← Authors

Tianyi Chen

65 papers · 2018–2026 · 16 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (16) 🌈 Renaissance Researcher (6) 🐝 Cross-Pollinator (7) πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (7) πŸŒ‰ Interdisciplinary Bridge πŸ”¬ Deep Specialist (19) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (245) ⚑ Prolific Year (7) πŸš€ Conference Pioneer πŸ’Ž Century Club (63) πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter ❓ The Questioner

Conferences

NIPS (13) AISTATS (10) ICML (10) AAAI (8) CVPR (7) ICLR (4) JMLR (3) IJCAI (2) ACL (1) ACML (1) ECCV (1) ICCV (1) INTERSPEECH (1) L4DC (1) MICCAI (1) MIDL (1)

Top co-authors

Quan Xiao (8) Lisha Chen (8) Han Shen (8) Si Wu (8) Tianyu Ding (7) Songtao Lu (6) Ilya Zharkov (6) Luming Liang (6) Wotao Yin (5) Yunfei Zhang (5)

Research topics

Applications (1)

Keywords

bilevel optimization (10) federated learning (6) semi-supervised learning (5) stochastic gradient descent (5) gradient descent (5) generative adversarial network (5) stochastic optimization (4) distributed learning (4) online learning (3) communication efficiency (3) image editing (2) few-shot learning (2) multi-agent reinforcement learning (2) image synthesis (2) model aggregation (2) neural network compression (2) ensemble learning (2) model compression (2) policy gradient (2) hyperparameter optimization (2)

Papers

Group-aware Multiscale Ensemble Learning for Test-Time Multimodal Sentiment Analysis AAAI 2026
ProCrop: Learning Aesthetic Image Cropping from Professional Compositions AAAI 2026
WinSpot: GUI Grounding Benchmark with Multimodal Large Language Models ACL 2025
Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance ICML 2025
AFL: A Single-Round Analytic Approach for Federated Learning with Pre-trained Models CVPR 2025
Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression CVPR 2025
SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection ICLR 2025
3DHumanEdit: Multi-modal Body Part-aware Conditioning Information Integration for 3D Human Manipulation AAAI 2025
Endo-CLIP: Progressive Self-Supervised Pre-training on Raw Colonoscopy Records MICCAI 2025
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF JMLR 2025
Efficient Online Reinforcement Learning for Diffusion Policy ICML 2025
Optimistic Safety for Online Convex Optimization with Unknown Linear Constraints AISTATS 2025
Primal-Dual Spectral Representation for Off-policy Evaluation AISTATS 2025
DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs ICML 2025
A First-order Generative Bilevel Optimization Framework for Diffusion Models ICML 2025
Unlocking Global Optimality in Bilevel Optimization: A Pilot Study ICLR 2025
SpotDiff: Spatial Gene Expression Imputation Diffusion with Single-Cell RNA Sequencing Data Integration AAAI 2025
RetouchFormer: Semi-supervised High-Quality Face Retouching Transformer with Prior-Based Selective Self-Attention AAAI 2024
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance JMLR 2024
AttriHuman-3D: Editable 3D Human Avatar Generation with Attribute Decomposition and Indexing CVPR 2024
DREAM: Diffusion Rectification and Estimation-Adaptive Models CVPR 2024
M2ASR: Multilingual Multi-task Automatic Speech Recognition via Multi-objective Optimization INTERSPEECH 2024
FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning NIPS 2024
Towards Exact Gradient-based Training on Analog In-memory Computing NIPS 2024
A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints NIPS 2024
CaesarNeRF: Calibrated Semantic Representation for Few-Shot Generalizable Neural Rendering ECCV 2024
The Language Model Can Have the Personality: Joint Learning for Personality Enhanced Language Model (Student Abstract) AAAI 2024
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning ICML 2024
Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF ICML 2024
DistiLLM: Towards Streamlined Distillation for Large Language Models ICML 2024
Enhancing In-context Learning via Linear Probe Calibration AISTATS 2024
An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition NIPS 2023
Enhancing Robot Program Synthesis Through Environmental Context NIPS 2023
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance NIPS 2023
Alternating Projected SGD for Equality-constrained Bilevel Optimization AISTATS 2023
Distributed Offline Policy Optimization Over Batch Data AISTATS 2023
Exploring Intra-Class Variation Factors With Learnable Cluster Prompts for Semi-Supervised Image Synthesis CVPR 2023
OTOv2: Automatic, Generic, User-Friendly ICLR 2023
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach ICLR 2023
On Penalty-based Bilevel Gradient Descent Method ICML 2023
LinSATNet: The Positive Linear Satisfiability Neural Networks ICML 2023
MAT: Mixed-Strategy Game of Adversarial Training in Fine-tuning IJCAI 2023
Federated Cross Learning for Medical Image Segmentation MIDL 2023
Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably? AISTATS 2022
Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning ICML 2022
Understanding Benign Overfitting in Gradient-Based Meta Learning NIPS 2022
A Single-timescale Analysis for Stochastic Approximation with Multiple Coupled Sequences NIPS 2022
SphericGAN: Semi-Supervised Hyper-Spherical Generative Adversarial Networks for Fine-Grained Image Synthesis CVPR 2022
Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees L4DC 2022
A Single-Timescale Method for Stochastic Bilevel Optimization AISTATS 2022
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems NIPS 2021
Only Train Once: A One-Shot Neural Network Training And Pruning Framework NIPS 2021
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning AAAI 2021
CADA: Communication-Adaptive Distributed Adam AISTATS 2021
Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning IJCAI 2021
CAFE: Catastrophic Data Leakage in Vertical Federated Learning NIPS 2021
Mask-Embedded Discriminator With Region-Based Semantic Regularization for Semi-Supervised Class-Conditional Image Synthesis CVPR 2021
Hybrid Estimation for Open-Ended Questions with Early-Age Students’ Block-Based Programming Answers ACML 2021
Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation ICCV 2021
Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics JMLR 2019
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets AAAI 2019
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients NIPS 2019
Bandit Online Learning with Unknown Delays AISTATS 2019
Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments AISTATS 2018
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning NIPS 2018