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📚TheoryAdvanced

Feature Learning vs Kernel Regime

The kernel (lazy) regime keeps neural network parameters close to their initialization, making training equivalent to kernel regression with a fixed kernel such as the Neural Tangent Kernel (NTK).

#neural tangent kernel#kernel ridge regression#lazy training+12
📚TheoryAdvanced

Mean Field Theory of Neural Networks

Mean field theory treats very wide randomly initialized neural networks as averaging machines where each neuron behaves like a sample from a common distribution.

Advanced
Group:
Deep Learning Theory
#mean field theory
#neural tangent kernel
#neural network gaussian process
+12
📚TheoryAdvanced

Information Bottleneck in Deep Learning

The Information Bottleneck (IB) principle formalizes learning compact representations T that keep only the information about X that is useful for predicting Y.

#information bottleneck#variational information bottleneck#mutual information+11
📚TheoryAdvanced

Generalization Bounds for Deep Learning

Generalization bounds explain why deep neural networks can perform well on unseen data despite having many parameters.

#generalization bounds#pac-bayes#compression bounds+12
📚TheoryAdvanced

Neural Tangent Kernel (NTK)

Neural Tangent Kernel (NTK) describes how wide neural networks train like kernel machines, turning gradient descent into kernel regression in the infinite-width limit.

#neural tangent kernel#ntk#nngp+12