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Richard Y. D. Xu
Richard Yi Da Xu – Richard Yida Xu – Richard Xu
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2020 – today
- 2024
- [i33]Miaoge Li, Jingcai Guo, Richard Yi Da Xu, Dongsheng Wang, Xiaofeng Cao, Song Guo:
TsCA: On the Semantic Consistency Alignment via Conditional Transport for Compositional Zero-Shot Learning. CoRR abs/2408.08703 (2024) - 2023
- [j48]Can Zhang, Richard Yi Da Xu, Xu Zhang, Wanming Huang:
Capture and control content discrepancies via normalised flow transfer. Pattern Recognit. Lett. 165: 161-167 (2023) - [j47]Yi Huang, Ying Li, Guillaume Jourjon, Suranga Seneviratne, Kanchana Thilakarathna, Adriel Cheng, Darren Webb, Richard Yi Da Xu:
Calibrated reconstruction based adversarial autoencoder model for novelty detection. Pattern Recognit. Lett. 169: 50-57 (2023) - [j46]Wei Huang, Chunrui Liu, Yilan Chen, Richard Yi Da Xu, Miao Zhang, Tsui-Wei Weng:
Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection. Trans. Mach. Learn. Res. 2023 (2023) - [c64]Sen Pei, Jiaxi Sun, Richard Yi Da Xu, Shiming Xiang, Gaofeng Meng:
Domain Decorrelation with Potential Energy Ranking. AAAI 2023: 2020-2028 - [c63]Shengchao Zhou, Gaofeng Meng, Zhaoxiang Zhang, Richard Yi Da Xu, Shiming Xiang:
Robust Feature Rectification of Pretrained Vision Models for Object Recognition. AAAI 2023: 3796-3804 - [c62]Qimeng Cao, Qing Yin, Yunya Song, Zhihua Wang, Yujun Chen, Richard Yi Da Xu, Xian Yang:
RTANet: Recommendation Target-Aware Network Embedding. ICWSM 2023: 84-94 - [i32]Hong-Bo Xie, Caoyuan Li, Shuliang Wang, Richard Yi Da Xu, Kerrie L. Mengersen:
A variational autoencoder-based nonnegative matrix factorisation model for deep dictionary learning. CoRR abs/2301.07272 (2023) - [i31]Haotian Li, Lingzhi Wang, Yuliang Wei, Richard Yi Da Xu, Bailing Wang:
KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation. CoRR abs/2309.14770 (2023) - 2022
- [j45]Helen H. Lou, Jian Fang, Huilong Gai, Richard Xu, Sidney Lin:
A novel zone-based machine learning approach for the prediction of the performance of industrial flares. Comput. Chem. Eng. 162: 107795 (2022) - [j44]Ying Li, Yi Huang, Suranga Seneviratne, Kanchana Thilakarathna, Adriel Cheng, Guillaume Jourjon, Darren Webb, David B. Smith, Richard Yi Da Xu:
From traffic classes to content: A hierarchical approach for encrypted traffic classification. Comput. Networks 212: 109017 (2022) - [j43]Chenghao Zhang, Gaofeng Meng, Richard Yi Da Xu, Shiming Xiang, Chunhong Pan:
Learning adversarial point-wise domain alignment for stereo matching. Neurocomputing 491: 564-574 (2022) - [j42]Zhenguo Shi, Qingqing Cheng, J. Andrew Zhang, Richard Yida Xu:
Environment-Robust WiFi-Based Human Activity Recognition Using Enhanced CSI and Deep Learning. IEEE Internet Things J. 9(24): 24643-24654 (2022) - [j41]Steven Y. K. Wong, Jennifer S. K. Chan, Lamiae Azizi, Richard Y. D. Xu:
Time-varying neural network for stock return prediction. Intell. Syst. Account. Finance Manag. 29(1): 3-18 (2022) - [j40]Xian Yang, Shuo Wang, Yuting Xing, Ling Li, Richard Yi Da Xu, Karl J. Friston, Yike Guo:
Bayesian data assimilation for estimating instantaneous reproduction numbers during epidemics: Applications to COVID-19. PLoS Comput. Biol. 18(2) (2022) - [j39]Yi Huang, Ying Li, Timothy Heyes, Guillaume Jourjon, Adriel Cheng, Suranga Seneviratne, Kanchana Thilakarathna, Darren Webb, Richard Yi Da Xu:
Task adaptive siamese neural networks for open-set recognition of encrypted network traffic with bidirectional dropout. Pattern Recognit. Lett. 159: 132-139 (2022) - [j38]Andre Pearce, J. Andrew Zhang, Richard Xu:
A Combined mmWave Tracking and Classification Framework Using a Camera for Labeling and Supervised Learning. Sensors 22(22): 8859 (2022) - [j37]Ziyue Zhang, Shuai Jiang, Congzhentao Huang, Richard Yi Da Xu:
Unsupervised Clothing Change Adaptive Person ReID. IEEE Signal Process. Lett. 29: 304-308 (2022) - [j36]Shuai Jiang, Kan Li, Richard Yi Da Xu:
Magnitude Bounded Matrix Factorisation for Recommender Systems. IEEE Trans. Knowl. Data Eng. 34(4): 1856-1869 (2022) - [j35]Zhenguo Shi, J. Andrew Zhang, Richard Yida Xu, Qingqing Cheng:
Environment-Robust Device-Free Human Activity Recognition With Channel-State-Information Enhancement and One-Shot Learning. IEEE Trans. Mob. Comput. 21(2): 540-554 (2022) - [c61]Qing Yin, Zhihua Wang, Yunya Song, Richard Yida Xu, Shuai Niu, Liang Bai, Yike Guo, Xian Yang:
Improving Deep Embedded Clustering via Learning Cluster-level Representations. COLING 2022: 2226-2236 - [c60]Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang:
Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective. ICLR 2022 - [c59]Lu Mi, Richard Xu, Sridhama Prakhya, Albert Lin, Nir Shavit, Aravinthan D. T. Samuel, Srinivas C. Turaga:
Connectome-constrained Latent Variable Model of Whole-Brain Neural Activity. ICLR 2022 - [i30]Wei Huang, Chunrui Liu, Yilan Chen, Tianyu Liu, Richard Yi Da Xu:
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning. CoRR abs/2202.01958 (2022) - [i29]Leijie Wu, Song Guo, Yaohong Ding, Junxiao Wang, Wenchao Xu, Richard Yida Xu, Jie Zhang:
Demystify Self-Attention in Vision Transformers from a Semantic Perspective: Analysis and Application. CoRR abs/2211.08543 (2022) - [i28]Yingchun Wang, Song Guo, Jingcai Guo, Weizhan Zhang, Richard Yida Xu, Jie Zhang, Yi Liu:
Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning. CoRR abs/2212.03537 (2022) - 2021
- [j34]Ziyue Zhang, Shuai Jiang, Congzhentao Huang, Yang Li, Richard Yi Da Xu:
RGB-IR cross-modality person ReID based on teacher-student GAN model. Pattern Recognit. Lett. 150: 155-161 (2021) - [j33]Wei Huang, Richard Yi Da Xu:
Gaussian process latent variable model factorization for context-aware recommender systems. Pattern Recognit. Lett. 151: 281-287 (2021) - [j32]Caoyuan Li, Hong-Bo Xie, Xuhui Fan, Richard Yi Da Xu, Sabine Van Huffel, Kerrie L. Mengersen:
Kernelized Sparse Bayesian Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. 32(1): 391-404 (2021) - [c58]Christos Markos, James J. Q. Yu, Richard Yi Da Xu:
Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning. AAAI 2021: 390-398 - [c57]Chapman Siu, Jason Traish, Richard Yi Da Xu:
Dynamic Coordination Graph for Cooperative Multi-Agent Reinforcement Learning. ACML 2021: 438-453 - [c56]Steven Y. K. Wong, Jennifer S. K. Chan, Lamiae Azizi, Richard Y. D. Xu:
Supervised Temporal Autoencoder for Stock Return Time-series Forecasting. COMPSAC 2021: 1735-1741 - [c55]Ziyue Zhang, Shuai Jiang, Congzhentao Huang, Richard Yi Da Xu:
Resolution-Invariant Person Reid Based On Feature Transformation And Self-Weighted Attention. ICIP 2021: 1134-1138 - [c54]Wei Huang, Weitao Du, Richard Yi Da Xu:
On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization. IJCAI 2021: 2577-2583 - [i27]Ziyue Zhang, Shuai Jiang, Congzhentao Huang, Richard Yi Da Xu:
Resolution-invariant Person ReID Based on Feature Transformation and Self-weighted Attention. CoRR abs/2101.04544 (2021) - [i26]Wei Huang, Yayong Li, Weitao Du, Richard Yi Da Xu, Jie Yin, Ling Chen:
Wide Graph Neural Networks: Aggregation Provably Leads to Exponentially Trainability Loss. CoRR abs/2103.03113 (2021) - [i25]Sen Pei, Richard Yi Da Xu, Shiming Xiang, Gaofeng Meng:
Alleviating Mode Collapse in GAN via Diversity Penalty Module. CoRR abs/2108.02353 (2021) - [i24]Ziyue Zhang, Shuai Jiang, Congzhentao Huang, Richard Yida Xu:
Unsupervised clothing change adaptive person ReID. CoRR abs/2109.03702 (2021) - [i23]Chapman Siu, Jason M. Traish, Richard Yi Da Xu:
Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning. CoRR abs/2109.09034 (2021) - [i22]Chapman Siu, Jason M. Traish, Richard Yi Da Xu:
Dual Behavior Regularized Reinforcement Learning. CoRR abs/2109.09037 (2021) - [i21]Chapman Siu, Jason Traish, Richard Yi Da Xu:
Regularize! Don't Mix: Multi-Agent Reinforcement Learning without Explicit Centralized Structures. CoRR abs/2109.09038 (2021) - [i20]Sen Pei, Xin Zhang, Richard Yida Xu, Gaofeng Meng:
GAN Based Boundary Aware Classifier for Detecting Out-of-distribution Samples. CoRR abs/2112.11648 (2021) - 2020
- [j31]Kael Dai, Sergey L. Gratiy, Yazan N. Billeh, Richard Xu, Binghuang Cai, Nicholas Cain, Atle E. Rimehaug, Alexander J. Stasik, Gaute T. Einevoll, Stefan Mihalas, Christof Koch, Anton Arkhipov:
Brain Modeling ToolKit: An open source software suite for multiscale modeling of brain circuits. PLoS Comput. Biol. 16(11) (2020) - [j30]Yang Li, Kan Li, Xinxin Wang, Richard Yi Da Xu:
Exploring temporal consistency for human pose estimation in videos. Pattern Recognit. 103: 107258 (2020) - [j29]Minqi Li, Richard Yida Xu, Jing Xin, Kaibing Zhang, Junfeng Jing:
Fast non-rigid points registration with cluster correspondences projection. Signal Process. 170: 107425 (2020) - [j28]Caoyuan Li, Hong-Bo Xie, Kerrie L. Mengersen, Xuhui Fan, Richard Yi Da Xu, Scott A. Sisson, Sabine Van Huffel:
Bayesian Nonnegative Matrix Factorization With Dirichlet Process Mixtures. IEEE Trans. Signal Process. 68: 3860-3870 (2020) - [c53]Yang Li, Kan Li, Shuai Jiang, Ziyue Zhang, Congzhentao Huang, Richard Yi Da Xu:
Geometry-Driven Self-Supervised Method for 3D Human Pose Estimation. AAAI 2020: 11442-11449 - [c52]Wei Huang, Richard Yi Da Xu, Weitao Du, Yutian Zeng, Yunce Zhao:
Mean Field Theory for Deep Dropout Networks: Digging up Gradient Backpropagation Deeply. ECAI 2020: 1215-1222 - [c51]Congzhentao Huang, Shuai Jiang, Yang Li, Ziyue Zhang, Jason M. Traish, Chen Deng, Sam Ferguson, Richard Yi Da Xu:
End-to-end Dynamic Matching Network for Multi-view Multi-person 3D Pose Estimation. ECCV (28) 2020: 477-493 - [c50]Zhenguo Shi, J. Andrew Zhang, Richard Y. D. Xu, Qingqing Cheng, Andre Pearce:
Towards Environment-independent Human Activity Recognition using Deep Learning and Enhanced CSI. GLOBECOM 2020: 1-6 - [c49]Zhenguo Shi, J. Andrew Zhang, Richard Yida Xu, Qingqing Cheng:
WiFi-Based Activity Recognition using Activity Filter and Enhanced Correlation with Deep Learning. ICC Workshops 2020: 1-6 - [c48]Ziyue Zhang, Richard Yi Da Xu, Shuai Jiang, Yang Li, Congzhentao Huang, Chen Deng:
Illumination Adaptive Person Reid Based on Teacher-Student Model and Adversarial Training. ICIP 2020: 2321-2325 - [c47]Siqi Zhang, Ling Luo, Zhidong Li, Yang Wang, Fang Chen, Richard Xu:
Simultaneous Customer Segmentation and Behavior Discovery. ICONIP (4) 2020: 122-130 - [c46]Wanming Huang, Richard Yida Xu, Shuai Jiang, Xuan Liang, Ian J. Oppermann:
GAN-based Gaussian Mixture Model Responsibility Learning. ICPR 2020: 3467-3474 - [c45]Jingwei Liu, J. Andrew Zhang, Richard Xu, Andre Pearce, Wei Ni, Mark Hedley:
Gaussian Mixture Model based Convolutional Sparse Coding for Radar Heartbeat Detection. ICSPCS 2020: 1-6 - [c44]Hong-Bo Xie, Caoyuan Li, Kerrie L. Mengersen, Shuliang Wang, Richard Yi Da Xu:
Nonparametric Bayesian Nonnegative Matrix Factorization. MDAI 2020: 132-141 - [c43]Luke Marsh, Madeleine Cochrane, Riley Lodge, Brendan Sims, Jason M. Traish, Richard Y. D. Xu:
Autonomous Target Allocation Recommendations. SSCI 2020: 1403-1410 - [i19]Ziyue Zhang, Richard Y. D. Xu, Shuai Jiang, Yang Li, Congzhentao Huang, Chen Deng:
Illumination adaptive person reid based on teacher-student model and adversarial training. CoRR abs/2002.01625 (2020) - [i18]Steven Y. K. Wong, Jennifer S. K. Chan, Lamiae Azizi, Richard Y. D. Xu:
Non-stationary neural network for stock return prediction. CoRR abs/2003.02515 (2020) - [i17]Wei Huang, Weitao Du, Richard Yi Da Xu:
On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization. CoRR abs/2004.05867 (2020) - [i16]Ziyue Zhang, Shuai Jiang, Congzhentao Huang, Yang Li, Richard Yi Da Xu:
RGB-IR Cross-modality Person ReID based on Teacher-Student GAN Model. CoRR abs/2007.07452 (2020) - [i15]Wei Huang, Weitao Du, Richard Yi Da Xu, Chunrui Liu:
Implicit bias of deep linear networks in the large learning rate phase. CoRR abs/2011.12547 (2020)
2010 – 2019
- 2019
- [j27]Caoyuan Li, Hong-Bo Xie, Xuhui Fan, Richard Yi Da Xu, Sabine Van Huffel, Scott A. Sisson, Kerrie L. Mengersen:
Image Denoising Based on Nonlocal Bayesian Singular Value Thresholding and Stein's Unbiased Risk Estimator. IEEE Trans. Image Process. 28(10): 4899-4911 (2019) - [j26]Shuai Jiang, Kan Li, Richard Yi Da Xu:
Relative Pairwise Relationship Constrained Non-Negative Matrix Factorisation. IEEE Trans. Knowl. Data Eng. 31(8): 1595-1609 (2019) - [j25]Wei He, Changyin Sun, Donald C. Wunsch, Richard Yi Da Xu:
Guest Editorial Special Issue on Intelligent Control Through Neural Learning and Optimization for Human-Machine Hybrid Systems. IEEE Trans. Neural Networks Learn. Syst. 30(12): 3530-3533 (2019) - [c42]Wanming Huang, Richard Yi Da Xu, Ian J. Oppermann:
Realistic Image Generation using Region-phrase Attention. ACML 2019: 284-299 - [c41]Wanming Huang, Richard Yi Da Xu, Ian J. Oppermann:
Efficient Diversified Mini-Batch Selection using Variable High-layer Features. ACML 2019: 300-315 - [c40]Zhenguo Shi, J. Andrew Zhang, Richard Yi Da Xu, Qingqing Cheng:
Deep Learning Networks for Human Activity Recognition with CSI Correlation Feature Extraction. ICC 2019: 1-6 - [c39]Kai Zhou, Xiangfeng Luo, Hao Wang, Richard Y. D. Xu:
Multi-task Learning for Relation Extraction. ICTAI 2019: 1480-1487 - [c38]Qiongxing Tao, Xiangfeng Luo, Hao Wang, Richard Y. D. Xu:
Enhancing Relation Extraction Using Syntactic Indicators and Sentential Contexts. ICTAI 2019: 1574-1580 - [c37]Hong-Bo Xie, Caoyuan Li, Richard Yi Da Xu, Kerrie L. Mengersen:
Robust Kernelized Bayesian Matrix Factorization for Video Background/Foreground Separation. LOD 2019: 484-495 - [i14]Maoying Qiao, Wei Bian, Richard Yida Xu, Dacheng Tao:
Diversified Hidden Markov Models for Sequential Labeling. CoRR abs/1904.03170 (2019) - [i13]Wei Huang, Richard Yi Da Xu, Weitao Du, Yutian Zeng, Yunce Zhao:
Mean field theory for deep dropout networks: digging up gradient backpropagation deeply. CoRR abs/1912.09132 (2019) - [i12]Wei Huang, Richard Yi Da Xu:
Gaussian Process Latent Variable Model Factorization for Context-aware Recommender Systems. CoRR abs/1912.09593 (2019) - 2018
- [j24]Wankou Yang, Jun Li, Hao Zheng, Richard Yi Da Xu:
A Nuclear Norm Based Matrix Regression Based Projections Method for Feature Extraction. IEEE Access 6: 7445-7451 (2018) - [j23]Xiang Feng, Wanggen Wan, Richard Yi Da Xu, Stuart W. Perry, Pengfei Li, Song Zhu:
A novel spatial pooling method for 3D mesh quality assessment based on percentile weighting strategy. Comput. Graph. 74: 12-22 (2018) - [j22]Xiang Feng, Wanggen Wan, Richard Yi Da Xu, Stuart W. Perry, Song Zhu, Zexin Liu:
A new mesh visual quality metric using saliency weighting-based pooling strategy. Graph. Model. 99: 1-12 (2018) - [j21]Xiang Feng, Wanggen Wan, Richard Yi Da Xu, Haoyu Chen, Pengfei Li, J. Alfredo Sánchez:
A perceptual quality metric for 3D triangle meshes based on spatial pooling. Frontiers Comput. Sci. 12(4): 798-812 (2018) - [j20]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes. IEEE Trans. Neural Networks Learn. Syst. 29(5): 1835-1849 (2018) - [j19]Ava Bargi, Richard Yi Da Xu, Massimo Piccardi:
AdOn HDP-HMM: An Adaptive Online Model for Segmentation and Classification of Sequential Data. IEEE Trans. Neural Networks Learn. Syst. 29(9): 3953-3968 (2018) - [c36]Zhenguo Shi, J. Andrew Zhang, Richard Yi Da Xu, Gengfa Fang:
Human Activity Recognition Using Deep Learning Networks with Enhanced Channel State Information. GLOBECOM Workshops 2018: 1-6 - [c35]Ying Li, Yi Huang, Richard Yi Da Xu, Suranga Seneviratne, Kanchana Thilakarathna, Adriel Cheng, Darren Webb, Guillaume Jourjon:
Deep Content: Unveiling Video Streaming Content from Encrypted WiFi Traffic. NCA 2018: 1-8 - [i11]Shuai Jiang, Kan Li, Richard Yida Xu:
Relative Pairwise Relationship Constrained Non-negative Matrix Factorisation. CoRR abs/1803.02218 (2018) - [i10]Chapman Siu, Richard Yi Da Xu:
Diverse Online Feature Selection. CoRR abs/1806.04308 (2018) - [i9]Shuai Jiang, Kan Li, Richard Yi Da Xu:
Magnitude Bounded Matrix Factorisation for Recommender Systems. CoRR abs/1807.05515 (2018) - 2017
- [j18]Weidong Liu, Xiangfeng Luo, Jun Zhang, Ruirong Xue, Richard Yi Da Xu:
Semantic summary automatic generation in news event. Concurr. Comput. Pract. Exp. 29(24) (2017) - [j17]Yufei Chen, Xiaodong Yue, Richard Yi Da Xu, Hamido Fujita:
Region scalable active contour model with global constraint. Knowl. Based Syst. 120: 57-73 (2017) - [j16]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
A Bayesian nonparametric model for multi-label learning. Mach. Learn. 106(11): 1787-1815 (2017) - [j15]Zheng Xu, Junchi Yan, Richard Yida Xu, Lin Mei:
Guest Editorial: Visual Multimedia Learning from Big Surveillance Data. Multim. Tools Appl. 76(13): 14557 (2017) - [j14]Xuhui Fan, Richard Yi Da Xu, Longbing Cao, Yin Song:
Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network. IEEE Trans. Cybern. 47(3): 589-599 (2017) - [j13]Jiatong Li, Chenwei Deng, Richard Yi Da Xu, Dacheng Tao, Baojun Zhao:
Robust Object Tracking With Discrete Graph-Based Multiple Experts. IEEE Trans. Image Process. 26(6): 2736-2750 (2017) - [j12]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
Bayesian Nonparametric Relational Topic Model through Dependent Gamma Processes. IEEE Trans. Knowl. Data Eng. 29(7): 1357-1369 (2017) - [i8]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu:
Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization. CoRR abs/1707.05420 (2017) - 2016
- [j11]Furong Peng, Jianfeng Lu, Yongli Wang, Richard Yi Da Xu, Chao Ma, Jingyu Yang:
N-dimensional Markov random field prior for cold-start recommendation. Neurocomputing 191: 187-199 (2016) - [j10]Jiatong Li, Baojun Zhao, Chenwei Deng, Richard Yi Da Xu:
Time Varying Metric Learning for visual tracking. Pattern Recognit. Lett. 80: 157-164 (2016) - [j9]Maoying Qiao, Richard Yi Da Xu, Wei Bian, Dacheng Tao:
Fast Sampling for Time-Varying Determinantal Point Processes. ACM Trans. Knowl. Discov. Data 11(1): 8:1-8:24 (2016) - [c34]Qiang Li, Wei Bian, Richard Yi Da Xu, Jane You, Dacheng Tao:
Random Mixed Field Model for Mixed-Attribute Data Restoration. AAAI 2016: 1244-1250 - [c33]Furong Peng, Xuan Lu, Jianfeng Lu, Richard Yi Da Xu, Cheng Luo, Chao Ma, Jingyu Yang:
MetricRec: Metric Learning for Cold-Start Recommendations. ADMA 2016: 445-458 - [c32]Maoying Qiao, Wei Bian, Richard Yi Da Xu, Dacheng Tao:
Diversified hidden Markov models for sequential labeling. ICDE 2016: 1512-1513 - [c31]Xuhui Fan, Richard Yi Da Xu, Longbing Cao:
Copula Mixed-Membership Stochastic Blockmodel. IJCAI 2016: 1462-1468 - 2015
- [j8]Michael Kemp, Richard Yi Da Xu:
Geometrically-constrained balloon fitting for multiple connected ellipses. Pattern Recognit. 48(7): 2198-2208 (2015) - [j7]Maoying Qiao, Wei Bian, Richard Yi Da Xu, Dacheng Tao:
Diversified Hidden Markov Models for Sequential Labeling. IEEE Trans. Knowl. Data Eng. 27(11): 2947-2960 (2015) - [j6]Xuhui Fan, Longbing Cao, Richard Yi Da Xu:
Dynamic Infinite Mixed-Membership Stochastic Blockmodel. IEEE Trans. Neural Networks Learn. Syst. 26(9): 2072-2085 (2015) - [c30]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
Infinite Author Topic Model Based on Mixed Gamma-Negative Binomial Process. ICDM 2015: 489-498 - [c29]Minqi Li, Richard Yi Da Xu, Xiangjian He:
Face hallucination based on nonparametric Bayesian learning. ICIP 2015: 986-990 - [c28]Fengli Zhang, Jun Li, Feng Li, Min Xu, Richard Y. D. Xu, Xiangjian He:
Community Detection Based on Links and Node Features in Social Networks. MMM (1) 2015: 418-429 - [i7]Ava Bargi, Richard Yi Da Xu, Massimo Piccardi:
An Adaptive Online HDP-HMM for Segmentation and Classification of Sequential Data. CoRR abs/1503.02761 (2015) - [i6]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
Infinite Author Topic Model based on Mixed Gamma-Negative Binomial Process. CoRR abs/1503.08535 (2015) - [i5]Junyu Xuan, Jie Lu, Guangquan Zhang, Richard Yi Da Xu, Xiangfeng Luo:
Nonparametric Relational Topic Models through Dependent Gamma Processes. CoRR abs/1503.08542 (2015) - 2014
- [c27]Ava Bargi, Richard Yi Da Xu, Zoubin Ghahramani, Massimo Piccardi:
A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response. AISTATS 2014: 77-85 - [c26]Ava Bargi, Richard Yi Da Xu, Massimo Piccardi:
An Infinite Adaptive Online Learning Model for Segmentation and Classification of Streaming Data. ICPR 2014: 3440-3445 - 2013
- [j5]