no code implementations • 24 May 2024 • Sheng Yue, Xingyuan Hua, Lili Chen, Ju Ren
Federated Reinforcement Learning (FRL) has garnered increasing attention recently.
no code implementations • 23 May 2024 • Hanzhang Tu, Ruizhi Shao, Xue Dong, Shunyuan Zheng, Hao Zhang, Lili Chen, Meili Wang, Wenyu Li, Siyan Ma, Shengping Zhang, Boyao Zhou, Yebin Liu
Altogether, our telepresence system demonstrates the sense of co-presence in real-life experiments, inspiring the next generation of communication.
no code implementations • 7 Dec 2023 • Lili Chen, Shikhar Bahl, Deepak Pathak
To make diffusion models more useful for skill learning, we encourage robotic agents to acquire a vocabulary of skills by introducing discrete bottlenecks into the conditional behavior generation process.
no code implementations • 22 May 2023 • Lili Chen, Jingge Zhu, Jamie Evans
Since unpaired transmitters and receivers are often spatially distant, the distance-based threshold is proposed to reduce the computation time by excluding or including the channel state information in GNNs.
no code implementations • CVPR 2023 • Shikhar Bahl, Russell Mendonca, Lili Chen, Unnat Jain, Deepak Pathak
Utilizing internet videos of human behavior, we train a visual affordance model that estimates where and how in the scene a human is likely to interact.
no code implementations • 27 Mar 2023 • Lili Chen, Jingge Zhu, Jamie Evans
We further refine this trade-off by introducing a distance-based threshold for inclusion or exclusion of edges in the network.
no code implementations • SenSys 2022 • Yongjian Fu, Shuning Wang, Linghui Zhong, Lili Chen, Ju Ren, Yaoxue Zhang
The design of introduces a new model that provides the unique mapping relationship between ultrasound and speech signals, so that the audible speech can be successfully reconstructed from the silent speech.
no code implementations • 27 Oct 2022 • Lili Chen, Wensheng Gan, Chien-Ming Chen
To compensate for this deficiency, high-utility sequential rule mining (HUSRM) is designed to explore the confidence or probability of predicting the occurrence of consequence sequential patterns based on the appearance of premise sequential patterns.
no code implementations • 29 Nov 2021 • Wensheng Gan, Lili Chen, Shicheng Wan, Jiahui Chen, Chien-Ming Chen
Analyzing sequence data usually leads to the discovery of interesting patterns and then anomaly detection.
no code implementations • 24 Nov 2021 • Chien-Ming Chen, Lili Chen, Wensheng Gan
Based on the analysis of the proportion of utility in the supporting transactions used in the field of data mining, high utility-occupancy pattern mining (HUOPM) has recently attracted widespread attention.
no code implementations • 8 Aug 2021 • Yaobin Xu, Weitang Liu, Zhongyi Jiang, Zixuan Xu, Tingyun Mao, Lili Chen, Mingwei Zhou
In this paper, we propose a Multi-adaptive Spatiotemporal-flow Graph Neural Network (MAF-GNN) for traffic speed forecasting.
16 code implementations • NeurIPS 2021 • Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
In particular, we present Decision Transformer, an architecture that casts the problem of RL as conditional sequence modeling.
Ranked #3 on Offline RL on D4RL
1 code implementation • NeurIPS 2021 • Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel
Recent advances in off-policy deep reinforcement learning (RL) have led to impressive success in complex tasks from visual observations.
Ranked #33 on Atari Games on Atari 2600 Amidar
2 code implementations • ICLR Workshop SSL-RL 2021 • Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
Recent exploration methods have proven to be a recipe for improving sample-efficiency in deep reinforcement learning (RL).
no code implementations • 1 Jan 2021 • Lili Chen, Kimin Lee, Aravind Srinivas, Pieter Abbeel
In this paper, we present Latent Vector Experience Replay (LeVER), a simple modification of existing off-policy RL methods, to address these computational and memory requirements without sacrificing the performance of RL agents.
no code implementations • 18 Aug 2020 • Chien-Ming Chen, Lili Chen, Wensheng Gan, Lina Qiu, Weiping Ding
To find patterns that can represent the supporting transaction, a recent study was conducted to mine high utility-occupancy patterns whose contribution to the utility of the entire transaction is greater than a certain value.
Databases
no code implementations • 25 Jun 2020 • Jingang Tan, Lili Chen, Kangru Wang, Jingquan Peng, Jiamao Li, Xiaolin Zhang
We propose a novel 3D point cloud segmentation framework named SASO, which jointly performs semantic and instance segmentation tasks.
Ranked #2 on 3D Instance Segmentation on S3DIS (mIoU metric)
3D Instance Segmentation 3D Semantic Instance Segmentation +4
no code implementations • 1 Mar 2020 • Liang Du, Jingang Tan, xiangyang xue, Lili Chen, Hongkai Wen, Jianfeng Feng, Jiamao Li, Xiaolin Zhang
We propose a novel fast and robust 3D point clouds segmentation framework via coupled feature selection, named 3DCFS, that jointly performs semantic and instance segmentation.
no code implementations • 27 Sep 2016 • Kangru Wang, Lei Qu, Lili Chen, Yuzhang Gu, DongChen zhu, Xiaolin Zhang
The main contribution of this paper is a newly proposed descriptor which is implemented in the disparity image to obtain a disparity texture image.