← Authors

Kaiyi Ji

30 papers · 2018–2025 · 8 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (7) 🐝 Cross-Pollinator (8) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (41) 🌍 Conference Polyglot (8) 🀝 Dynamic Duo (15) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (22) πŸ† Keyword Champion (13) πŸ—ƒοΈ Keyword Collector (103) ⚑ Prolific Year (8) πŸ”₯ Unstoppable (8) πŸ’Ž Century Club (30)

Conferences

NIPS (12) ICML (7) ICLR (3) JMLR (3) AAAI (2) ICCV (1) IJCAI (1) UAI (1)

Top co-authors

Yingbin Liang (15) Peiyao Xiao (6) Yi Zhou (5) Yifan Yang (5) Zhe Wang (4) Hao Ban (4) Junjie Yang (3) Shiqian Ma (3) Minhui Huang (3) Vahid Tarokh (2)

Keywords

bilevel optimization (13) convergence rate (6) stochastic optimization (5) convergence analysis (5) nonconvex optimization (5) federated learning (4) hyperparameter optimization (3) variance reduction (3) sample complexity (3) gradient descent (3) multi-task learning (3) stochastic gradient descent (2) online learning (2) client sampling (2) model-agnostic meta-learning (2) implicit differentiation (2) neural network optimization (2) few-shot learning (2) communication efficiency (2) momentum method (2)

Papers

Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis ICLR 2025
Efficiently Escaping Saddle Points in Bilevel Optimization JMLR 2025
First-Order Federated Bilevel Learning AAAI 2025
SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation ICCV 2025
MGDA Converges under Generalized Smoothness, Provably ICLR 2025
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning ICLR 2024
First-Order Minimax Bilevel Optimization NIPS 2024
Fair Resource Allocation in Multi-Task Learning ICML 2024
Understanding Forgetting in Continual Learning with Linear Regression ICML 2024
Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization NIPS 2023
Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm NIPS 2023
Achieving Linear Speedup in Non-IID Federated Bilevel Learning ICML 2023
Lower Bounds and Accelerated Algorithms for Bilevel Optimization JMLR 2023
Communication-Efficient Federated Hypergradient Computation via Aggregated Iterative Differentiation ICML 2023
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms NIPS 2023
Non-Convex Bilevel Optimization with Time-Varying Objective Functions NIPS 2023
SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning NIPS 2023
Data sampling affects the complexity of online SGD over dependent data UAI 2022
Will Bilevel Optimizers Benefit from Loops NIPS 2022
On the Convergence Theory for Hessian-Free Bilevel Algorithms NIPS 2022
Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning JMLR 2022
Provably Faster Algorithms for Bilevel Optimization NIPS 2021
Bilevel Optimization: Convergence Analysis and Enhanced Design ICML 2021
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms ICML 2020
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization IJCAI 2020
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack AAAI 2020
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters NIPS 2020
Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization ICML 2019
SpiderBoost and Momentum: Faster Variance Reduction Algorithms NIPS 2019
Minimax Estimation of Neural Net Distance NIPS 2018