Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
Stochastic Gradient Descent
Adaptive subgradient methods for online learning and stochastic optimization
A Variational Analysis of Stochastic Gradient Algorithms
Gradient Descent Only Converges to Minimizers: Non-Isolated Critical Points and Invariant Regions
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization
Accelerated gradient methods for stochastic optimization and online learning
Theoretical Insights Into the Optimization Landscape of Over-Parameterized Shallow Neural Networks
First- and Second-Order Methods for Learning: Between Steepest Descent and Newton's Method
An overview of gradient descent optimization algorithms
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Minima and Regularization Effects
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
EE-Grad: Exploration and Exploitation for Cost-Efficient Mini-Batch SGD
Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization
A Bayesian Perspective on Generalization and Stochastic Gradient Descent
Parameterless Stochastic Natural Gradient Method for Discrete Optimization and its Application to Hyper-Parameter Optimization for Neural Network
Continuous-Time Limit of Stochastic Gradient Descent Revisited
Adaptive sampling for SGD by exploiting side information
Learning Gradient Descent: Better Generalization and Longer Horizons
An Active-Clamp Push–Pull Converter for Battery Sourcing Applications
on the emergence of invariance and disentangling in deep representations .
Predicting Information Seeking Intentions from Search Behaviors
Improving Data Quality through Deep Learning and Statistical Models
Orthognathic surgery: a hierarchy of stability.