large-scale learning

SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations NeurIPS 2023 Learning Distributionally Robust Models at Scale via Composite Optimization ICLR 2022 Similarity Search for Efficient Active Learning and Search of Rare Concepts AAAI 2022 Kernel Methods Through the Roof: Handling Billions of Points Efficiently NeurIPS 2020 Detecting 11K Classes: Large Scale Object Detection Without Fine-Grained Bounding Boxes ICCV 2019 High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks NeurIPS 2019 Algorithms or Actions? A Study in Large-Scale Reinforcement Learning IJCAI 2018 MISSION: Ultra Large-Scale Feature Selection using Count-Sketches ICML 2018 Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization IJCAI 2017 FALKON: An Optimal Large Scale Kernel Method NeurIPS 2017 Hierarchically-partitioned Gaussian Process Approximation AISTATS 2017 Spatial Decompositions for Large Scale SVMs AISTATS 2017 Importance Sampling Tree for Large-scale Empirical Expectation ICML 2016 Large Scale Online Kernel Learning JMLR 2016 NYTRO: When Subsampling Meets Early Stopping AISTATS 2016 One-Pass Multi-View Learning ACML 2015 Spherical Random Features for Polynomial Kernels NeurIPS 2015 Stochastic Expectation Propagation NeurIPS 2015 Adaptive Sampling for Large Scale Boosting JMLR 2014 Discrete Chebyshev Classifiers ICML 2014 large scale canonical correlation analysis with iterative least squares NeurIPS 2014 LIBOL: A Library for Online Learning Algorithms JMLR 2014 Linear Time Solver for Primal SVM ICML 2014 Three Guidelines of Online Learning for Large-Scale Visual Recognition CVPR 2014 Communication-Efficient Algorithms for Statistical Optimization JMLR 2013