Yuhao Ding

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 41

Top Topics

Markov Decision Process

Policy Gradient

Reinforcement Learning

Convex Optimization

Top Venues

Publications

Yizhao Gao, Baoheng Zhang, Yuhao Ding, Hayden Kwok-Hay So
A Composable Dynamic Sparse Dataflow Architecture for Efficient Event-based Vision Processing on FPGA. CoRR (2024)
Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Multi-Agent Reinforcement Learning with General Utilities. CoRR (2023)
Yuhao Ding, Junzi Zhang, Javad Lavaei
Local Analysis of Entropy-Regularized Stochastic Soft-Max Policy Gradient Methods. ECC (2023)
Jiajun Zhou, Jiajun Wu, Yizhao Gao, Yuhao Ding, Chaofan Tao, Boyu Li, Fengbin Tu, Kwang-Ting Cheng, Hayden Kwok-Hay So, Ngai Wong
DyBit: Dynamic Bit-Precision Numbers for Efficient Quantized Neural Network Inference. CoRR (2023)
Jiajun Wu, Jiajun Zhou, Yizhao Gao, Yuhao Ding, Ngai Wong, Hayden Kwok-Hay So
MSD: Mixing Signed Digit Representations for Hardware-efficient DNN Acceleration on FPGA with Heterogeneous Resources. FCCM (2023)
Salar Fattahi, Cédric Josz, Yuhao Ding, Reza Mohammadi-Ghazi, Javad Lavaei, Somayeh Sojoudi
On the Absence of Spurious Local Trajectories in Time-Varying Nonconvex Optimization. IEEE Trans. Autom. Control. 68 (1) (2023)
Bilgehan Sel, Ahmad Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin
Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold. L4DC (2023)
Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin
A CMDP-within-online framework for Meta-Safe Reinforcement Learning. ICLR (2023)
Mo Song, Jiajun Wu, Yuhao Ding, Hayden Kwok-Hay So
SqueezeBlock: A Transparent Weight Compression Scheme for Deep Neural Networks. ICFPT (2023)
Yuhao Ding, Javad Lavaei
Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints. AAAI (2023)
Yuhao Ding, Qi Liu, Ping Lao, Meng Li, Yuan Li, Qun Zheng, Yanghui Peng
Spatial Distributions of Cloud Occurrences in Terms of Volume Fraction as Inferred from CloudSat and CALIPSO. Remote. Sens. 15 (16) (2023)
Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
Tempo Adaption in Non-stationary Reinforcement Learning. CoRR (2023)
Donghao Ying, Mengzi Amy Guo, Yuhao Ding, Javad Lavaei, Zuo-Jun Max Shen
Policy-Based Primal-Dual Methods for Convex Constrained Markov Decision Processes. AAAI (2023)
Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
Tempo Adaptation in Non-stationary Reinforcement Learning. NeurIPS (2023)
Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. NeurIPS (2023)
Yuhao Ding, Javad Lavaei, Murat Arcak
Time-Variation in Online Nonconvex Optimization Enables Escaping From Spurious Local Minima. IEEE Trans. Autom. Control. 68 (1) (2023)
Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Multi-Agent Reinforcement Learning with General Utilities. ACC (2023)
Yuhao Ding, Ming Jin, Javad Lavaei
Non-stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design. AAAI (2023)
Yuhao Ding, Jiajun Wu, Yizhao Gao, Maolin Wang, Hayden Kwok-Hay So
Model-Platform Optimized Deep Neural Network Accelerator Generation through Mixed-Integer Geometric Programming. FCCM (2023)
Donghao Ying, Yunkai Zhang, Yuhao Ding, Alec Koppel, Javad Lavaei
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities. CoRR (2023)
Donghao Ying, Mengzi Guo, Yuhao Ding, Javad Lavaei, Zuo-Jun Shen
Policy-based Primal-Dual Methods for Convex Constrained Markov Decision Processes. CoRR (2022)
Donghao Ying, Yuhao Ding, Javad Lavaei
A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization. AISTATS (2022)
Yuhao Ding, Ming Jin, Javad Lavaei
Non-stationary Risk-sensitive Reinforcement Learning: Near-optimal Dynamic Regret, Adaptive Detection, and Separation Design. CoRR (2022)
Yuhao Ding, Junzi Zhang, Javad Lavaei
On the Global Optimum Convergence of Momentum-based Policy Gradient. AISTATS (2022)
Yuhao Ding, Javad Lavaei
Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints. CoRR (2022)
Yuhao Ding, Junzi Zhang, Javad Lavaei
Beyond Exact Gradients: Convergence of Stochastic Soft-Max Policy Gradient Methods with Entropy Regularization. CoRR (2021)
Yuhao Ding, Yik-Cheung Tam
Ontology-Enhanced Slot Filling. CoRR (2021)
Yuhao Ding, Javad Lavaei
Structured Projection-free Online Convex Optimization with Multi-point Bandit Feedback. CDC (2021)
Yuhao Ding, Junzi Zhang, Javad Lavaei
On the Global Convergence of Momentum-based Policy Gradient. CoRR (2021)
Ping Lao, Qi Liu, Yuhao Ding, Yu Wang, Yuan Li, Meng Li
Rainrate Estimation from FY-4A Cloud Top Temperature for Mesoscale Convective Systems by Using Machine Learning Algorithm. Remote. Sens. 13 (16) (2021)
Yuhao Ding, Javad Lavaei, Murat Arcak
Escaping Spurious Local Minimum Trajectories in Online Time-varying Nonconvex Optimization. ACC (2021)
Yuhao Ding, Yingjie Bi, Javad Lavaei
Analysis of Spurious Local Solutions of Optimal Control Problems: One-Shot Optimization Versus Dynamic Programming. ACC (2021)
Donghao Ying, Yuhao Ding, Javad Lavaei
A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization. CoRR (2021)
Runbin Shi, Peiyan Dong, Tong Geng, Yuhao Ding, Xiaolong Ma, Hayden Kwok-Hay So, Martin C. Herbordt, Ang Li, Yanzhi Wang
CSB-RNN: A Faster-than-Realtime RNN Acceleration Framework with Compressed Structured Blocks. CoRR (2020)
Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. DAC (2020)
Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding
FTDL: An FPGA-tailored Architecture for Deep Learning Systems. FPGA (2020)
Runbin Shi, Peiyan Dong, Tong Geng, Yuhao Ding, Xiaolong Ma, Hayden Kwok-Hay So, Martin C. Herbordt, Ang Li, Yanzhi Wang
CSB-RNN: a faster-than-realtime RNN acceleration framework with compressed structured blocks. ICS (2020)
Yuhao Ding, Javad Lavaei, Murat Arcak
Escaping spurious local minimum trajectories in online time-varying nonconvex optimization. CoRR (2019)
Yuhao Ding, Farshad Harirchi, Sze Zheng Yong, Emil Jacobsen, Necmiye Ozay
Optimal input design for affine model discrimination with applications in intention-aware vehicles. ICCPS (2018)
Kanishka Raj Singh, Yuhao Ding, Necmiye Ozay, Sze Zheng Yong
Input Design for Nonlinear Model Discrimination via Affine Abstraction. ADHS (2018)
Wenbin Yao, Yuhao Ding, Fangming Xu, Sheng Jin
Analysis of cars' commuting behavior under license plate restriction policy: a case study in Hangzhou, China. ITSC (2018)