Mathematics & Optimization

Bayesian inference on random simple graphs with power law degree distributions ICML 2017 Bayesian Learning of Dynamic Multilayer Networks JMLR 2017 Bayesian Network Learning via Topological Order JMLR 2017 Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract) IJCAI 2017 Bayesian Optimization with Gradients NeurIPS 2017 Bayesian Tensor Regression JMLR 2017 Bernoulli Rank-1 Bandits for Click Feedback IJCAI 2017 Best Response Regression NeurIPS 2017 Beta calibration: a well-founded and easily implemented improvement on logistic calibration for binary classifiers AISTATS 2017 Between Reading Time and Syntactic/Semantic Categories IJCNLP 2017 Beyond Forks: Finding and Ranking Star Factorings for Decoupled Search IJCAI 2017 Beyond the Nystrom Approximation: Speeding up Spectral Clustering using Uniform Sampling and Weighted Kernel k-means IJCAI 2017 Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization NeurIPS 2017 Binary Constraint Preserving Graph Matching CVPR 2017 Black-box Importance Sampling AISTATS 2017 Boundary Crossing for General Exponential Families ALT 2017 Breaking Locality Accelerates Block Gauss-Seidel ICML 2017 Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization NeurIPS 2017 Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction NeurIPS 2017 Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NeurIPS 2017 CANE: Context-Aware Network Embedding for Relation Modeling ACL 2017 Capacity Releasing Diffusion for Speed and Locality ICML 2017 Cardinality Encodings for Graph Optimization Problems IJCAI 2017 CCEHC: An Efficient Local Search Algorithm for Weighted Partial Maximum Satisfiability (Extended Abstract) IJCAI 2017 Certifiably Optimal Low Rank Factor Analysis JMLR 2017