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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

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.

Intermediate
Advanced
Filtering by:
#generalization
Group:
Deep Learning Theory
#information bottleneck
#variational information bottleneck
#mutual information
+11
📚TheoryIntermediate

Lottery Ticket Hypothesis

The Lottery Ticket Hypothesis (LTH) says that inside a large dense neural network there exist small sparse subnetworks that, when trained in isolation from their original initialization, can reach comparable accuracy to the full model.

#lottery ticket hypothesis#magnitude pruning#sparsity+12
📚TheoryIntermediate

Double Descent Phenomenon

Double descent describes how test error first follows the classic U-shape with increasing model complexity, spikes near the interpolation threshold, and then drops again in the highly overparameterized regime.

#double descent#interpolation threshold#overparameterization+12