Hassan Rafique

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All published works

Action	Title	Year	Authors
+ PDF Chat	Weakly-convex–concave min–max optimization: provable algorithms and applications in machine learning	2021	Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang
+	Model-Agnostic Linear Competitors -- When Interpretable Models Compete and Collaborate with Black-Box Models	2019	Hassan Rafique Tong Wang Qihang Lin
+	Solving Weakly-Convex-Weakly-Concave Saddle-Point Problems as Successive Strongly Monotone Variational Inequalities	2018	Qihang Lin Mingrui Liu Hassan Rafique Tianbao Yang
+	Solving Weakly-Convex-Weakly-Concave Saddle-Point Problems as Weakly-Monotone Variational Inequality	2018	Qihang Lin Mingrui Liu Hassan Rafique Tianbao Yang
+	First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems	2018	Mingrui Liu Hassan Rafique Qihang Lin Tianbao Yang
+	Non-Convex Min-Max Optimization: Provable Algorithms and Applications in Machine Learning	2018	Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang
+	Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning	2018	Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang
+	First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems	2018	Mingrui Liu Hassan Rafique Qihang Lin Tianbao Yang

Common Coauthors

Coauthor	Papers Together
Qihang Lin	8
Tianbao Yang	7
Mingrui Liu	4
Mingrui Liu	3
Tong Wang	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Certifying Some Distributional Robustness with Principled Adversarial Training	2017	Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi	3
+ PDF Chat	Stochastic Model-Based Minimization of Weakly Convex Functions	2019	Damek Davis Dmitriy Drusvyatskiy	3
+	Robust Stochastic Approximation Approach to Stochastic Programming	2009	Arkadi Nemirovski Anatoli Juditsky Guanghui Lan Alexander Shapiro	3
+	Stochastic subgradient method converges at the rate $O(k^{-1/4})$ on weakly convex functions	2018	Damek Davis Dmitriy Drusvyatskiy	3
+ PDF Chat	Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems	2019	Damek Davis Benjamin Grimmer	3
+	Stochastic Variance Reduction Methods for Saddle-Point Problems	2016	Palaniappan Balamurugan Francis Bach	2
+ PDF Chat	Accelerated gradient methods for nonconvex nonlinear and stochastic programming	2015	Saeed Ghadimi Guanghui Lan	2
+ PDF Chat	Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming	2013	Saeed Ghadimi Guanghui Lan	2
+ PDF Chat	Efficiency of minimizing compositions of convex functions and smooth maps	2018	Dmitriy Drusvyatskiy Courtney Paquette	2
+	Monotone Operators and the Proximal Point Algorithm	1976	R. T. Rockafellar	2
+	Fast incremental method for smooth nonconvex optimization	2016	Sashank J. Reddi Suvrit Sra Barnabás Póczos Alex Smola	2
+ PDF Chat	A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging	2010	Antonin Chambolle Thomas Pock	2
+ PDF Chat	Prox-Method with Rate of Convergence <i>O</i>(1/<i>t</i>) for Variational Inequalities with Lipschitz Continuous Monotone Operators and Smooth Convex-Concave Saddle Point Problems	2004	Arkadi Nemirovski	2
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	2
+	Unified Convergence Analysis of Stochastic Momentum Methods for Convex and Non-convex Optimization	2016	Tianbao Yang Qihang Lin Zhe Li	2
+	Learning with Non-Convex Truncated Losses by SGD	2018	Yi Xu Shenghuo Zhu Sen Yang Chi Zhang Rong Jin Tianbao Yang	2
+	On the Convergence Rate of Stochastic Mirror Descent for Nonsmooth Nonconvex Optimization	2018	Siqi Zhang Niao He	2
+	Efficiency of minimizing compositions of convex functions and smooth maps	2016	Dmitriy Drusvyatskiy Courtney Paquette	1
+ PDF Chat	Extragradient Method with Variance Reduction for Stochastic Variational Inequalities	2017	Alfredo N. Iusem A. Jofré Roberto I. Oliveira Philip Thompson	1
+	Learning with Average Top-k Loss	2017	Yanbo Fan Siwei Lyu Yiming Ying Bao-Gang Hu	1
+	Towards Deep Learning Models Resistant to Adversarial Attacks	2017	Aleksander Mądry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu	1
+	Interpretable and Explorable Approximations of Black Box Models	2017	Himabindu Lakkaraju Ece Kamar Rich Caruana Jure Leskovec	1
+	Natasha: Faster Non-Convex Stochastic Optimization Via Strongly Non-Convex Parameter	2017	Zeyuan Allen-Zhu	1
+	Robust Optimization for Non-Convex Objectives	2017	Robert F. Chen Brendan Lucier Yaron Singer Vasilis Syrgkanis	1
+	The proximal point method revisited	2017	Dmitriy Drusvyatskiy	1
+	On the Convergence of Adam and Beyond	2019	Sashank J. Reddi Satyen Kale Sanjiv Kumar	1
+	A Variational Inequality Perspective on Generative Adversarial Networks	2018	Gauthier Gidel Hugo Berard Gaëtan Vignoud Pascal Vincent Simon Lacoste-Julien	1
+	Complexity of finding near-stationary points of convex functions stochastically	2018	Damek Davis Dmitriy Drusvyatskiy	1
+	Robust Optimization over Multiple Domains	2018	Qi Qian Shenghuo Zhu Jiasheng Tang Rong Jin Baigui Sun Hao Li	1
+	Level-Set Methods for Finite-Sum Constrained Convex Optimization	2018	Qihang Lin Runchao Ma Tianbao Yang	1
+	SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation	2017	Bo Dai Albert Shaw Lihong Li Lin Xiao Niao He Zhen Liu Jianshu Chen Le Song	1
+	Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions.	2018	Zaiyi Chen Zhuoning Yuan Jinfeng Yi Bowen Zhou Enhong Chen Tianbao Yang	1
+	Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile	2018	Panayotis Mertikopoulos Bruno Lecouat Houssam Zenati Chuan-Sheng Foo Vijay Chandrasekhar Georgios Piliouras	1
+	Non-Convex Min-Max Optimization: Provable Algorithms and Applications in Machine Learning	2018	Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang	1
+	An Interpretable Model with Globally Consistent Explanations for Credit Risk	2018	Chaofan Chen Kangcheng Lin Cynthia Rudin Yaron Shaposhnik Sijia Wang Tong Wang	1
+	Variance-based Regularization with Convex Objectives	2017	Hongseok Namkoong John C. Duchi	1
+	Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods	2019	Maher Nouiehed Maziar Sanjabi Tianjian Huang Jason D. Lee Meisam Razaviyayn	1
+	Efficient Algorithms for Smooth Minimax Optimization	2019	Kiran Koshy Thekumparampil Prateek Jain Praneeth Netrapalli Sewoong Oh	1
+ PDF Chat	Saddle-Point Dynamics: Conditions for Asymptotic Stability of Saddle Points	2017	Ashish Cherukuri Bahman Gharesifard Jorge Cortés	1
+	A Unified Approach to Interpreting Model Predictions	2017	Scott Lundberg Su‐In Lee	1
+ PDF Chat	Robust Optimization over Multiple Domains	2019	Qi Qian Shenghuo Zhu Jiasheng Tang Rong Jin Baigui Sun Hao Li	1
+	An Alternative View: When Does SGD Escape Local Minima?	2018	Robert Kleinberg Yuanzhi Li Yuan Yang	1
+	Improved Techniques for Training GANs	2016	Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen	1
+	Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions	2018	Zaiyi Chen Zhuoning Yuan Jinfeng Yi Bowen Zhou Enhong Chen Tianbao Yang	1
+	Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations	2017	Andrew Slavin Ross Michael C. Hughes Finale Doshi‐Velez	1
+	Statistical consistency and asymptotic normality for high-dimensional robust $M$-estimators	2017	Po‐Ling Loh	1
+	Stochastic Variance Reduction for Nonconvex Optimization	2016	Sashank J. Reddi Ahmed Hefny Suvrit Sra Barnabás Póczos Alex Smola	1
+	The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization	2018	Constantinos Daskalakis Ioannis Panageas	1
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	1
+	Gradient descent GAN optimization is locally stable	2017	Vaishnavh Nagarajan J. Zico Kolter	1