Optimization

Sparse and low-rank multivariate Hawkes processes JMLR 2020 Sparse and Low-rank Tensor Estimation via Cubic Sketchings AISTATS 2020 Sparse Coding with Gated Learned ISTA ICLR 2020 Sparse Learning with CART NeurIPS 2020 Sparse Optimization for Unsupervised Extractive Summarization of Long Documents with the Frank-Wolfe Algorithm EMNLP 2020 Sparse Shrunk Additive Models ICML 2020 Sparse Symplectically Integrated Neural Networks NeurIPS 2020 Spatio-temporal alignments: Optimal transport through space and time AISTATS 2020 Spatiotemporal Fusion in 3D CNNs: A Probabilistic View CVPR 2020 Spectral Deconfounding via Perturbed Sparse Linear Models JMLR 2020 Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory ICML 2020 Speeding Up Incomplete GDL-based Algorithms for Multi-agent Optimization with Dense Local Utilities IJCAI 2020 Spike-based causal inference for weight alignment ICLR 2020 SQE: a Self Quality Evaluation Metric for Parameters Optimization in Multi-Object Tracking CVPR 2020 Stabilizing Differentiable Architecture Search via Perturbation-based Regularization ICML 2020 Stable Intrinsic Auto-Calibration from Fundamental Matrices of Devices with Uncorrelated Camera Parameters WACV 2020 Stable Learning via Sample Reweighting AAAI 2020 Stable Regression: On the Power of Optimization over Randomization JMLR 2020 Statistical and Computational Rates in Graph Logistic Regression AISTATS 2020 Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization ICML 2020 Steady-State Policy Synthesis in Multichain Markov Decision Processes IJCAI 2020 Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning AISTATS 2020 Stochastic Approximate Gradient Descent via the Langevin Algorithm AAAI 2020 Stochastic AUC Maximization with Deep Neural Networks ICLR 2020 Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020