Shuai Zhang
Orcid: 0000-0001-8280-6988Affiliations:
- New Jersey Institute of Technology, Newark, NJ, USA
- Rensselaer Polytechnic Institute, Department of Electrical, Computer, and Systems Engineering, Troy, NY, USA (former)
According to our database1,
Shuai Zhang authored at least 48 papers
between 2017 and 2026.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2026
Never Too Cocky to Cooperate: An FIM and RL-Based USV-AUV Collaborative System for Underwater Tasks in Extreme Sea Conditions.
IEEE Trans. Mob. Comput., July, 2026
ERFSL: An Efficient Reward Function Searcher via Language Models for Custom-Environment Multi-Objective Optimization (Student Abstract).
CoRR, May, 2026
CoRR, May, 2026
Efficient Training of Large-Scale AI Models Through Federated Mixture-of-Experts: A System-Level Approach.
IEEE Commun. Mag., April, 2026
Underwater Embodied Intelligence for Autonomous Robots: A Constraint-Coupled Perspective on Planning, Control, and Deployment.
CoRR, March, 2026
IEEE Trans. Mob. Comput., February, 2026
2025
CoRR, December, 2025
When Motion Learns to Listen: Diffusion-Prior Lyapunov Actor-Critic Framework with LLM Guidance for Stable and Robust AUV Control in Underwater Tasks.
CoRR, November, 2025
Towards Efficient Federated Learning of Networked Mixture-of-Experts for Mobile Edge Computing.
CoRR, November, 2025
Never Too Rigid to Reach: Adaptive Virtual Model Control with LLM- and Lyapunov-Based Reinforcement Learning.
CoRR, October, 2025
EasyUUV: An LLM-Enhanced Universal and Lightweight Sim-to-Real Reinforcement Learning Framework for UUV Attitude Control.
CoRR, October, 2025
Never too Cocky to Cooperate: An FIM and RL-based USV-AUV Collaborative System for Underwater Tasks in Extreme Sea Conditions.
CoRR, April, 2025
UPEGSim: An RL-Enabled Simulator for Unmanned Underwater Vehicles Dedicated in the Underwater Pursuit-Evasion Game.
IEEE Internet Things J., 2025
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025
Multi-Modal Gradual Domain Osmosis: Stepwise Dynamic Learning with Batch Matching for Gradual Domain Adaptation.
Proceedings of the 33rd ACM International Conference on Multimedia, 2025
Never too Prim to Swim: An LLM-Enhanced RL-based Adaptive S-Surface Controller for AUVs under Extreme Sea Conditions.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025
Make Your AUV Adaptive: An Environment-Aware Reinforcement Learning Framework For Underwater Tasks.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Mixture-of-Experts for Distributed Edge Computing with Channel-Aware Gating Function.
Proceedings of the IEEE International Conference on Communications, 2025
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025
UACOF: A USV-AUV Collaboration Framework for Underwater Tasks Under Extreme Sea Conditions (Student Abstract).
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
ERFSL: An Efficient Reward Function Searcher via Large Language Models for Custom-Environment Multi-Objective Reinforcement Learning (Student Abstract).
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
AoI-MDP: An AoI Optimized Markov Decision Process Dedicated in the Underwater Task (Student Abstract).
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025
2024
Large Language Models as Efficient Reward Function Searchers for Custom-Environment Multi-Objective Reinforcement Learning.
CoRR, 2024
Enhancing Information Freshness: An AoI Optimized Markov Decision Process Dedicated In the Underwater Task.
CoRR, 2024
How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance.
CoRR, 2024
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024
FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
CoRR, 2022
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data.
Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022
2021
Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case.
IEEE Trans. Neural Networks Learn. Syst., 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks.
CoRR, 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case.
Proceedings of the 37th International Conference on Machine Learning, 2020
Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent.
Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020
2019
IEEE Trans. Signal Process., 2019
2018
IEEE J. Sel. Top. Signal Process., 2018
Correction of Simultaneous Bad Measurements by Exploiting the Low-rank Hankel Structure.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018
2017
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017