Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Discretization-free Knowledge Gradient Methods for Bayesian Optimization
Practical Bayesian Optimization of Machine Learning Algorithms
Bayesian Optimization in AlphaGo
On the Limited Memory BFGS Method for Large Scale Optimization
Simulation optimization: A tutorial overview and recent developments in gradient-based methods
Portfolio Allocation for Bayesian Optimization
Learning to Optimize Via Posterior Sampling
Derivative-free optimization: a review of algorithms and comparison of software implementations
FLASH: Fast Bayesian Optimization for Data Analytic Pipelines
On the Use of Stochastic Hessian Information in Optimization Methods for Machine Learning
Bayesian Gradient Descent: Online Variational Bayes Learning with Increased Robustness to Catastrophic Forgetting and Weight Pruning
an adaptive gradient sampling algorithm for non - smooth optimization .
Benchmarking derivative-free optimization algorithms
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization
A Variational Perspective on Accelerated Methods in Optimization
Langevin-gradient parallel tempering for Bayesian neural learning
High Dimensional Bayesian Optimisation and Bandits via Additive Models
Input Warping for Bayesian Optimization of Non-stationary Functions
Bayesian optimization for predicting rare internal failures in manufacturing processes
Projected Newton methods for optimization problems with simple constraints
Contextual Gaussian Process Bandit Optimization
2D face liveness detection: An overview
Relaxed local ternary pattern for face recognition
Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award)
Global-scale object detection using satellite imagery