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2020 – today
- 2024
[j6]Jihun Kim
, Yuhao Ding, Yingjie Bi, Javad Lavaei:
The Landscape of Deterministic and Stochastic Optimal Control Problems: One-Shot Optimization Versus Dynamic Programming. IEEE Trans. Autom. Control. 69(12): 8587-8602 (2024)- [j5]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. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(5): 1613-1617 (2024) - [c25]Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Ming Jin, Alois Knoll:
Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation. AAAI 2024: 21099-21106 - [c24]Yizhao Gao, Baoheng Zhang, Yuhao Ding, Hayden Kwok-Hay So:
A Composable Dynamic Sparse Dataflow Architecture for Efficient Event-based Vision Processing on FPGA. FPGA 2024: 246-257 - [i18]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 abs/2401.05626 (2024) - [i17]Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Ming Jin, Alois Knoll:
Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation. CoRR abs/2405.01677 (2024) - [i16]Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, Qingwei Lin, Alois Knoll, Ming Jin:
Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning. CoRR abs/2405.16390 (2024) - [i15]Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin:
A CMDP-within-online framework for Meta-Safe Reinforcement Learning. CoRR abs/2405.16601 (2024) - [i14]Shangding Gu, Laixi Shi, Yuhao Ding, Alois Knoll, Costas J. Spanos, Adam Wierman, Ming Jin:
Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation. CoRR abs/2405.20860 (2024) - 2023
- [j4]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): 3978 (2023) - [j3]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): 80-95 (2023) - [j2]Yuhao Ding, Javad Lavaei, Murat Arcak:
Time-Variation in Online Nonconvex Optimization Enables Escaping From Spurious Local Minima. IEEE Trans. Autom. Control. 68(1): 156-171 (2023) - [c23]Yuhao Ding, Javad Lavaei:
Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints. AAAI 2023: 7396-7404 - [c22]Yuhao Ding, Ming Jin, Javad Lavaei:
Non-stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design. AAAI 2023: 7405-7413 - [c21]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: 10963-10971 - [c20]Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei:
Scalable Multi-Agent Reinforcement Learning with General Utilities. ACC 2023: 3977-3982 - [c19]Yuhao Ding, Junzi Zhang, Javad Lavaei:
Local Analysis of Entropy-Regularized Stochastic Soft-Max Policy Gradient Methods. ECC 2023: 1-8 - [c18]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: 83-93 - [c17]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: 94-104 - [c16]Mo Song, Jiajun Wu, Yuhao Ding, Hayden Kwok-Hay So:
SqueezeBlock: A Transparent Weight Compression Scheme for Deep Neural Networks. ICFPT 2023: 238-243 - [c15]Vanshaj Khattar, Yuhao Ding, Bilgehan Sel, Javad Lavaei, Ming Jin:
A CMDP-within-online framework for Meta-Safe Reinforcement Learning. ICLR 2023 - [c14]Bilgehan Sel, Ahmad Al-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: 38-50 - [c13]Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi:
Tempo Adaptation in Non-stationary Reinforcement Learning. NeurIPS 2023 - [c12]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 - [i13]Donghao Ying, Yuhao Ding, Alec Koppel, Javad Lavaei:
Scalable Multi-Agent Reinforcement Learning with General Utilities. CoRR abs/2302.07938 (2023) - [i12]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 abs/2302.12510 (2023) - [i11]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 abs/2305.17568 (2023) - [i10]Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi:
Tempo Adaption in Non-stationary Reinforcement Learning. CoRR abs/2309.14989 (2023) - 2022
- [c11]Donghao Ying, Yuhao Ding, Javad Lavaei:
A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization. AISTATS 2022: 1887-1909 - [c10]Yuhao Ding, Junzi Zhang, Javad Lavaei:
On the Global Optimum Convergence of Momentum-based Policy Gradient. AISTATS 2022: 1910-1934 - [i9]Yuhao Ding, Javad Lavaei:
Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints. CoRR abs/2201.11965 (2022) - [i8]Donghao Ying, Mengzi Guo, Yuhao Ding, Javad Lavaei, Zuo-Jun Shen:
Policy-based Primal-Dual Methods for Convex Constrained Markov Decision Processes. CoRR abs/2205.10715 (2022) - [i7]Yuhao Ding, Ming Jin, Javad Lavaei:
Non-stationary Risk-sensitive Reinforcement Learning: Near-optimal Dynamic Regret, Adaptive Detection, and Separation Design. CoRR abs/2211.10815 (2022) - 2021
- [j1]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): 3273 (2021) - [c9]Yuhao Ding, Javad Lavaei, Murat Arcak:
Escaping Spurious Local Minimum Trajectories in Online Time-varying Nonconvex Optimization. ACC 2021: 454-461 - [c8]Yuhao Ding, Yingjie Bi, Javad Lavaei:
Analysis of Spurious Local Solutions of Optimal Control Problems: One-Shot Optimization Versus Dynamic Programming. ACC 2021: 3836-3843 - [c7]Yuhao Ding, Javad Lavaei:
Structured Projection-free Online Convex Optimization with Multi-point Bandit Feedback. CDC 2021: 954-961 - [i6]Yuhao Ding, Yik-Cheung Tam:
Ontology-Enhanced Slot Filling. CoRR abs/2108.11275 (2021) - [i5]Donghao Ying, Yuhao Ding, Javad Lavaei:
A Dual Approach to Constrained Markov Decision Processes with Entropy Regularization. CoRR abs/2110.08923 (2021) - [i4]Yuhao Ding, Junzi Zhang, Javad Lavaei:
On the Global Convergence of Momentum-based Policy Gradient. CoRR abs/2110.10116 (2021) - [i3]Yuhao Ding, Junzi Zhang, Javad Lavaei:
Beyond Exact Gradients: Convergence of Stochastic Soft-Max Policy Gradient Methods with Entropy Regularization. CoRR abs/2110.10117 (2021) - 2020
- [c6]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: 1-6 - [c5]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: 320 - [c4]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: 24:1-24:12 - [i2]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 abs/2005.05758 (2020)
2010 – 2019
- 2019
- [i1]Yuhao Ding, Javad Lavaei, Murat Arcak:
Escaping spurious local minimum trajectories in online time-varying nonconvex optimization. CoRR abs/1912.00561 (2019) - 2018
- [c3]Kanishka Raj Singh, Yuhao Ding, Necmiye Ozay, Sze Zheng Yong:
Input Design for Nonlinear Model Discrimination via Affine Abstraction. ADHS 2018: 175-180 - [c2]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: 297-307 - [c1]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: 236-241
Coauthor Index
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last updated on 2024-12-23 20:33 CET by the dblp team
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