Optimization

Learning Logistic Circuits AAAI 2019 Learning Neural PDE Solvers with Convergence Guarantees ICLR 2019 Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks NeurIPS 2019 Learning One-hidden-layer Neural Networks under General Input Distributions AISTATS 2019 Learning One-hidden-layer ReLU Networks via Gradient Descent AISTATS 2019 Learning Optimal Classification Trees Using a Binary Linear Program Formulation AAAI 2019 Learning Optimal Linear Regularizers ICML 2019 Learning Optimized Risk Scores JMLR 2019 Learning Parametric Constraints in High Dimensions from Demonstrations CoRL 2019 Learning Positive Functions with Pseudo Mirror Descent NeurIPS 2019 Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization ACL 2019 Learning Resource Allocation and Pricing for Cloud Profit Maximization AAAI 2019 Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances IJCAI 2019 Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning NeurIPS 2019 Learning Sparse Distributions using Iterative Hard Thresholding NeurIPS 2019 Learning step sizes for unfolded sparse coding NeurIPS 2019 Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method IJCAI 2019 Learning Swarm Behaviors using Grammatical Evolution and Behavior Trees IJCAI 2019 Learning to bid in revenue-maximizing auctions ICML 2019 Learning to Find Common Objects Across Few Image Collections ICCV 2019 Learning-to-Learn Stochastic Gradient Descent with Biased Regularization ICML 2019 Learning to Match via Inverse Optimal Transport JMLR 2019 Learning to Optimize in Swarms NeurIPS 2019 Learning to Perform Local Rewriting for Combinatorial Optimization NeurIPS 2019 Learning to Route in Similarity Graphs ICML 2019