- neural networks gradient descent
- Paper
- pedro domingos
- proof
- representation learning
- representations
- representer theorem
- SGD
- stochastic gradient descent
- Support Vector Machine
- SVM
- what is deep learning
Yannic Kilcher explains the paper “Every Model Learned by Gradient Descent Is Approximately a Kernel Machine.” Deep Neural Networks are often said to discover useful representations of the data. However, this paper challenges this prevailing view and suggest that rather than representing the data, deep neural networks store superpositions of the training data in their […]
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