Lijun Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Efficient Stochastic Approximation of Minimax Excess Risk Optimization.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Nearly Optimal Regret for Decentralized Online Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Non-stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Efficient Stochastic Approximation of Minimax Excess Risk Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Stochastic Approximation Approaches to Group Distributionally Robust Optimization.

[BibT_eX]

[DOI]

CoRR, 2023

Stochastic Graphical Bandits with Heavy-Tailed Rewards.

[BibT_eX]

[DOI]

Yutian Gou

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Stochastic Approximation Approaches to Group Distributionally Robust Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Learning Unnormalized Statistical Models via Compositional Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Improved Dynamic Regret for Online Frank-Wolfe.

[BibT_eX]

[DOI]

Mingli Song

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Distributed Projection-Free Online Learning for Smooth and Convex Losses.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Prediction With Unpredictable Feature Evolution.

[BibT_eX]

[DOI]

Bo-Jian Hou

IEEE Trans. Neural Networks Learn. Syst., 2022

Efficient Adaptive Online Learning via Frequent Directions.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Online strongly convex optimization with unknown delays.

[BibT_eX]

[DOI]

Mach. Learn., 2022

Projection-free Distributed Online Learning with Sublinear Communication Complexity.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Online Frank-Wolfe with Unknown Delays.

[BibT_eX]

[DOI]

CoRR, 2022

Strongly adaptive online learning over partial intervals.

[BibT_eX]

[DOI]

Sci. China Inf. Sci., 2022

Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization.

[BibT_eX]

[DOI]

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Adaptive Feature Generation for Online Continual Learning from Imbalanced Data.

[BibT_eX]

[DOI]

Yingchun Jian

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Frank-Wolfe with Arbitrary Delays.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Methods for Non-stationary Online Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Simple yet Universal Strategy for Online Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Optimal Algorithms for Stochastic Multi-Level Compositional Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Momentum Accelerates the Convergence of Stochastic AUPRC Maximization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Charging Task Scheduling for Directional Wireless Charger Networks.

[BibT_eX]

[DOI]

IEEE Trans. Mob. Comput., 2021

Learning With Feature Evolvable Streams.

[BibT_eX]

[DOI]

Bo-Jian Hou

IEEE Trans. Knowl. Data Eng., 2021

Bandit Convex Optimization in Non-stationary Environments.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

Projection-free Distributed Online Learning with Strongly Convex Losses.

[BibT_eX]

[DOI]

CoRR, 2021

Non-stationary Linear Bandits Revisited.

[BibT_eX]

[DOI]

Peng Zhao

CoRR, 2021

Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Revisiting Smoothed Online Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Convex Optimization with Continuous Switching Constraint.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improved Analysis for Dynamic Regret of Strongly Convex and Smooth Functions.

[BibT_eX]

[DOI]

Peng Zhao

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Deep Unified Cross-Modality Hashing by Pairwise Data Alignment.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning to Augment Imbalanced Data for Re-ranking Models.

[BibT_eX]

[DOI]

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Projection-free Online Learning over Strongly Convex Sets.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Approximate Multiplication of Sparse Matrices with Limited Space.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Projection-free Online Learning in Dynamic Environments.

[BibT_eX]

[DOI]

Bo Xue

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Stochastic Graphical Bandits with Adversarial Corruptions.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Stochastic Bandits with Graph Feedback in Non-Stationary Environments.

[BibT_eX]

[DOI]

Yao Hu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2020

High-dimensional model recovery from random sketched data by exploring intrinsic sparsity.

[BibT_eX]

[DOI]

Mach. Learn., 2020

Accelerating adaptive online learning by matrix approximation.

[BibT_eX]

[DOI]

Int. J. Data Sci. Anal., 2020

An Adversarial Domain Adaptation Network For Cross-Domain Fine-Grained Recognition.

[BibT_eX]

[DOI]

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Piecewise Hashing: A Deep Hashing Method for Large-Scale Fine-Grained Search.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition and Computer Vision - Third Chinese Conference, 2020

Dynamic Regret of Convex and Smooth Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Searching Privately by Imperceptible Lying: A Novel Private Hashing Method with Differential Privacy.

[BibT_eX]

[DOI]

Yimu Wang

Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Online Learning in Changing Environments.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Stochastic Optimization for Non-convex Inf-Projection Problems.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

SAdam: A Variant of Adam for Strongly Convex Functions.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Improving Multi-Scenario Learning to Rank in E-commerce by Exploiting Task Relationships in the Label Space.

[BibT_eX]

[DOI]

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

A Simple Approach for Non-stationary Linear Bandits.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Minimizing Dynamic Regret and Adaptive Regret Simultaneously.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

A simple homotopy proximal mapping algorithm for compressive sensing.

[BibT_eX]

[DOI]

Mach. Learn., 2019

Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2019

More Adaptive Algorithms for Tracking the Best Expert.

[BibT_eX]

[DOI]

CoRR, 2019

Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions.

[BibT_eX]

[DOI]

CoRR, 2019

SAdam: A Variant of Adam for Strongly Convex Functions.

[BibT_eX]

[DOI]

CoRR, 2019

Stochastic Primal-Dual Algorithms with Faster Convergence than O(1/√T) for Problems without Bilinear Structure.

[BibT_eX]

[DOI]

CoRR, 2019

Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Multi-Objective Generalized Linear Bandits.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Adaptive Regret of Convex and Smooth Functions.

[BibT_eX]

[DOI]

Tie-Yan Liu

Proceedings of the 36th International Conference on Machine Learning, 2019

Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2019

2018

Matrix Completion from Non-Uniformly Sampled Entries.

[BibT_eX]

[DOI]

CoRR, 2018

𝓁<sub>1</sub>-regression with Heavy-tailed Distributions.

[BibT_eX]

[DOI]

CoRR, 2018

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2018

\ell_1-regression with Heavy-tailed Distributions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Adaptive Online Learning in Dynamic Environments.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Minimizing Adaptive Regret with One Gradient per Iteration.

[BibT_eX]

[DOI]

Dakuan Zhao

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Efficient Adaptive Online Learning via Frequent Directions.

[BibT_eX]

[DOI]

Nan Wei

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Dynamic Regret of Strongly Adaptive Methods.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Query-Efficient Black-Box Attack by Active Learning.

[BibT_eX]

[DOI]

Pengcheng Li

Proceedings of the IEEE International Conference on Data Mining, 2018

A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer.

[BibT_eX]

[DOI]

Zhe Li

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Sparse Learning with Stochastic Composite Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Non-redundant multiple clustering by nonnegative matrix factorization.

[BibT_eX]

[DOI]

Sen Yang

Mach. Learn., 2017

Positive-Unlabeled Demand-Aware Recommendation.

[BibT_eX]

[DOI]

CoRR, 2017

Strongly Adaptive Regret Implies Optimally Dynamic Regret.

[BibT_eX]

[DOI]

CoRR, 2017

Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n<sup>2</sup>)-type of Risk Bounds.

[BibT_eX]

[DOI]

CoRR, 2017

Scalable Demand-Aware Recommendation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Improved Dynamic Regret for Non-degenerate Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Semi-Supervised Deep Hashing with a Bipartite Graph.

[BibT_eX]

[DOI]

Xinyu Yan

Wu-Jun Li

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

SVD-free Convex-Concave Approaches for Nuclear Norm Regularization.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Storage Fit Learning with Unlabeled Data.

[BibT_eX]

[DOI]

Bo-Jian Hou

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates.

[BibT_eX]

[DOI]

Qihang Lin

Proceedings of the 34th International Conference on Machine Learning, 2017

Empirical Risk Minimization for Stochastic Convex Optimization: $O(1/n)$- and $O(1/n^2)$-type of Risk Bounds.

[BibT_eX]

[DOI]

Proceedings of the 30th Conference on Learning Theory, 2017

Efficient Stochastic Optimization for Low-Rank Distance Metric Learning.

[BibT_eX]

[DOI]

Jie Zhang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Efficient Non-Oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Graph Regularized Feature Selection with Data Reconstruction.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2016

A-Optimal Projection for Image Representation.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2016

Online kernel learning with nearly constant support vectors.

[BibT_eX]

[DOI]

Neurocomputing, 2016

Improved dynamic regret for non-degeneracy functions.

[BibT_eX]

[DOI]

CoRR, 2016

Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Online Stochastic Linear Optimization under One-bit Feedback.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

Sparse Learning for Large-Scale and High-Dimensional Data: A Randomized Convex-Concave Optimization Approach.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

Accelerated Sparse Linear Regression via Random Projection.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Fast and Accurate Refined Nyström-Based Kernel SVM.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Stochastic Optimization for Kernel PCA.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Expert Finding for Question Answering via Graph Regularized Matrix Completion.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2015

Multi-View Concept Learning for Data Representation.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2015

Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD).

[BibT_eX]

[DOI]

Mach. Learn., 2015

Graph-based local concept coordinate factorization.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2015

Unsupervised document summarization from data reconstruction perspective.

[BibT_eX]

[DOI]

Neurocomputing, 2015

Fast Sparse Least-Squares Regression with Non-Asymptotic Guarantees.

[BibT_eX]

[DOI]

CoRR, 2015

Towards Making High Dimensional Distance Metric Learning Practical.

[BibT_eX]

[DOI]

CoRR, 2015

Stochastic Proximal Gradient Descent for Nuclear Norm Regularization.

[BibT_eX]

[DOI]

CoRR, 2015

Online Stochastic Linear Optimization under One-bit Feedback.

[BibT_eX]

[DOI]

CoRR, 2015

Analysis of Nuclear Norm Regularization for Full-rank Matrix Completion.

[BibT_eX]

[DOI]

CoRR, 2015

An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints.

[BibT_eX]

[DOI]

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Theory of Dual-sparse Regularized Randomized Reduction.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

An Explicit Sampling Dependent Spectral Error Bound for Column Subset Selection.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization.

[BibT_eX]

[DOI]

Proceedings of The 28th Conference on Learning Theory, 2015

A Simple Homotopy Algorithm for Compressive Sensing.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Online Bandit Learning for a Special Class of Non-Convex Losses.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Random Projections for Classification: A Recovery Approach.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2014

A Simple Homotopy Proximal Mapping for Compressive Sensing.

[BibT_eX]

[DOI]

CoRR, 2014

Binary Excess Risk for Smooth Convex Surrogates.

[BibT_eX]

[DOI]

CoRR, 2014

A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Efficient Algorithms for Robust One-bit Compressive Sensing.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Sparse Learning for Stochastic Composite Optimization.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Efficient Stochastic Gradient Descent for Strongly Convex Optimization

[BibT_eX]

[DOI]

CoRR, 2013

Improving the Minimax Rate of Active Learning.

[BibT_eX]

[DOI]

CoRR, 2013

Mixed Optimization for Smooth Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Linear Convergence with Condition Number Independent Access of Full Gradients.

[BibT_eX]

[DOI]