← Authors

Qihang Lin

29 papers · 2012–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (4) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (12) 🌈 Renaissance Researcher (5) 🧭 Keyword Pioneer πŸƒ Academic Marathon (13) 🀝 Dynamic Duo (16) πŸ† Keyword Champion πŸ”¬ Deep Specialist (17) πŸ—ƒοΈ Keyword Collector (54) πŸ”₯ Unstoppable (12) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ“ˆ Trend Setter πŸ’Ž Century Club (29)

Conferences

JMLR (9) NIPS (9) ICML (8) IJCAI (2) AISTATS (1)

Top co-authors

Tianbao Yang (16) Yi Xu (6) Xi Chen (5) Yan Yan (3) Tong Wang (3) Lin Xiao (3) Runchao Ma (3) Negar Soheili (2) Yao Yao (2) Mingrui Liu (2)

Keywords

convex optimization (8) stochastic optimization (7) iteration complexity (4) convergence rate (4) subgradient method (4) first-order method (3) markov decision process (3) knowledge gradient (3) stochastic variance reduced gradient (3) budget allocation (3) min-max optimization (2) deep neural network (2) black-box model (2) linear convergence (2) bayesian optimization (2) proximal gradient method (2) strongly convex (2) stochastic convex optimization (2) distributed optimization (2) empirical risk minimization (2)

Papers

An Adaptive Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition JMLR 2025
Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization NIPS 2023
Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints AISTATS 2023
ProtoX: Explaining a Reinforcement Learning Agent via Prototyping NIPS 2022
Large-scale Optimization of Partial AUC in a Range of False Positive Rates NIPS 2022
Hybrid Predictive Models: When an Interpretable Model Collaborates with a Black-box Model JMLR 2021
First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems JMLR 2021
Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints ICML 2020
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints JMLR 2020
Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max Optimization NIPS 2020
Bayesian Decision Process for Budget-efficient Crowdsourced Clustering IJCAI 2020
Transparency Promotion with Model-Agnostic Linear Competitors ICML 2020
DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization JMLR 2019
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence ICML 2019
Level-Set Methods for Finite-Sum Constrained Convex Optimization ICML 2018
A Unified Analysis of Stochastic Momentum Methods for Deep Learning IJCAI 2018
RSG: Beating Subgradient Method without Smoothness and Strong Convexity JMLR 2018
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence ICML 2017
Distributed Stochastic Variance Reduced Gradient Methods by Sampling Extra Data with Replacement JMLR 2017
ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization NIPS 2017
Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter NIPS 2017
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates ICML 2017
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than $O(1/\epsilon)$ NIPS 2016
Bayesian Decision Process for Cost-Efficient Dynamic Ranking via Crowdsourcing JMLR 2016
Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling JMLR 2015
An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization ICML 2014
An Accelerated Proximal Coordinate Gradient Method NIPS 2014
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing ICML 2013
Optimal Regularized Dual Averaging Methods for Stochastic Optimization NIPS 2012