Yajie Bao - RankMe

47 papers A* 7A 2B 1C 3Journal 27Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	CAP: A General Algorithm for Online Selective Conformal Prediction with FCR Control. J. Mach. Learn. Res. Yajie Bao, Yuyang Huo, Haojie Ren, Changliang Zou
2025	A*	`conf`	Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach. ICML Qian Peng, Yajie Bao, Haojie Ren, Zhaojun Wang, Changliang Zou
2025	J	`jnl`	Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach. CoRR Qian Peng, Yajie Bao, Haojie Ren, Zhaojun Wang, Changliang Zou
2025	J	`jnl`	Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention. CoRR Shuang Wu, Youtian Lin, Feihu Zhang, Yifei Zeng, Yikang Yang, Yajie Bao, Jiachen Qian, Siyu Zhu, Xun Cao, Philip Torr, Yao Yao
2025	A*	`conf`	Error-quantified Conformal Inference for Time Series. ICLR Junxi Wu, Dongjian Hu, Yajie Bao, Shu-Tao Xia, Changliang Zou
2025	J	`jnl`	Error-quantified Conformal Inference for Time Series. CoRR Junxi Wu, Dongjian Hu, Yajie Bao, Shu-Tao Xia, Changliang Zou
2025	J	`jnl`	Feedback for Improved Hierarchical Reinforcement Learning With Timed Subgoals. IEEE Control. Syst. Lett. Yajie Bao, Dan Shen, Genshe Chen, Hao Xu, Samson Badlia, Simon Khan, Erik Blasch, Khanh D. Pham
2025	J	`jnl`	Learning-Assisted Multi-IMU Proprioceptive State Estimation for Quadruped Robots. Inf. Xuanning Liu, Yajie Bao, Peng Cheng, Dan Shen, Zhengyang Fan, Hao Xu, Genshe Chen
2025	J	`jnl`	Optimal Model Selection for Conformalized Robust Optimization. CoRR Yajie Bao, Yang Hu, Haojie Ren, Peng Zhao, Changliang Zou
2025	J	`jnl`	SpatialVID: A Large-Scale Video Dataset with Spatial Annotations. CoRR Jiahao Wang, Yufeng Yuan, Rujie Zheng, Youtian Lin, Jian Gao, Lin-Zhuo Chen, Yajie Bao, Yi Zhang, Chang Zeng, Yanxi Zhou, Xiaoxiao Long, Hao Zhu, Zhaoxiang Zhang, Xun Cao, Yao Yao
2025	J	`jnl`	TEXTRIX: Latent Attribute Grid for Native Texture Generation and Beyond. CoRR Yifei Zeng, Yajie Bao, Jiachen Qian, Shuang Wu, Youtian Lin, Hao Zhu, Buyu Li, Feihu Zhang, Xun Cao, Yao Yao
2024	J	`jnl`	A Lightweight Sparse Focus Transformer for Remote Sensing Image Change Captioning. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Dongwei Sun, Yajie Bao, Junmin Liu, Xiangyong Cao
2024	J	`jnl`	A Lightweight Transformer for Remote Sensing Image Change Captioning. CoRR Dongwei Sun, Yajie Bao, Xiangyong Cao
2024	J	`jnl`	A learning- and scenario-based MPC design for nonlinear systems in LPV framework with safety and stability guarantees. Int. J. Control Yajie Bao, Hossam S. Abbas, Javad Mohammadpour Velni
2024	—	`conf`	Adaptive Multi-stage Sensor Fusion Under Neuro-Symbolic Framework for The Multi-modal Ranging System in Adverse Weather Conditions. DDDAS/Infosymbiotics Yajie Bao, Peng Cheng, Ping Zhuang, Yunqi Zhang, Zhengyang Fan, Genshe Chen, Erik Blasch, Khanh D. Pham
2024	J	`jnl`	Adaptive Uncertainty Quantification for Scenario-based Control Using Meta-learning of Bayesian Neural Networks. CoRR Yajie Bao, Javad Mohammadpour Velni
2024	J	`jnl`	CAP: A General Algorithm for Online Selective Conformal Prediction with FCR Control. CoRR Yajie Bao, Yuyang Huo, Haojie Ren, Changliang Zou
2024	J	`jnl`	Confidence-based interactable neural-symbolic visual question answering. Neurocomputing Yajie Bao, Tianwei Xing, Xun Chen
2024	A*	`conf`	Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective. ICML Yajie Bao, Michael Crawshaw, Mingrui Liu
2024	C	`conf`	RNN-UKF: Enhancing Hyperparameter Auto-Tuning in Unscented Kalman Filters through Recurrent Neural Networks. FUSION Zhengyang Fan, Dan Shen, Yajie Bao, Khanh Pham, Erik Blasch, Genshe Chen
2023	J	`jnl`	A Hybrid Neural Network Approach for Adaptive Scenario-Based Model Predictive Control in the LPV Framework. IEEE Control. Syst. Lett. Yajie Bao, Javad Mohammadpour Velni
2023	A*	`conf`	EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data. ICLR Michael Crawshaw, Yajie Bao, Mingrui Liu
2023	J	`jnl`	EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data. CoRR Michael Crawshaw, Yajie Bao, Mingrui Liu
2023	A*	`conf`	Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds. NeurIPS Michael Crawshaw, Yajie Bao, Mingrui Liu
2023	A*	`conf`	Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization. NeurIPS Yajie Bao, Amarda Shehu, Mingrui Liu
2023	—	`conf`	Resilient Range-Only Cooperative Positioning of Multiple Smart Unmanned Aerial Systems. SmartSP Yajie Bao, Dan Shen, Genshe Chen, Khanh Pham, Erik Blasch
2023	J	`jnl`	Safe control of nonlinear systems in LPV framework using model-based reinforcement learning. Int. J. Control Yajie Bao, Javad Mohammadpour Velni
2023	—	`conf`	Scenario-Based Hybrid Model Predictive Design for Cooperative Adaptive Cruise Control in Mixed-Autonomy Environments. CDC Sahand Mosharafian, Yajie Bao, Javad Mohammadpour Velni
2023	J	`jnl`	Semi-profiled distributed estimation for high-dimensional partially linear model. Comput. Stat. Data Anal. Yajie Bao, Haojie Ren
2022	—	`conf`	A Deep Reinforcement Learning-based Sliding Mode Control Design for Partially-known Nonlinear Systems. ECC Sahand Mosharafian, Shirin Afzali, Yajie Bao, Javad Mohammadpour Velni
2022	J	`jnl`	A Deep Reinforcement Learning-based Sliding Mode Control Design for Partially-known Nonlinear Systems. CoRR Sahand Mosharafian, Shirin Afzali, Yajie Bao, Javad Mohammadpour Velni
2022	J	`jnl`	A Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees. CoRR Yajie Bao, Hossam S. Abbas, Javad Mohammadpour Velni
2022	J	`jnl`	An Information-Theoretic Approach to Transferability in Task Transfer Learning. CoRR Yajie Bao, Yang Li, Shao-Lun Huang, Lin Zhang, Lizhong Zheng, Amir Zamir, Leonidas J. Guibas
2022	A	`conf`	Byzantine-tolerant distributed multiclass sparse linear discriminant analysis. UAI Yajie Bao, Weidong Liu, Xiaojun Mao, Weijia Xiong
2022	A*	`conf`	Fast Composite Optimization and Statistical Recovery in Federated Learning. ICML Yajie Bao, Michael Crawshaw, Shan Luo, Mingrui Liu
2022	J	`jnl`	Fast Composite Optimization and Statistical Recovery in Federated Learning. CoRR Yajie Bao, Michael Crawshaw, Shan Luo, Mingrui Liu
2022	C	`conf`	Learning-based Adaptive-Scenario-Tree Model Predictive Control with Probabilistic Safety Guarantees Using Bayesian Neural Networks. ACC Yajie Bao, Kimberly J. Chan, Ali Mesbah, Javad Mohammadpour Velni
2022	—	`conf`	Optimal Lighting Control in Greenhouses Using Bayesian Neural Networks for Sunlight Prediction. ECC Shirin Afzali, Yajie Bao, Marc W. van Iersel, Javad Mohammadpour Velni
2022	J	`jnl`	Optimal Lighting Control in Greenhouses Using Bayesian Neural Networks for Sunlight Prediction. CoRR Shirin Afzali, Yajie Bao, Marc W. van Iersel, Javad Mohammadpour Velni
2022	—	`conf`	Physics-guided and Energy-based Learning of Interconnected Systems: from Lagrangian to Port-Hamiltonian Systems. CDC Yajie Bao, Vaishnavi Thesma, Atul Kelkar, Javad Mohammadpour Velni
2022	J	`jnl`	Varying Coefficient Linear Discriminant Analysis for Dynamic Data. CoRR Yajie Bao, Yuyang Liu
2021	J	`jnl`	Data-Driven Linear Parameter-Varying Model Identification Using Transfer Learning. IEEE Control. Syst. Lett. Yajie Bao, Javad Mohammadpour Velni
2021	C	`conf`	Data-driven Linear Parameter-varying Model Identification Using Transfer Learning. ACC Yajie Bao, Javad Mohammadpour Velni
2021	J	`jnl`	Epistemic Uncertainty Quantification in State-Space LPV Model Identification Using Bayesian Neural Networks. IEEE Control. Syst. Lett. Yajie Bao, Javad Mohammadpour Velni, Mahdi Shahbakhti
2021	—	`conf`	Model-free Control Design Using Policy Gradient Reinforcement Learning in LPV Framework. ECC Yajie Bao, Javad Mohammadpour Velni
2021	A	`conf`	One-Round Communication Efficient Distributed M-Estimation. AISTATS Yajie Bao, Weijia Xiong
2019	B	`conf`	An Information-Theoretic Approach to Transferability in Task Transfer Learning. ICIP Yajie Bao, Yang Li, Shao-Lun Huang, Lin Zhang, Lizhong Zheng, Amir Zamir, Leonidas J. Guibas

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.