Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data
Theoretical Insights Into the Optimization Landscape of Over-Parameterized Shallow Neural Networks
Memory limitations alone do not lead to over-regularization: An experimental and computational investigation
A continuum among logarithmic, linear, and exponential functions, and its potential to improve generalization in neural networks
A Generalized Representer Theorem
the effective number of parameters : an analysis of generalization and regularization in nonlinear learning systems .
Nearly-tight VC-dimension bounds for piecewise linear neural networks
Learning Overcomplete Representations
Distribution-Specific Hardness of Learning Neural Networks
Layer-Specific Adaptive Learning Rates for Deep Networks
Regularization Theory and Neural Networks Architectures
No . 067 April 4 , 2017 Theory of Deep Learning III : Generalization Properties of SGD by
Global Optimality in Neural Network Training
Statistical inference using SGD
Stiffness: A New Perspective on Generalization in Neural Networks
Polynomial Bounds for VC Dimension of Sigmoidal and General Pfaffian Neural Networks
Minnorm training: an algorithm for training over-parameterized deep neural networks
Data-Dependent Generalization Bounds for Multi-Class Classification
Train longer, generalize better: closing the generalization gap in large batch training of neural networks
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond
SnapLink: Fast and Accurate Vision-Based Appliance Control in Large Commercial Buildings
Multidimensional materials and device architectures for future hybrid energy storage
Train faster, generalize better: Stability of stochastic gradient descent
conceptual metaphor theory meets the data : a corpus - based human annotation study .
Memory Capacities for Synaptic and Structural Plasticity