An Information-Theoretic Approach to Transferability in Task Transfer Learning. - Yajie Bao; Yang Li 104; Shao-Lun Huang; Lin Zhang 001; Lizhong Zheng; Amir Zamir; Leonidas J. Guibas (ICIP, 2019)

One-Round Communication Efficient Distributed M-Estimation. - Yajie Bao; Weijia Xiong (AISTATS, 2021)

Model-free Control Design Using Policy Gradient Reinforcement Learning in LPV Framework. - Yajie Bao; Javad Mohammadpour Velni (ECC, 2021)

Data-Driven Linear Parameter-Varying Model Identification Using Transfer Learning. - Yajie Bao; Javad Mohammadpour Velni (IEEE Control. Syst. Lett., 2021)

Epistemic Uncertainty Quantification in State-Space LPV Model Identification Using Bayesian Neural Networks. - Yajie Bao; Javad Mohammadpour Velni; Mahdi Shahbakhti (IEEE Control. Syst. Lett., 2021)

Learning-based Adaptive-Scenario-Tree Model Predictive Control with Probabilistic Safety Guarantees Using Bayesian Neural Networks. - Yajie Bao; Kimberly J. Chan; Ali Mesbah 002; Javad Mohammadpour Velni (ACC, 2022)

Physics-guided and Energy-based Learning of Interconnected Systems: from Lagrangian to Port-Hamiltonian Systems. - Yajie Bao; Vaishnavi Thesma; Atul Kelkar; Javad Mohammadpour Velni (CDC, 2022)

Optimal Lighting Control in Greenhouses Using Bayesian Neural Networks for Sunlight Prediction. - Shirin Afzali; Yajie Bao; Marc W. van Iersel; Javad Mohammadpour Velni (ECC, 2022)

A Deep Reinforcement Learning-based Sliding Mode Control Design for Partially-known Nonlinear Systems. - Sahand Mosharafian; Shirin Afzali; Yajie Bao; Javad Mohammadpour Velni (ECC, 2022)

Fast Composite Optimization and Statistical Recovery in Federated Learning. - Yajie Bao; Michael Crawshaw; Shan Luo 005; Mingrui Liu (ICML, 2022)

Byzantine-tolerant distributed multiclass sparse linear discriminant analysis. - Yajie Bao; Weidong Liu 005; Xiaojun Mao; Weijia Xiong (UAI, 2022)

Varying Coefficient Linear Discriminant Analysis for Dynamic Data. - Yajie Bao; Yuyang Liu (CoRR, 2022)

Scenario-Based Hybrid Model Predictive Design for Cooperative Adaptive Cruise Control in Mixed-Autonomy Environments. - Sahand Mosharafian; Yajie Bao; Javad Mohammadpour Velni (CDC, 2023)

EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data. - Michael Crawshaw; Yajie Bao; Mingrui Liu (ICLR, 2023)

Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization. - Yajie Bao; Amarda Shehu; Mingrui Liu (NeurIPS, 2023)

Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds. - Michael Crawshaw; Yajie Bao; Mingrui Liu (NeurIPS, 2023)

Resilient Range-Only Cooperative Positioning of Multiple Smart Unmanned Aerial Systems. - Yajie Bao; Dan Shen; Genshe Chen; Khanh Pham 001; Erik Blasch (SmartSP, 2023)

A Hybrid Neural Network Approach for Adaptive Scenario-Based Model Predictive Control in the LPV Framework. - Yajie Bao; Javad Mohammadpour Velni (IEEE Control. Syst. Lett., 2023)

Safe control of nonlinear systems in LPV framework using model-based reinforcement learning. - Yajie Bao; Javad Mohammadpour Velni (Int. J. Control, 2023)

Semi-profiled distributed estimation for high-dimensional partially linear model. - Yajie Bao; Haojie Ren (Comput. Stat. Data Anal., 2023)

Adaptive Multi-stage Sensor Fusion Under Neuro-Symbolic Framework for The Multi-modal Ranging System in Adverse Weather Conditions. - Yajie Bao; Peng Cheng; Ping Zhuang; Yunqi Zhang; Zhengyang Fan; Genshe Chen; Erik Blasch; Khanh D. Pham (DDDAS/Infosymbiotics, 2024)

RNN-UKF: Enhancing Hyperparameter Auto-Tuning in Unscented Kalman Filters through Recurrent Neural Networks. - Zhengyang Fan; Dan Shen; Yajie Bao; Khanh Pham 001; Erik Blasch; Genshe Chen (FUSION, 2024)

Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective. - Yajie Bao; Michael Crawshaw; Mingrui Liu (ICML, 2024)

CAP: A General Algorithm for Online Selective Conformal Prediction with FCR Control. - Yajie Bao; Yuyang Huo; Haojie Ren; Changliang Zou (CoRR, 2024)

A Lightweight Transformer for Remote Sensing Image Change Captioning. - Dongwei Sun; Yajie Bao; Xiangyong Cao (CoRR, 2024)

Adaptive Uncertainty Quantification for Scenario-based Control Using Meta-learning of Bayesian Neural Networks. - Yajie Bao; Javad Mohammadpour Velni (CoRR, 2024)

A learning- and scenario-based MPC design for nonlinear systems in LPV framework with safety and stability guarantees. - Yajie Bao; Hossam S. Abbas; Javad Mohammadpour Velni (Int. J. Control, 2024)

A Lightweight Sparse Focus Transformer for Remote Sensing Image Change Captioning. - Dongwei Sun; Yajie Bao; Junmin Liu; Xiangyong Cao (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

Confidence-based interactable neural-symbolic visual question answering. - Yajie Bao; Tianwei Xing; Xun Chen (Neurocomputing, 2024)

Error-quantified Conformal Inference for Time Series. - Junxi Wu; Dongjian Hu; Yajie Bao; Shu-Tao Xia; Changliang Zou (ICLR, 2025)

Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach. - Qian Peng; Yajie Bao; Haojie Ren; Zhaojun Wang; Changliang Zou (CoRR, 2025)

Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention. - Shuang Wu; Youtian Lin; Feihu Zhang; Yifei Zeng; Yikang Yang; Yajie Bao; Jiachen Qian; Siyu Zhu 001; Xun Cao; Philip Torr 001; Yao Yao 008 (CoRR, 2025)

Optimal Model Selection for Conformalized Robust Optimization. - Yajie Bao; Yang Hu; Haojie Ren; Peng Zhao; Changliang Zou (CoRR, 2025)