Mathematics & Optimization

Sample Amplification: Increasing Dataset Size even when Learning is Impossible ICML 2020 Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors ICML 2020 Sample complexity bounds for localized sketching AISTATS 2020 Sample Complexity of Kalman Filtering for Unknown Systems L4DC 2020 Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining NeurIPS 2020 Sampling from a k-DPP without looking at all items NeurIPS 2020 Sampling Random Chordal Graphs by MCMC (Student Abstract) AAAI 2020 Sampling Without Compromising Accuracy in Adaptive Data Analysis ALT 2020 Scalable and Probabilistically Complete Planning for Robotic Spatial Extrusion RSS 2020 Scalable Approximate MCMC Algorithms for the Horseshoe Prior JMLR 2020 Scalable Bayesian Network Structure Learning via Maximum Acyclic Subgraph PGM 2020 Scalable Calibration of Affinity Matrices from Incomplete Observations ACML 2020 Scalable Nearest Neighbor Search for Optimal Transport ICML 2020 Scalable Nonparametric Factorization for High-Order Interaction Events AISTATS 2020 Scaling Hidden Markov Language Models EMNLP 2020 Scaling Up AND/OR Abstraction Sampling IJCAI 2020 Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing ICML 2020 Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension ICML 2020 Scikit-network: Graph Analysis in Python JMLR 2020 Script Induction as Association Rule Mining ACL 2020 Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations COLT 2020 Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking NeurIPS 2020 Secretary and Online Matching Problems with Machine Learned Advice NeurIPS 2020 Selecting Portfolios Directly Using Recurrent Reinforcement Learning (Student Abstract) AAAI 2020 Selecting Voting Locations for Fun and Profit IJCAI 2020