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Xiangru Lian

13 papers · 2015–2021 · 4 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (20) πŸƒ Academic Marathon Β· Sprint 🌍 Conference Polyglot Β· Bronze πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🀝 Dynamic Duo (13) ❓ The Questioner πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (64)

Venues

ICML (5) NeurIPS (5) AISTATS (2) IJCAI (1)

Top co-authors

Ji Liu (13) Ce Zhang (4) Hanlin Tang (3) Wei Zhang (3) Cho-jui Hsieh (3) Huan Zhang (2) Yijun Huang (2) Xia Hu (1) Hsiang-Fu Yu (1) Ming Yan (1)

Research topics

Machine Learning (12) Optimization & Theory Β· Machine Learning (12) Mathematics & Optimization (8) Optimization (8) Deep Learning (4) Optimization & Theory Β· Deep Learning (4) Application Areas (2) Core Methods (1) Learning Types (1) Techniques (1)

Keywords

stochastic gradient descent (6) distributed learning (5) linear speedup (3) asynchronous parallel (3) non-convex optimization (2) communication efficiency (2) stochastic optimization (2) error compensation (2) deep neural network (2) decentralized optimization (2) variance reduction (2) asynchronous parallel optimization (2) linear convergence (2) gradient descent (2) compositional optimization (2) parallel computing (1) batch normalization (1) neural network optimization (1) distributed optimization (1) stochastic gradient (1)

Papers

1-bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed ICML 2021 DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning ICML 2021 DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression ICML 2019 Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent NeurIPS 2019 Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019 D^2: Decentralized Training over Decentralized Data ICML 2018 Asynchronous Decentralized Parallel Stochastic Gradient Descent ICML 2018 Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NeurIPS 2017 Finite-sum Composition Optimization via Variance Reduced Gradient Descent AISTATS 2017 A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order NeurIPS 2016 Asynchronous Parallel Greedy Coordinate Descent NeurIPS 2016 Staleness-Aware Async-SGD for Distributed Deep Learning IJCAI 2016 Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization NeurIPS 2015