Optimization

BA-Net: Dense Bundle Adjustment Networks ICLR 2019 Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design AISTATS 2019 Bayesian Functional Optimisation with Shape Prior AAAI 2019 Bayesian optimisation under uncertain inputs AISTATS 2019 Bayesian Optimization Meets Riemannian Manifolds in Robot Learning CoRL 2019 Bayesian Optimization of Composite Functions ICML 2019 Bayesian Optimization under Heavy-tailed Payoffs NeurIPS 2019 Bayesian Posterior Approximation via Greedy Particle Optimization AAAI 2019 Beating SGD Saturation with Tail-Averaging and Minibatching NeurIPS 2019 Benchmarking Approximate Inference Methods for Neural Structured Prediction NAACL 2019 Better generalization with less data using robust gradient descent ICML 2019 Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms NeurIPS 2019 Beyond Backprop: Online Alternating Minimization with Auxiliary Variables ICML 2019 Beyond BLEU: Training Neural Machine Translation with Semantic Similarity ACL 2019 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance COLT 2019 Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization NeurIPS 2019 Beyond the Single Neuron Convex Barrier for Neural Network Certification NeurIPS 2019 Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers ICLR 2019 Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation NAACL 2019 BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting AAAI 2019 Blended Matching Pursuit NeurIPS 2019 Blind Image Deblurring With Local Maximum Gradient Prior CVPR 2019 Block Coordinate Regularization by Denoising NeurIPS 2019 Block Stability for MAP Inference AISTATS 2019 BN-invariant Sharpness Regularizes the Training Model to Better Generalization IJCAI 2019