Optimization

Learning Data Augmentation With Online Bilevel Optimization for Image Classification WACV 2021 Learning Dynamic Interpolation for Extremely Sparse Light Fields With Wide Baselines ICCV 2021 Learning Fast-Inference Bayesian Networks NeurIPS 2021 Learning Fast Sample Re-Weighting Without Reward Data ICCV 2021 Learning Feature Weights using Reward Modeling for Denoising Parallel Corpora EMNLP 2021 Learning from Censored and Dependent Data: The case of Linear Dynamics COLT 2021 Learning from History for Byzantine Robust Optimization ICML 2021 Learning Graph Neural Networks with Approximate Gradient Descent AAAI 2021 Learning Hard Optimization Problems: A Data Generation Perspective NeurIPS 2021 Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence NeurIPS 2021 Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize ICLR 2021 Learning Invariant Representations using Inverse Contrastive Loss AAAI 2021 Learning Large Neighborhood Search Policy for Integer Programming NeurIPS 2021 Learning Model-Based Privacy Protection under Budget Constraints AAAI 2021 Learning Model Preconditions for Planning with Multiple Models CoRL 2021 Learning Motion Priors for 4D Human Body Capture in 3D Scenes ICCV 2021 Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation IJCAI 2021 Learning Optical Flow From a Few Matches CVPR 2021 Learning Optimal Predictive Checklists NeurIPS 2021 Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs NeurIPS 2021 Learning Prediction Intervals for Regression: Generalization and Calibration AISTATS 2021 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization ICML 2021 Learning Space Partitions for Path Planning NeurIPS 2021 Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives JMLR 2021 Learning Spatially-Variant MAP Models for Non-Blind Image Deblurring CVPR 2021