Mathematics & Optimization

Data-dependent compression of random features for large-scale kernel approximation AISTATS 2019 Data-driven Estimation of Sinusoid Frequencies NeurIPS 2019 DBSCAN: Optimal Rates For Density-Based Cluster Estimation JMLR 2019 Deanonymizing Social Networks Using Structural Information IJCAI 2019 Decentralized Cooperative Stochastic Bandits NeurIPS 2019 Decentralized Exploration in Multi-Armed Bandits ICML 2019 Decentralized Gradient Tracking for Continuous DR-Submodular Maximization AISTATS 2019 Decentralized Optimization with Edge Sampling IJCAI 2019 Decentralized sketching of low rank matrices NeurIPS 2019 Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication ICML 2019 Deep Bayesian Optimization on Attributed Graphs AAAI 2019 Deep Bayesian Trust: A Dominant and Fair Incentive Mechanism for Crowd AAAI 2019 Deep Compressed Sensing ICML 2019 Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data AAAI 2019 Deep Signature Transforms NeurIPS 2019 Deep Tensor ADMM-Net for Snapshot Compressive Imaging ICCV 2019 Deep Value Model Predictive Control CoRL 2019 Deformable Surface Tracking by Graph Matching ICCV 2019 DepDist: Surface realization via regex and learned dependency-distance tolerance EMNLP 2019 Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning NeurIPS 2019 Determinantal Point Processes for Coresets JMLR 2019 Determining Solvability in the Birds of a Feather Card Game AAAI 2019 Determining the Number of Latent Factors in Statistical Multi-Relational Learning JMLR 2019 DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation NeurIPS 2019 DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters NeurIPS 2019