Lin Xiao
36 papers · 2009–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge π Conference Polyglot (9) π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (16)
πΊοΈ
Taxonomy Completionist
(52)
π£
Hot Topic Early Bird
π
Interdisciplinary Bridge
πΊ
Lone Wolf
(3)
π¬
Deep Specialist
(17)
π
Keyword Champion
(2)
π
Grand Slam
ποΈ
Keyword Collector
(155)
π
Trend Setter
π
Century Club
(36)
π₯
Unstoppable
(7)
β‘
Prolific Year
(7)
Conferences
NIPS (10)
ICML (9)
JMLR (6)
AAAI (3)
ACL (2)
EMNLP (2)
ICLR (2)
ACML (1)
IJCNLP (1)
Top co-authors
Keywords
stochastic optimization
(7)
convex optimization
(6)
convergence rate
(4)
empirical risk minimization
(4)
document representation
(3)
variance reduction
(3)
distributed optimization
(3)
multi-label text classification
(3)
sample complexity
(3)
stochastic gradient descent
(3)
linear convergence
(3)
nonconvex optimization
(3)
strong convexity
(3)
multi-label classification
(3)
self-attention mechanism
(2)
coordinate descent
(2)
strongly convex
(2)
stochastic gradient
(2)
convergence analysis
(2)
latent dirichlet allocation
(2)
Papers
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games
ICML 2025
PARQ: Piecewise-Affine Regularized Quantization
ICML 2025
Label-Specific Feature Augmentation for Long-Tailed Multi-Label Text Classification
AAAI 2023
Linear Convergence of Natural Policy Gradient Methods with Log-Linear Policies
ICLR 2023
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
ICLR 2023
On the Convergence Rates of Policy Gradient Methods
JMLR 2022
BiT: Robustly Binarized Multi-distilled Transformer
NIPS 2022
On Continual Model Refinement in Out-of-Distribution Data Streams
ACL 2022
Federated Learning with Partial Model Personalization
ICML 2022
Does Head Label Help for Long-Tailed Multi-Label Text Classification
AAAI 2021
From Low Probability to High Confidence in Stochastic Convex Optimization
JMLR 2021
Hybrid Summarization with Semantic Weighting Reward and Latent Structure Detector
ACML 2021
Importance Estimation from Multiple Perspectives for Keyphrase Extraction
EMNLP 2021
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
ICML 2020
Hyperbolic Interaction Model for Hierarchical Multi-Label Classification
AAAI 2020
Hyperbolic Capsule Networks for Multi-Label Classification
ACL 2020
DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization
JMLR 2019
Label-Specific Document Representation for Multi-Label Text Classification
EMNLP 2019
A Composite Randomized Incremental Gradient Method
ICML 2019
Label-Specific Document Representation for Multi-Label Text Classification
IJCNLP 2019
Understanding the Role of Momentum in Stochastic Gradient Methods
NIPS 2019
A Stochastic Composite Gradient Method with Incremental Variance Reduction
NIPS 2019
Using Statistics to Automate Stochastic Optimization
NIPS 2019
Learning SMaLL Predictors
NIPS 2018
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
ICML 2018
Coupled Variational Bayes via Optimization Embedding
NIPS 2018
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
ICML 2017
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
JMLR 2017
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes
NIPS 2017
Stochastic Variance Reduction Methods for Policy Evaluation
ICML 2017
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture
NIPS 2015
An Accelerated Proximal Coordinate Gradient Method
NIPS 2014
An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization
ICML 2014
Optimal Distributed Online Prediction Using Mini-Batches
JMLR 2012
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization
JMLR 2010
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization
NIPS 2009