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Optimization

1203 directly classified papers

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Papers

Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020
Optimal Policy for Deployment of Machine Learning Models on Energy-Bounded Systems IJCAI 2020
Sparse Tree Search Optimality Guarantees in POMDPs with Continuous Observation Spaces IJCAI 2020
Learning Optimal Decision Trees using Constraint Programming (Extended Abstract) IJCAI 2020
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes AAAI 2020
SPAN: A Stochastic Projected Approximate Newton Method AAAI 2020
Error Estimation for Sketched SVD via the Bootstrap ICML 2020
Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle ICML 2020
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization ICML 2020
List Decodable Subspace Recovery COLT 2020
Sensor Placement for Spatial Gaussian Processes with Integral Observations UAI 2020
Zeroth Order Non-convex optimization with Dueling-Choice Bandits UAI 2020
Learning Intrinsic Rewards as a Bi-Level Optimization Problem UAI 2020
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers NIPS 2020
A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration NIPS 2020
Sampling from a k-DPP without looking at all items NIPS 2020
Deep Statistical Solvers NIPS 2020
Automatically Learning Compact Quality-aware Surrogates for Optimization Problems NIPS 2020
Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function NIPS 2020
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining NIPS 2020
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method NIPS 2020
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities NIPS 2020
Planning with General Objective Functions: Going Beyond Total Rewards NIPS 2020
Online Convex Optimization Over Erdos-Renyi Random Networks NIPS 2020
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling NIPS 2020