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Publication search results
found 21 matches
- 2024
- Weiwei Liu, Wenxuan Hu, Wei Jing, Lanxin Lei, Lingping Gao, Yong Liu:
Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learning. CoRR abs/2402.13481 (2024) - 2022
- Chen Xu, Bing Wang, Lin Yang, Lucas Zhongming Hu, Lanxing Yi, Yaxuan Wang, Shenglan Chen, Andrew Emili, Cuihong Wan:
Global Landscape of Native Protein Complexes in Synechocystis sp. PCC 6803. Genom. Proteom. Bioinform. 20(4): 715-727 (2022) - Lingping Gao, Ziqing Gu, Cong Qiu, Lanxin Lei, Shengbo Eben Li, Sifa Zheng, Wei Jing, Junbo Chen:
Cola-HRL: Continuous-Lattice Hierarchical Reinforcement Learning for Autonomous Driving. IROS 2022: 13143-13150 - Lanxin Wu, Ling Qiu, Xiaowen Liang:
Analysis of RSMA-aided UAV Network: A Stochastic Geometry Approach. VTC Spring 2022: 1-6 - 2020
- Linan Guo, Hongxing Zheng, Yanhong Wu, Tianqi Zhang, Mengxuan Wen, Lanxin Fan, Bing Zhang:
Responses of Lake Ice Phenology to Climate Change at Tibetan Plateau. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 3856-3861 (2020) - 2019
- Sirui Xie, Junning Huang, Lanxin Lei, Chunxiao Liu, Zheng Ma, Wei Zhang, Liang Lin:
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning. ICLR (Poster) 2019 - Lanxin Lei, Zhizhong Li, Dahua Lin:
Biased Estimates of Advantages over Path Ensembles. CoRR abs/1909.06851 (2019) - 2018
- Sirui Xie, Junning Huang, Lanxin Lei, Chunxiao Liu, Zheng Ma, Wei Zhang, Liang Lin:
NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning. CoRR abs/1812.09028 (2018) - 2016
- Jinshuo Liu, Yabo Xu, Juan Deng, Lina Wang, Lanxin Zhang:
Ld-CNNs: A Deep Learning System for Structured Text Categorization Based on LDA in Content Security. NSS 2016: 113-125 - 2014
- Lanxin Lin, Hing-Cheung So, Yiu Tong Chan:
Received signal strength based positioning for multiple nodes in wireless sensor networks. Digit. Signal Process. 25: 41-50 (2014) - Lanxin Lin, Hing-Cheung So, Frankie K. W. Chan:
Multidimensional scaling approach for node localization using received signal strength measurements. Digit. Signal Process. 34: 39-47 (2014) - 2013
- Lanxin Lin, Hing-Cheung So, Yiu Tong Chan:
Accurate and simple source localization using differential received signal strength. Digit. Signal Process. 23(3): 736-743 (2013) - Lanxin Lin, Hing-Cheung So, Frankie K. W. Chan, Yiu Tong Chan, K. C. Ho:
A new constrained weighted least squares algorithm for TDOA-based localization. Signal Process. 93(11): 2872-2878 (2013) - Weize Sun, Hing-Cheung So, Lanxin Lin:
Correlation-based algorithm for multi-dimensional single-tone frequency estimation. Signal Process. 93(4): 765-771 (2013) - 2012
- Lanxin Lin, Minfen Shen, Hing-Cheung So, Chunqi Chang:
Convergence Analysis for Initial Condition Estimation in Coupled Map Lattice Systems. IEEE Trans. Signal Process. 60(8): 4426-4432 (2012) - 2011
- Hing-Cheung So, Lanxin Lin:
Linear Least Squares Approach for Accurate Received Signal Strength Based Source Localization. IEEE Trans. Signal Process. 59(8): 4035-4040 (2011) - Lanxin Lin, Hing-Cheung So:
Best linear unbiased estimator algorithm for received signal strength based localization. EUSIPCO 2011: 1989-1993 - Lanxin Lin, Hing-Cheung So:
New constrained least squares approach for range-based positioning. EUSIPCO 2011: 1999-2003 - 2010
- Minfen Shen, Lanxin Lin, Jialiang Chen, C. Q. Chang:
A Prediction Approach for Multichannel EEG Signals Modeling Using Local Wavelet SVM. IEEE Trans. Instrum. Meas. 59(5): 1485-1492 (2010) - 2008
- Lisha Sun, Lanxin Lin, Chunhao Lin:
Modeling and Prediction of Nonlinear EEG Signal Using Local SVM Method. ICONIP (2) 2008: 426-433 - Minfen Shen, Lanxin Lin, Guoliang Chang:
Novel Coupled Map Lattice Model for Prediction of EEG Signal. ISNN (1) 2008: 347-356
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