Optimization

Bidirectional Model-based Policy Optimization ICML 2020 Bi-level Score Matching for Learning Energy-based Latent Variable Models NeurIPS 2020 Binarized Neural Architecture Search AAAI 2020 BINOCULARS for efficient, nonmyopic sequential experimental design ICML 2020 Biological credit assignment through dynamic inversion of feedforward networks NeurIPS 2020 Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework NeurIPS 2020 Black-Box Optimization with Local Generative Surrogates NeurIPS 2020 Black Box Submodular Maximization: Discrete and Continuous Settings AISTATS 2020 Blur Aware Calibration of Multi-Focus Plenoptic Camera CVPR 2020 Boosting-Based Reliable Model Reuse ACML 2020 Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates NeurIPS 2020 Boosting for Control of Dynamical Systems ICML 2020 Boosting Frank-Wolfe by Chasing Gradients ICML 2020 Boundary thickness and robustness in learning models NeurIPS 2020 Bounded Incentives in Manipulating the Probabilistic Serial Rule AAAI 2020 Bounding the expected run-time of nonconvex optimization with early stopping UAI 2020 BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic AAAI 2020 Branch and Bound for Piecewise Linear Neural Network Verification JMLR 2020 BRDF-Reconstruction in Photogrammetry Studio Setups WACV 2020 Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization NeurIPS 2020 Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model NeurIPS 2020 Bridging Maximum Likelihood and Adversarial Learning via α-Divergence AAAI 2020 Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection CVPR 2020 Bridging the Gap Between f-GANs and Wasserstein GANs ICML 2020 Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints ICLR 2020