no code implementations • 15 Mar 2024 • Swetha Ganesh, Jiayu Chen, Gugan Thoppe, Vaneet Aggarwal
Federated Reinforcement Learning (FRL) allows multiple agents to collaboratively build a decision making policy without sharing raw trajectories.
1 code implementation • 12 Mar 2024 • Dipesh Tamboli, Jiayu Chen, Kiran Pranesh Jotheeswaran, Denny Yu, Vaneet Aggarwal
Sepsis, a life-threatening condition triggered by the body's exaggerated response to infection, demands urgent intervention to prevent severe complications.
no code implementations • 21 Feb 2024 • Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal
This work offers a hands-on reference for the research progress in deep generative models for offline policy learning, and aims to inspire improved DGM-based offline RL or IL algorithms.
no code implementations • 30 Jan 2024 • Long Liu, Xin Wang, Fangming Li, Jiayu Chen
To solve those problems, We propose a novel active generative network (AGN), which can adaptively learn various action categories by motion style transfer to generate new actions when the data for a particular action is only a single sample or few samples.
1 code implementation • 25 Jan 2024 • Tianhe Ren, Shilong Liu, Ailing Zeng, Jing Lin, Kunchang Li, He Cao, Jiayu Chen, Xinyu Huang, Yukang Chen, Feng Yan, Zhaoyang Zeng, Hao Zhang, Feng Li, Jie Yang, Hongyang Li, Qing Jiang, Lei Zhang
We introduce Grounded SAM, which uses Grounding DINO as an open-set object detector to combine with the segment anything model (SAM).
no code implementations • 19 Dec 2023 • Jiayu Chen, Guosheng Li, Chao Yu, Xinyi Yang, Botian Xu, Huazhong Yang, Yu Wang
In this work, we combine RL and curriculum learning to introduce a flexible solver for multiagent pursuit problems, named TaskFlex Solver (TFS), which is capable of solving multi-agent pursuit problems with diverse and dynamically changing task conditions in both 2-dimensional and 3-dimensional scenarios.
no code implementations • 5 Dec 2023 • Xinyi Yang, Xinting Yang, Chao Yu, Jiayu Chen, Huazhong Yang, Yu Wang
Besides, to enhance generalization capabilities in scenarios with unseen team sizes, we divide agents into multiple groups, each with a previously trained number of agents.
1 code implementation • 6 Nov 2023 • Bishal Thapaliya, Esra Akbas, Jiayu Chen, Raam Sapkota, Bhaskar Ray, Pranav Suresh, Vince Calhoun, Jingyu Liu
Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying on a specific task or stimuli.
no code implementations • 1 Nov 2023 • Xinyi Yang, Yuxiang Yang, Chao Yu, Jiayu Chen, Jingchen Yu, Haibing Ren, Huazhong Yang, Yu Wang
In this paper, we propose Multi-Agent Neural Topological Mapping (MANTM) to improve exploration efficiency and generalization for multi-agent exploration tasks.
no code implementations • 9 Oct 2023 • Weifeng Lin, Ziheng Wu, Jiayu Chen, Wentao Yang, Mingxin Huang, Jun Huang, Lianwen Jin
Fine-tuning pre-trained Vision Transformers (ViT) has consistently demonstrated promising performance in the realm of visual recognition.
no code implementations • 7 Oct 2023 • Jiayu Chen, Zelai Xu, Yunfei Li, Chao Yu, Jiaming Song, Huazhong Yang, Fei Fang, Yu Wang, Yi Wu
In this work, we present a novel subgame curriculum learning framework for zero-sum games.
no code implementations • 21 Sep 2023 • Zhenzhen Chu, Jiayu Chen, Cen Chen, Chengyu Wang, Ziheng Wu, Jun Huang, Weining Qian
Position-aware global tokens also contain the position information of the image, which makes our model better for vision tasks.
no code implementations • 21 Jul 2023 • Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal
Our key idea is to approximate the joint state space as a Kronecker graph, based on which we can directly estimate its Fiedler vector using the Laplacian spectrum of individual agents' transition graphs.
1 code implementation • ICCV 2023 • Weifeng Lin, Ziheng Wu, Jiayu Chen, Jun Huang, Lianwen Jin
Specifically, SMT with 11. 5M / 2. 4GFLOPs and 32M / 7. 7GFLOPs can achieve 82. 2% and 84. 3% top-1 accuracy on ImageNet-1K, respectively.
1 code implementation • 27 May 2023 • Jiayu Chen, Tian Lan, Vaneet Aggarwal
Imperfect Information Games (IIGs) offer robust models for scenarios where decision-makers face uncertainty or lack complete information.
1 code implementation • 22 May 2023 • Jiayu Chen, Dipesh Tamboli, Tian Lan, Vaneet Aggarwal
Multi-task Imitation Learning (MIL) aims to train a policy capable of performing a distribution of tasks based on multi-task expert demonstrations, which is essential for general-purpose robots.
1 code implementation • ICCV 2023 • Shilong Liu, Tianhe Ren, Jiayu Chen, Zhaoyang Zeng, Hao Zhang, Feng Li, Hongyang Li, Jun Huang, Hang Su, Jun Zhu, Lei Zhang
We point out that the unstable matching in DETR is caused by a multi-optimization path problem, which is highlighted by the one-to-one matching design in DETR.
2 code implementations • 9 Jan 2023 • Chao Yu, Xinyi Yang, Jiaxuan Gao, Jiayu Chen, Yunfei Li, Jijia Liu, Yunfei Xiang, Ruixin Huang, Huazhong Yang, Yi Wu, Yu Wang
Simply waiting for every robot being ready for the next action can be particularly time-inefficient.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 7 Oct 2022 • Jiayu Chen, Marina Haliem, Tian Lan, Vaneet Aggarwal
In this case, we propose Multi-agent Deep Covering Option Discovery, which constructs the multi-agent options through minimizing the expected cover time of the multiple agents' joint state space.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 5 Oct 2022 • Jiayu Chen, Tian Lan, Vaneet Aggarwal
In this work, we develop a novel HIL algorithm based on Adversarial Inverse Reinforcement Learning and adapt it with the Expectation-Maximization algorithm in order to directly recover a hierarchical policy from the unannotated demonstrations.
no code implementations • 15 Sep 2022 • Yuda Bi, Anees Abrol, Zening Fu, Jiayu Chen, Jingyu Liu, Vince Calhoun
Prior work has demonstrated that deep learning models that take advantage of the data's 3D structure can outperform standard machine learning on several learning tasks.
no code implementations • 20 Jan 2022 • Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal
Covering skill (a. k. a., option) discovery has been developed to improve the exploration of reinforcement learning in single-agent scenarios with sparse reward signals, through connecting the most distant states in the embedding space provided by the Fiedler vector of the state transition graph.
1 code implementation • NeurIPS 2021 • Jiayu Chen, Yuanxin Zhang, Yuanfan Xu, Huimin Ma, Huazhong Yang, Jiaming Song, Yu Wang, Yi Wu
We motivate our paradigm through a variational perspective, where the learning objective can be decomposed into two terms: task learning on the current task distribution, and curriculum update to a new task distribution.
1 code implementation • 5 Mar 2021 • Jiayu Chen, Abhishek K. Umrawal, Tian Lan, Vaneet Aggarwal
Then an efficient multi-transfer matching algorithm is executed to assign the delivery requests to the trucks.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 27 May 2020 • Wonryong Ryou, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Dan, Martin Vechev
We present a scalable and precise verifier for recurrent neural networks, called Prover based on two novel ideas: (i) a method to compute a set of polyhedral abstractions for the non-convex and nonlinear recurrent update functions by combining sampling, optimization, and Fermat's theorem, and (ii) a gradient descent based algorithm for abstraction refinement guided by the certification problem that combines multiple abstractions for each neuron.
no code implementations • 19 Nov 2019 • Pin Wang, Dapeng Liu, Jiayu Chen, Hanhan Li, Ching-Yao Chan
Simulation results show that the augmented AIRL outperforms all the baseline methods, and its performance is comparable with that of the experts on all of the four metrics.
no code implementations • CONLL 2019 • Jiayu Chen, Caixia Yuan, Xiaojie Wang, Ziwei Bai
This paper focuses on how to extract multiple relational facts from unstructured text.