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Kuan Liu
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2020 – today
- 2024
- [j13]Hongtao Hou, Mingzhen Guo, Wei Wang, Kuan Liu, Zijiang Luo:
Improved Lightweight Head Detection Based on GhostNet-SSD. Neural Process. Lett. 56(2): 126 (2024) - [j12]Chenyu Zhang, Haohao Qin, Shiying Sun, Yi Pan, Kuan Liu, Tao Li, Xiaoguang Zhao:
JPMDP: Joint base placement and multi-configuration path planning for 3D surface disinfection with a UV-C robotic system. Robotics Auton. Syst. 174: 104644 (2024) - [j11]Ming Chen, Xing Rao, Kuan Liu, Yuhang Wang, Shuqing Chen, Lin Xu, Rendong Xu, George Y. Chen, Yiping Wang:
Distributed Vibration Sensing Based on a Forward Transmission Polarization-Generated Carrier. Sensors 24(16): 5257 (2024) - [j10]Ke Wang, Yanmin Zhu, Tianzi Zang, Chunyang Wang, Kuan Liu, Peibo Ma:
Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation. ACM Trans. Inf. Syst. 42(2): 51:1-51:29 (2024) - [c12]Kuan Liu, Yanmin Zhu, Zhaobo Wang, Ke Wang, Gang Zhou:
Rethinking Normals: Direction Guided Point Cloud Recognition. ICASSP 2024: 8110-8114 - [c11]Kuan Liu, Yanmin Zhu, Zhaobo Wang, Ke Wang, Gang Zhou:
Axis Order Invariance Learned from Point Clouds. ICASSP 2024: 8120-8124 - 2022
- [c10]Ke Wang, Yanmin Zhu, Haobing Liu, Tianzi Zang, Chunyang Wang, Kuan Liu:
Inter- and Intra-Domain Relation-Aware Heterogeneous Graph Convolutional Networks for Cross-Domain Recommendation. DASFAA (2) 2022: 53-68 - 2021
- [j9]Kuan Liu, Haiyuan Liu, Dongyan Sun, Lei Zhang:
Network Inference from Gene Expression Data with Distance Correlation and Network Topology Centrality. Algorithms 14(2): 61 (2021) - [j8]Xin Huang, Xiaoya Dong, Jing Ma, Kuan Liu, Shibbir Ahmed, Jinlong Lin, Baijing Qiu:
The Improved A* Obstacle Avoidance Algorithm for the Plant Protection UAV with Millimeter Wave Radar and Monocular Camera Data Fusion. Remote. Sens. 13(17): 3364 (2021) - [j7]Xing Rao, Lin Zhao, Lukui Xu, Yuhang Wang, Kuan Liu, Ying Wang, George Y. Chen, Tongyu Liu, Yiping Wang:
Review of Optical Humidity Sensors. Sensors 21(23): 8049 (2021) - [c9]Xiangsheng Yi, Zhifeng Shi, Hu Zhao, Ye Fu, Shangjie Ma, Kuan Liu:
Research on optimization of crop planting area estimation from remote sensing data. Agro-Geoinformatics 2021: 1-6
2010 – 2019
- 2019
- [j6]Kuan Liu, Chun Wang, Weizhang Wang, Yujie Chen, Huicheng Wu:
Linear Power Flow Calculation of Distribution Networks With Distributed Generation. IEEE Access 7: 44686-44695 (2019) - [j5]Kuan Liu, Aurélien Bellet:
Escaping the curse of dimensionality in similarity learning: Efficient Frank-Wolfe algorithm and generalization bounds. Neurocomputing 333: 185-199 (2019) - [j4]Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel Hsu, Brian Kingsbury, Michael Picheny, Fei Sha:
Kernel Approximation Methods for Speech Recognition. J. Mach. Learn. Res. 20: 59:1-59:36 (2019) - 2018
- [j3]Hongpeng Liu, Yan Ran, Kuan Liu, Wei Wang, Dianguo Xu:
A Modified Single-Phase Transformerless Y-Source PV Grid-Connected Inverter. IEEE Access 6: 18561-18569 (2018) - [c8]Kuan Liu, Prem Natarajan:
A Batch Learning Framework for Scalable Personalized Ranking. AAAI 2018: 3667-3674 - [c7]Hongpeng Liu, Zichao Zhou, Kuan Liu, Wei Wang:
An Improved Y-Source Inverter with Continuous Input Current. ISIE 2018: 346-351 - [i10]Kuan Liu, Xing Shi, Prem Natarajan:
A Sequential Embedding Approach for Item Recommendation with Heterogeneous Attributes. CoRR abs/1805.11008 (2018) - [i9]Kuan Liu, Yanen Li, Ning Xu, Prem Natarajan:
Learn to Combine Modalities in Multimodal Deep Learning. CoRR abs/1805.11730 (2018) - [i8]Kuan Liu, Aurélien Bellet:
Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds. CoRR abs/1807.07789 (2018) - 2017
- [c6]Kuan Liu, Xing Shi, Prem Natarajan:
Sequential Heterogeneous Attribute Embedding for Item Recommendation. ICDM Workshops 2017: 773-780 - [c5]Kuan Liu, Prem Natarajan:
WMRB: Learning to Rank in a Scalable Batch Training Approach. RecSys Posters 2017 - [i7]Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel J. Hsu, Brian Kingsbury, Michael Picheny, Fei Sha:
Kernel Approximation Methods for Speech Recognition. CoRR abs/1701.03577 (2017) - [i6]Kuan Liu, Prem Natarajan:
WMRB: Learning to Rank in a Scalable Batch Training Approach. CoRR abs/1711.04015 (2017) - [i5]Kuan Liu, Prem Natarajan:
A Batch Learning Framework for Scalable Personalized Ranking. CoRR abs/1711.04019 (2017) - 2016
- [c4]Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
A comparison between deep neural nets and kernel acoustic models for speech recognition. ICASSP 2016: 5070-5074 - [c3]Kuan Liu, Xing Shi, Anoop Kumar, Linhong Zhu, Prem Natarajan:
Temporal learning and sequence modeling for a job recommender system. RecSys Challenge 2016: 7:1-7:4 - [i4]Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition. CoRR abs/1603.05800 (2016) - [i3]Kuan Liu, Xing Shi, Anoop Kumar, Linhong Zhu, Prem Natarajan:
Temporal Learning and Sequence Modeling for a Job Recommender System. CoRR abs/1608.03333 (2016) - 2015
- [j2]Tianxu Zhang, Gang Zhou, Chao Zhang, Gaofei Li, Jianchong Chen, Kuan Liu:
A novel temporal-spatial variable scale algorithm for detecting multiple moving objects. IEEE Trans. Aerosp. Electron. Syst. 51(1): 627-641 (2015) - [j1]Mingzheng Wang, Kuan Liu, Tsan-Ming Choi, Xiaohang Yue:
Effects of Carbon Emission Taxes on Transportation Mode Selections and Social Welfare. IEEE Trans. Syst. Man Cybern. Syst. 45(11): 1413-1423 (2015) - [c2]Kuan Liu, Aurélien Bellet, Fei Sha:
Similarity Learning for High-Dimensional Sparse Data. AISTATS 2015 - 2014
- [i2]Kuan Liu, Aurélien Bellet, Fei Sha:
Similarity Learning for High-Dimensional Sparse Data. CoRR abs/1411.2374 (2014) - [i1]Zhiyun Lu, Avner May, Kuan Liu, Alireza Bagheri Garakani, Dong Guo, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets. CoRR abs/1411.4000 (2014) - 2013
- [c1]Soravit Changpinyo, Kuan Liu, Fei Sha:
Similarity Component Analysis. NIPS 2013: 1511-1519
Coauthor Index
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last updated on 2024-10-04 21:02 CEST by the dblp team
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