bregman divergence

Unified Interpretation of Softmax Cross-Entropy and Negative Sampling: With Case Study for Knowledge Graph Embedding ACL 2021 A Unified Statistically Efficient Estimation Framework for Unnormalized Models AISTATS 2020 Deep Divergence Learning ICML 2020 Dual-Free Stochastic Decentralized Optimization with Variance Reduction NeurIPS 2020 Federated Patient Hashing AAAI 2020 Learning to Approximate a Bregman Divergence NeurIPS 2020 Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming ICML 2020 Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications IJCAI 2020 Memoryless Sequences for General Losses JMLR 2020 On the consistency of top-k surrogate losses ICML 2020 Supervised learning: no loss no cry ICML 2020 An adaptive Mirror-Prox method for variational inequalities with singular operators NeurIPS 2019 Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization NeurIPS 2019 Divergence-Augmented Policy Optimization NeurIPS 2019 Robust Bi-Tempered Logistic Loss Based on Bregman Divergences NeurIPS 2019 Inductive Two-Layer Modeling with Parametric Bregman Transfer ICML 2018 Regularized Optimal Transport and the Rot Mover's Distance JMLR 2018 Toward Designing Convergent Deep Operator Splitting Methods for Task-specific Nonconvex Optimization IJCAI 2018 Boundary Crossing for General Exponential Families ALT 2017 Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction NeurIPS 2017 Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$ COLT 2017 A scaled Bregman theorem with applications NeurIPS 2016 Clustering with Bregman Divergences: an Asymptotic Analysis NeurIPS 2016 Linking losses for density ratio and class-probability estimation ICML 2016 Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016