Yuhao Ding - RankMe

56 papers A* 9A 5C 4Misc 2Journal 29Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Real-time cooperative scheduling for CAVs at signal-free intersections via dynamic graph analysis and tree search. Robotics Auton. Syst. Xiaojun Tan, Yuhao Ding, Shuai Wang
2025	J	`jnl`	Beyond Exact Gradients: Convergence of Stochastic Soft-Max Policy Gradient Methods With Entropy Regularization. IEEE Trans. Autom. Control. Yuhao Ding, Junzi Zhang, Hyunin Lee, Javad Lavaei
2025	J	`jnl`	Policy-based Primal-Dual Methods for Concave CMDP with Variance Reduction. J. Artif. Intell. Res. Donghao Ying, Mengzi Amy Guo, Hyunin Lee, Yuhao Ding, Javad Lavaei, Zuo-Jun Max Shen
2025	J	`jnl`	Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning. IEEE Trans. Pattern Anal. Mach. Intell. Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Alois Knoll, Ming Jin
2025	J	`jnl`	Solving the Vehicle Cooperation Problem at Signal-Free Intersection via an Asynchronous Deep Reinforcement Learning Approach. IEEE Internet Things J. Shuai Wang, Yuhao Ding, Xiaoqi Ding, Xiaojun Tan
2024	J	`jnl`	A CMDP-within-online framework for Meta-Safe Reinforcement Learning. CoRR Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin
2024	A	`conf`	A Composable Dynamic Sparse Dataflow Architecture for Efficient Event-based Vision Processing on FPGA. FPGA Yizhao Gao, Baoheng Zhang, Yuhao Ding, Hayden Kwok-Hay So
2024	J	`jnl`	A Composable Dynamic Sparse Dataflow Architecture for Efficient Event-based Vision Processing on FPGA. CoRR Yizhao Gao, Baoheng Zhang, Yuhao Ding, Hayden Kwok-Hay So
2024	A*	`conf`	Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation. AAAI Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Ming Jin, Alois Knoll
2024	J	`jnl`	Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation. CoRR Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Ming Jin, Alois Knoll
2024	J	`jnl`	DyBit: Dynamic Bit-Precision Numbers for Efficient Quantized Neural Network Inference. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Jiajun Zhou, Jiajun Wu, Yizhao Gao, Yuhao Ding, Chaofan Tao, Boyu Li, Fengbin Tu, Kwang-Ting Cheng, Hayden Kwok-Hay So, Ngai Wong
2024	A*	`conf`	Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. NeurIPS Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas J. Spanos, Adam Wierman, Ming Jin
2024	J	`jnl`	Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. CoRR Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas J. Spanos, Adam Wierman, Ming Jin
2024	C	`conf`	Multi-Modal Flexible Headband for Sleep Monitoring. BSN Zaihao Wang, Yuhao Ding, Hongyu Chen, Zihao Wang, Chen Chen, Wei Chen
2024	J	`jnl`	Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning. CoRR Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Alois Knoll, Ming Jin
2024	J	`jnl`	The Landscape of Deterministic and Stochastic Optimal Control Problems: One-Shot Optimization Versus Dynamic Programming. IEEE Trans. Autom. Control. Jihun Kim, Yuhao Ding, Yingjie Bi, Javad Lavaei
2023	A*	`conf`	A CMDP-within-online framework for Meta-Safe Reinforcement Learning. ICLR Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin
2023	J	`jnl`	DyBit: Dynamic Bit-Precision Numbers for Efficient Quantized Neural Network Inference. CoRR Jiajun Zhou, Jiajun Wu, Yizhao Gao, Yuhao Ding, Chaofan Tao, Boyu Li, Fengbin Tu, Kwang-Ting Cheng, Hayden Kwok-Hay So, Ngai Wong
2023	—	`conf`	Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold. L4DC Bilgehan Sel, Ahmad Al-Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin
2023	—	`conf`	Local Analysis of Entropy-Regularized Stochastic Soft-Max Policy Gradient Methods. ECC Yuhao Ding, Junzi Zhang, Javad Lavaei
2023	Misc	`conf`	MSD: Mixing Signed Digit Representations for Hardware-efficient DNN Acceleration on FPGA with Heterogeneous Resources. FCCM Jiajun Wu, Jiajun Zhou, Yizhao Gao, Yuhao Ding, Ngai Wong, Hayden Kwok-Hay So
2023	Misc	`conf`	Model-Platform Optimized Deep Neural Network Accelerator Generation through Mixed-Integer Geometric Programming. FCCM Yuhao Ding, Jiajun Wu, Yizhao Gao, Maolin Wang, Hayden Kwok-Hay So
2023	A*	`conf`	Non-stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design. AAAI Yuhao Ding, Ming Jin, Javad Lavaei
2023	J	`jnl`	On the Absence of Spurious Local Trajectories in Time-Varying Nonconvex Optimization. IEEE Trans. Autom. Control. Salar Fattahi, Cédric Josz, Yuhao Ding, Reza Mohammadi-Ghazi, Javad Lavaei, Somayeh Sojoudi
2023	A*	`conf`	Policy-Based Primal-Dual Methods for Convex Constrained Markov Decision Processes. AAAI Donghao Ying, Mengzi Amy Guo, Yuhao Ding, Javad Lavaei, Zuo-Jun Max Shen
2023	A*	`conf`	Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints. AAAI Yuhao Ding, Javad Lavaei
2023	C	`conf`	Scalable Multi-Agent Reinforcement Learning with General Utilities. ACC Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	J	`jnl`	Scalable Multi-Agent Reinforcement Learning with General Utilities. CoRR Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	A*	`conf`	Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. NeurIPS Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	J	`jnl`	Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. CoRR Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
2023	J	`jnl`	Spatial Distributions of Cloud Occurrences in Terms of Volume Fraction as Inferred from CloudSat and CALIPSO. Remote. Sens. Yuhao Ding, Qi Liu, Ping Lao, Meng Li, Yuan Li, Qun Zheng, Yanghui Peng
2023	—	`conf`	SqueezeBlock: A Transparent Weight Compression Scheme for Deep Neural Networks. ICFPT Mo Song, Jiajun Wu, Yuhao Ding, Hayden Kwok-Hay So
2023	A*	`conf`	Tempo Adaptation in Non-stationary Reinforcement Learning. NeurIPS Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
2023	J	`jnl`	Tempo Adaption in Non-stationary Reinforcement Learning. CoRR Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
2023	J	`jnl`	Time-Variation in Online Nonconvex Optimization Enables Escaping From Spurious Local Minima. IEEE Trans. Autom. Control. Yuhao Ding, Javad Lavaei, Murat Arcak
2022	A	`conf`	A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization. AISTATS Donghao Ying, Yuhao Ding, Javad Lavaei
2022	J	`jnl`	Non-stationary Risk-sensitive Reinforcement Learning: Near-optimal Dynamic Regret, Adaptive Detection, and Separation Design. CoRR Yuhao Ding, Ming Jin, Javad Lavaei
2022	A	`conf`	On the Global Optimum Convergence of Momentum-based Policy Gradient. AISTATS Yuhao Ding, Junzi Zhang, Javad Lavaei
2022	J	`jnl`	Policy-based Primal-Dual Methods for Convex Constrained Markov Decision Processes. CoRR Donghao Ying, Mengzi Guo, Yuhao Ding, Javad Lavaei, Zuo-Jun Shen
2022	J	`jnl`	Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints. CoRR Yuhao Ding, Javad Lavaei
2021	J	`jnl`	A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization. CoRR Donghao Ying, Yuhao Ding, Javad Lavaei
2021	C	`conf`	Analysis of Spurious Local Solutions of Optimal Control Problems: One-Shot Optimization Versus Dynamic Programming. ACC Yuhao Ding, Yingjie Bi, Javad Lavaei
2021	J	`jnl`	Beyond Exact Gradients: Convergence of Stochastic Soft-Max Policy Gradient Methods with Entropy Regularization. CoRR Yuhao Ding, Junzi Zhang, Javad Lavaei
2021	C	`conf`	Escaping Spurious Local Minimum Trajectories in Online Time-varying Nonconvex Optimization. ACC Yuhao Ding, Javad Lavaei, Murat Arcak
2021	J	`jnl`	On the Global Convergence of Momentum-based Policy Gradient. CoRR Yuhao Ding, Junzi Zhang, Javad Lavaei
2021	J	`jnl`	Ontology-Enhanced Slot Filling. CoRR Yuhao Ding, Yik-Cheung Tam
2021	J	`jnl`	Rainrate Estimation from FY-4A Cloud Top Temperature for Mesoscale Convective Systems by Using Machine Learning Algorithm. Remote. Sens. Ping Lao, Qi Liu, Yuhao Ding, Yu Wang, Yuan Li, Meng Li
2021	—	`conf`	Structured Projection-free Online Convex Optimization with Multi-point Bandit Feedback. CDC Yuhao Ding, Javad Lavaei
2020	J	`jnl`	CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks. CoRR Runbin Shi, Peiyan Dong, Tong Geng, Yuhao Ding, Xiaolong Ma, Hayden Kwok-Hay So, Martin C. Herbordt, Ang Li, Yanzhi Wang
2020	A	`conf`	CSB-RNN: a faster-than-realtime RNN acceleration framework with compressed structured blocks. ICS Runbin Shi, Peiyan Dong, Tong Geng, Yuhao Ding, Xiaolong Ma, Hayden Kwok-Hay So, Martin C. Herbordt, Ang Li, Yanzhi Wang
2020	A*	`conf`	FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. DAC Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
2020	A	`conf`	FTDL: An FPGA-tailored Architecture for Deep Learning Systems. FPGA Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
2019	J	`jnl`	Escaping spurious local minimum trajectories in online time-varying nonconvex optimization. CoRR Yuhao Ding, Javad Lavaei, Murat Arcak
2018	—	`conf`	Analysis of cars' commuting behavior under license plate restriction policy: a case study in Hangzhou, China. ITSC Wenbin Yao, Yuhao Ding, Fangming Xu, Sheng Jin
2018	—	`conf`	Input Design for Nonlinear Model Discrimination via Affine Abstraction. ADHS Kanishka Raj Singh, Yuhao Ding, Necmiye Ozay, Sze Zheng Yong
2018	—	`conf`	Optimal input design for affine model discrimination with applications in intention-aware vehicles. ICCPS Yuhao Ding, Farshad Harirchi, Sze Zheng Yong, Emil Jacobsen, Necmiye Ozay