Timezone: »
Error bound, an inherent property of an optimization problem, has recently revived in the development of algorithms with improved global convergence without strong convexity. The most studied error bound is the quadratic error bound, which generalizes strong convexity and is satisfied by a large family of machine learning problems. Quadratic error bound have been leveraged to achieve linear convergence in many first-order methods including the stochastic variance reduced gradient (SVRG) method, which is one of the most important stochastic optimization methods in machine learning. However, the studies along this direction face the critical issue that the algorithms must depend on an unknown growth parameter (a generalization of strong convexity modulus) in the error bound. This parameter is difficult to estimate exactly and the algorithms choosing this parameter heuristically do not have theoretical convergence guarantee. To address this issue, we propose novel SVRG methods that automatically search for this unknown parameter on the fly of optimization while still obtain almost the same convergence rate as when this parameter is known. We also analyze the convergence property of SVRG methods under H\"{o}lderian error bound, which generalizes the quadratic error bound.
Author Information
Yi Xu (The University of Iowa)
Qihang Lin (University of Iowa)
Tianbao Yang (The University of Iowa)
More from the Same Authors
-
2021 : Practice-Consistent Analysis of Adam-Style Methods »
Zhishuai Guo · Yi Xu · Wotao Yin · Rong Jin · Tianbao Yang -
2021 : A Stochastic Momentum Method for Min-max Bilevel Optimization »
Quanqi Hu · Bokun Wang · Tianbao Yang -
2021 : A Unified DRO View of Multi-class Loss Functions with top-N Consistency »
Dixian Zhu · Tianbao Yang -
2021 : Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities »
Tianbao Yang -
2022 Spotlight: Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization »
Wei Jiang · Gang Li · Yibo Wang · Lijun Zhang · Tianbao Yang -
2022 Spotlight: Lightning Talks 6B-1 »
Yushun Zhang · Duc Nguyen · Jiancong Xiao · Wei Jiang · Yaohua Wang · Yilun Xu · Zhen LI · Anderson Ye Zhang · Ziming Liu · Fangyi Zhang · Gilles Stoltz · Congliang Chen · Gang Li · Yanbo Fan · Ruoyu Sun · Naichen Shi · Yibo Wang · Ming Lin · Max Tegmark · Lijun Zhang · Jue Wang · Ruoyu Sun · Tommi Jaakkola · Senzhang Wang · Zhi-Quan Luo · Xiuyu Sun · Zhi-Quan Luo · Tianbao Yang · Rong Jin -
2022 Spotlight: Lightning Talks 4A-2 »
Barakeel Fanseu Kamhoua · Hualin Zhang · Taiki Miyagawa · Tomoya Murata · Xin Lyu · Yan Dai · Elena Grigorescu · Zhipeng Tu · Lijun Zhang · Taiji Suzuki · Wei Jiang · Haipeng Luo · Lin Zhang · Xi Wang · Young-San Lin · Huan Xiong · Liyu Chen · Bin Gu · Jinfeng Yi · Yongqiang Chen · Sandeep Silwal · Yiguang Hong · Maoyuan Song · Lei Wang · Tianbao Yang · Han Yang · MA Kaili · Samson Zhou · Deming Yuan · Bo Han · Guodong Shi · Bo Li · James Cheng -
2022 Spotlight: Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor »
Lijun Zhang · Wei Jiang · Jinfeng Yi · Tianbao Yang -
2022 Poster: Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization »
Quanqi Hu · YONGJIAN ZHONG · Tianbao Yang -
2022 Poster: ProtoX: Explaining a Reinforcement Learning Agent via Prototyping »
Ronilo Ragodos · Tong Wang · Qihang Lin · Xun Zhou -
2022 Poster: Large-scale Optimization of Partial AUC in a Range of False Positive Rates »
Yao Yao · Qihang Lin · Tianbao Yang -
2022 Poster: Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor »
Lijun Zhang · Wei Jiang · Jinfeng Yi · Tianbao Yang -
2022 Poster: Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization »
Wei Jiang · Gang Li · Yibo Wang · Lijun Zhang · Tianbao Yang -
2021 Poster: Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning »
ZHENHUAN YANG · Yunwen Lei · Puyu Wang · Tianbao Yang · Yiming Ying -
2021 Poster: Revisiting Smoothed Online Learning »
Lijun Zhang · Wei Jiang · Shiyin Lu · Tianbao Yang -
2021 Poster: Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence »
Qi Qi · Youzhi Luo · Zhao Xu · Shuiwang Ji · Tianbao Yang -
2021 Poster: Online Convex Optimization with Continuous Switching Constraint »
Guanghui Wang · Yuanyu Wan · Tianbao Yang · Lijun Zhang -
2021 Poster: An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives »
Qi Qi · Zhishuai Guo · Yi Xu · Rong Jin · Tianbao Yang -
2020 Poster: Improved Schemes for Episodic Memory-based Lifelong Learning »
Yunhui Guo · Mingrui Liu · Tianbao Yang · Tajana S Rosing -
2020 Spotlight: Improved Schemes for Episodic Memory-based Lifelong Learning »
Yunhui Guo · Mingrui Liu · Tianbao Yang · Tajana S Rosing -
2020 Poster: A Decentralized Parallel Algorithm for Training Generative Adversarial Nets »
Mingrui Liu · Wei Zhang · Youssef Mroueh · Xiaodong Cui · Jarret Ross · Tianbao Yang · Payel Das -
2020 Poster: Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization »
Yan Yan · Yi Xu · Qihang Lin · Wei Liu · Tianbao Yang -
2019 Poster: Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems »
Yi Xu · Rong Jin · Tianbao Yang -
2019 Poster: Stagewise Training Accelerates Convergence of Testing Error Over SGD »
Zhuoning Yuan · Yan Yan · Rong Jin · Tianbao Yang -
2018 : Poster spotlight »
Tianbao Yang · Pavel Dvurechenskii · Panayotis Mertikopoulos · Hugo Berard -
2018 Poster: First-order Stochastic Algorithms for Escaping From Saddle Points in Almost Linear Time »
Yi Xu · Rong Jin · Tianbao Yang -
2018 Poster: Adaptive Negative Curvature Descent with Applications in Non-convex Optimization »
Mingrui Liu · Zhe Li · Xiaoyu Wang · Jinfeng Yi · Tianbao Yang -
2018 Poster: Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization »
Xiaoxuan Zhang · Mingrui Liu · Xun Zhou · Tianbao Yang -
2018 Poster: Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions »
Mingrui Liu · Xiaoxuan Zhang · Lijun Zhang · Rong Jin · Tianbao Yang -
2017 Poster: ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization »
Yi Xu · Mingrui Liu · Qihang Lin · Tianbao Yang -
2017 Poster: Improved Dynamic Regret for Non-degenerate Functions »
Lijun Zhang · Tianbao Yang · Jinfeng Yi · Rong Jin · Zhi-Hua Zhou -
2017 Poster: Adaptive Accelerated Gradient Converging Method under H\"{o}lderian Error Bound Condition »
Mingrui Liu · Tianbao Yang -
2016 Poster: Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than $O(1/\epsilon)$ »
Yi Xu · Yan Yan · Qihang Lin · Tianbao Yang -
2016 Poster: Improved Dropout for Shallow and Deep Learning »
Zhe Li · Boqing Gong · Tianbao Yang