Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: A Bayesian Perspective on Generalization and Stochastic Gradient Descent
Bayesian Learning via Stochastic Gradient Langevin Dynamics
Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains
Stochastic Gradient Boosting
The Marginal Value of Adaptive Gradient Methods in Machine Learning
Accelerating Stochastic Gradient Descent using Predictive Variance Reduction
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization
Semi-Stochastic Gradient Descent Methods
An adaptive learning rate for stochastic variational inference
On Generalization and Regularization in Deep Learning
Bayesian Sampling Using Stochastic Gradient Thermostats
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
A robust adaptive stochastic gradient method for deep learning
Improving Generalization Performance by Switching from Adam to SGD
The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Minima and Regularization Effects
Variance Reduction for Stochastic Gradient Optimization
Bayesian Back-Propagation.
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method
On the Stability and Convergence of Stochastic Gradient Descent with Momentum
Adaptive subgradient methods for online learning and stochastic optimization
Parle: parallelizing stochastic gradient descent
A two-stage 3D Unet framework for multi-class segmentation on full resolution image
KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems
Bioavailability of fluticasone propionate and mometasone furoate aqueous nasal sprays
A cross-platform evaluation of various decision tree algorithms for prognostic analysis of breast cancer data
Stability and generalization