102 citations · 157 across the 6 of their papers we have counts for
16 papers
Ridgeless Interpolation with Shallow ReLU Networks in is Nearest Neighbor Curvature Extrapolation and Provably Generalizes on Lipschitz Functions
Boris Hanin
We prove a precise geometric description of all one layer ReLU networks with a single linear unit and input/output dimensions equal to one that interpolate a given dataset…
Random Neural Networks in the Infinite Width Limit as Gaussian Processes
Boris Hanin
This article gives a new proof that fully connected neural networks with random weights and biases converge to Gaussian processes in the regime where the input dimension, output di…
Deep ReLU Networks Preserve Expected Length
Boris Hanin, Ryan Jeong, David Rolnick
Assessing the complexity of functions computed by a neural network helps us understand how the network will learn and generalize. One natural measure of complexity is how the netwo…
Neural Network Approximation
Ronald DeVore, Boris Hanin, Guergana Petrova
Neural Networks (NNs) are the method of choice for building learning algorithms. Their popularity stems from their empirical success on several challenging learning problems. Howev…
How Data Augmentation affects Optimization for Linear Regression
Boris Hanin, Yi Sun
Though data augmentation has rapidly emerged as a key tool for optimization in modern machine learning, a clear picture of how augmentation schedules affect optimization and intera…
Non-asymptotic Results for Singular Values of Gaussian Matrix Products
Boris Hanin, Grigoris Paouris
This article concerns the non-asymptotic analysis of the singular values (and Lyapunov exponents) of Gaussian matrix products in the regime where the number of term in the pro…