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ORCIDQi Yu 0001
Person information
- affiliation: Rochester Institute of Technology, College of Computing and Information Sciences, Henrietta, NY, USA
- affiliation (PhD 2008): Virginia Tech, Department of Computer Science, Blacksburg, VA, USA
Other persons with the same name
- Qi Yu — disambiguation page
- Qi Yu 0002
![[0000-0002-0490-0749]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-0490-0749")
— University of Electronic Science and Technology of China, State Key Laboratory of Electronic Thin Films and Integrated Devices, Chengdu, China - Qi Yu 0003 — National University of Defense Technology, College of Computer, Changsha, China
- Qi Yu 0004 — Aalto University, Helsinki, Finland
- Qi Yu 0005 — Shanxi Medical University, School of Management, Taiyuan, China
- Qi Yu 0006 — Griffith University, Centre of Quantum Dynamics, Brisbane, Queensland, Australia (and 1 more)
- Qi Yu 0007 — University of Konstanz, Department of Linguistics, Cluster of Excellence 'The Politics of Inequality', Germany
- Qi Yu 0008 — Shanghai Jiao Tong University, Shanghai General Hospital, China
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2020 – today
- 2024
[j52]Dayou Yu, Deep Shankar Pandey, Joshua Hinz, Deyan I. Mihaylov, Valentin V. Karasiev, S. X. Hu, Qi Yu:
Deep energy-pressure regression for a thermodynamically consistent EOS model. Mach. Learn. Sci. Technol. 5(1): 15031 (2024)- [j51]Weishi Shi, Heather Moses, Qi Yu, Samuel A. Malachowsky, Daniel E. Krutz:
ALL: Supporting Experiential Accessibility Education and Inclusive Software Development. ACM Trans. Softw. Eng. Methodol. 33(2): 39:1-39:30 (2024) - [c98]Xiaofan Que, Qi Yu:
Dual-Level Curriculum Meta-Learning for Noisy Few-Shot Learning Tasks. AAAI 2024: 14740-14748 - [c97]Xiaofan Que, Qi Yu:
Optimal Transport of Diverse Unsupervised Tasks for Robust Learning from Noisy Few-Shot Data. ECCV (39) 2024: 294-311 - [c96]Abhinab Acharya, Dayou Yu, Qi Yu, Xumin Liu:
Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection. ICML 2024 - [c95]Spandan Pyakurel, Qi Yu:
Hierarchical Novelty Detection via Fine-Grained Evidence Allocation. ICML 2024 - [c94]Hitesh Sapkota, Krishna Prasad Neupane, Qi Yu:
Meta Evidential Transformer for Few-Shot Open-Set Recognition. ICML 2024 - [c93]Dingrong Wang, Hitesh Sapkota, Zhiqiang Tao, Qi Yu:
Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness. KDD 2024: 3001-3012 - [i21]Dingrong Wang, Hitesh Sapkota, Zhiqiang Tao, Qi Yu:
Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness. CoRR abs/2406.06792 (2024) - 2023
- [c92]Ervine Zheng, Qi Yu, Zhi Zheng:
Sparse Maximum Margin Learning from Multimodal Human Behavioral Patterns. AAAI 2023: 5437-5445 - [c91]Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng:
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. AAAI 2023: 8588-8596 - [c90]Deep Shankar Pandey, Qi Yu:
Evidential Conditional Neural Processes. AAAI 2023: 9389-9397 - [c89]Dayou Yu, Weishi Shi, Qi Yu:
STARS: Spatial-Temporal Active Re-sampling for Label-Efficient Learning from Noisy Annotations. AAAI 2023: 10980-10988 - [c88]Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne R. Haake:
Knowledge Acquisition for Human-In-The-Loop Image Captioning. AISTATS 2023: 2191-2206 - [c87]Hitesh Sapkota, Qi Yu:
Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data. ICLR 2023 - [c86]Deep Shankar Pandey, Qi Yu:
Learn to Accumulate Evidence from All Training Samples: Theory and Practice. ICML 2023: 26963-26989 - [c85]Dingrong Wang, Deep Shankar Pandey, Krishna Prasad Neupane, Zhiwei Yu, Ervine Zheng, Zhi Zheng, Qi Yu:
Deep Temporal Sets with Evidential Reinforced Attentions for Unique Behavioral Pattern Discovery. ICML 2023: 36205-36223 - [c84]Dayou Yu, Weishi Shi, Qi Yu:
Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning. ICML 2023: 40321-40338 - [c83]Ervine Zheng, Qi Yu:
Evidential Interactive Learning for Medical Image Captioning. ICML 2023: 42478-42491 - [c82]Hitesh Sapkota, Dingrong Wang, Zhiqiang Tao, Qi Yu:
Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training. NeurIPS 2023 - [c81]Dayou Yu, Weishi Shi, Qi Yu:
Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice. NeurIPS 2023 - [i20]Deep Shankar Pandey, Qi Yu:
Learn to Accumulate Evidence from All Training Samples: Theory and Practice. CoRR abs/2306.11113 (2023) - [i19]Xinmiao Lin, Wentao Bao, Qi Yu, Yu Kong:
On Model Explanations with Transferable Neural Pathways. CoRR abs/2309.09887 (2023) - [i18]Wentao Bao, Qi Yu, Yu Kong:
Latent Space Energy-based Model for Fine-grained Open Set Recognition. CoRR abs/2309.10711 (2023) - 2022
- [j50]Lei Wang, Yunqiu Zhang, Xubin Zheng, Qi Yu, Shuhan Chen, Junyao Ding:
Singular value decomposition-based behavior-aware cloud service application programming interfaces recommendation for large-scale software cloud directory platforms. Concurr. Comput. Pract. Exp. 34(21) (2022) - [c80]Krishna Prasad Neupane, Ervine Zheng, Yu Kong, Qi Yu:
A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations. AAAI 2022: 7868-7876 - [c79]Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne R. Haake:
Dual-Level Adaptive Information Filtering for Interactive Image Segmentation. AISTATS 2022: 6862-6879 - [c78]Wentao Bao, Qi Yu, Yu Kong:
OpenTAL: Towards Open Set Temporal Action Localization. CVPR 2022: 2969-2979 - [c77]Hitesh Sapkota, Qi Yu:
Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection. CVPR 2022: 3202-3211 - [c76]Deep Shankar Pandey, Qi Yu:
Multidimensional Belief Quantification for Label-Efficient Meta-Learning. CVPR 2022: 14371-14380 - [c75]Yuansheng Zhu, Wentao Bao, Qi Yu:
Towards Open Set Video Anomaly Detection. ECCV (34) 2022: 395-412 - [c74]Niranjana Deshpande, Naveen Sharma, Qi Yu, Daniel E. Krutz:
Online Learning Using Incomplete Execution Data for Self-Adaptive Service-Oriented Systems. ICWS 2022: 296-301 - [c73]Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo:
Spiking Graph Convolutional Networks. IJCAI 2022: 2434-2440 - [c72]Hitesh Sapkota, Qi Yu:
Balancing Bias and Variance for Active Weakly Supervised Learning. KDD 2022: 1536-1546 - [c71]Moayad Alshangiti, Weishi Shi, Eduardo Lima, Xumin Liu, Qi Yu:
Hierarchical Bayesian multi-kernel learning for integrated classification and summarization of app reviews. ESEC/SIGSOFT FSE 2022: 558-569 - [i17]Wentao Bao, Qi Yu, Yu Kong:
OpenTAL: Towards Open Set Temporal Action Localization. CoRR abs/2203.05114 (2022) - [i16]Deep Shankar Pandey, Qi Yu:
Multidimensional Belief Quantification for Label-Efficient Meta-Learning. CoRR abs/2203.12768 (2022) - [i15]Hitesh Sapkota, Qi Yu:
Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection. CoRR abs/2203.12840 (2022) - [i14]Krishna Prasad Neupane, Ervine Zheng, Yu Kong, Qi Yu:
A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations. CoRR abs/2204.00970 (2022) - [i13]Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo:
Spiking Graph Convolutional Networks. CoRR abs/2205.02767 (2022) - [i12]Hitesh Sapkota, Qi Yu:
Balancing Bias and Variance for Active Weakly Supervised Learning. CoRR abs/2206.05682 (2022) - [i11]Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng:
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. CoRR abs/2208.10364 (2022) - [i10]Yuansheng Zhu, Wentao Bao, Qi Yu:
Towards Open Set Video Anomaly Detection. CoRR abs/2208.11113 (2022) - [i9]Deep Shankar Pandey, Qi Yu:
Evidential Conditional Neural Processes. CoRR abs/2212.00131 (2022) - 2021
- [j49]Rui Liu, Chao Peng, Yunbo Zhang, Hannah Husarek, Qi Yu:
A survey of immersive technologies and applications for industrial product development. Comput. Graph. 100: 137-151 (2021) - [c70]Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne R. Haake:
A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation. AAAI 2021: 6030-6038 - [c69]Weishi Shi, Qi Yu:
Active Learning with Maximum Margin Sparse Gaussian Processes. AISTATS 2021: 406-414 - [c68]Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu:
Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning. AISTATS 2021: 2188-2196 - [c67]Yuansheng Zhu, Weishi Shi, Deep Shankar Pandey, Yang Liu, Xiaofan Que, Daniel E. Krutz, Qi Yu:
Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data. IEEE BigData 2021: 1772-1778 - [c66]Wentao Bao, Qi Yu, Yu Kong:
DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation. ICCV 2021: 7599-7608 - [c65]Wentao Bao, Qi Yu, Yu Kong:
Evidential Deep Learning for Open Set Action Recognition. ICCV 2021: 13329-13338 - [c64]Dingrong Wang, Hitesh Sapkota, Xumin Liu, Qi Yu:
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval. ICDM 2021: 669-678 - [c63]Krishna Prasad Neupane, Ervine Zheng, Qi Yu:
MetaEDL: Meta Evidential Learning For Uncertainty-Aware Cold-Start Recommendations. ICDM 2021: 1258-1263 - [c62]Niranjana Deshpande, Naveen Sharma, Qi Yu, Daniel E. Krutz:
R-CASS: Using Algorithm Selection for Self-Adaptive Service Oriented Systems. ICWS 2021: 61-72 - [c61]Weishi Shi, Dayou Yu, Qi Yu:
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning. NeurIPS 2021: 27542-27554 - [i8]Wentao Bao, Qi Yu, Yu Kong:
Evidential Deep Learning for Open Set Action Recognition. CoRR abs/2107.10161 (2021) - [i7]Wentao Bao, Qi Yu, Yu Kong:
DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation. CoRR abs/2107.10189 (2021) - [i6]Yuansheng Zhu, Weishi Shi, Deep Shankar Pandey, Yang Liu, Xiaofan Que, Daniel E. Krutz, Qi Yu:
Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data. CoRR abs/2111.08625 (2021) - [i5]Dingrong Wang, Hitesh Sapkota, Xumin Liu, Qi Yu:
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval. CoRR abs/2111.10917 (2021) - 2020
- [j48]Shunshun Peng, Hongbing Wang, Qi Yu:
Multi-Clusters Adaptive Brain Storm Optimization Algorithm for QoS-Aware Service Composition. IEEE Access 8: 48822-48835 (2020) - [j47]Moayad Alshangiti, Weishi Shi, Xumin Liu, Qi Yu:
A Bayesian learning model for design-phase service mashup popularity prediction. Expert Syst. Appl. 149: 113231 (2020) - [j46]Hongbing Wang, Jiajie Li, Qi Yu, Tianjing Hong, Jia Yan, Wei Zhao:
Integrating recurrent neural networks and reinforcement learning for dynamic service composition. Future Gener. Comput. Syst. 107: 551-563 (2020) - [j45]Hongbing Wang, Xingguo Hu, Qi Yu, Mingzhu Gu, Wei Zhao, Jia Yan, Tianjing Hong:
Integrating reinforcement learning and skyline computing for adaptive service composition. Inf. Sci. 519: 141-160 (2020) - [j44]Peng-Nien Yin, Kishan KC, Shishi Wei, Qi Yu, Rui Li, Anne R. Haake, Hiroshi Miyamoto, Feng Cui:
Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches. BMC Medical Informatics Decis. Mak. 20(1): 162 (2020) - [c60]Yasmine N. El-Glaly, Weishi Shi, Samuel A. Malachowsky, Qi Yu, Daniel E. Krutz:
Presenting and evaluating the impact of experiential learning in computing accessibility education. ICSE (SEET) 2020: 49-60 - [c59]Weishi Shi, Saad Khan, Yasmine N. El-Glaly, Samuel A. Malachowsky, Qi Yu, Daniel E. Krutz:
Experiential learning in computing accessibility education. ICSE (Companion Volume) 2020: 250-251 - [c58]Wentao Bao, Qi Yu, Yu Kong:
Object-Aware Centroid Voting for Monocular 3D Object Detection. IROS 2020: 2197-2204 - [c57]Wentao Bao, Qi Yu, Yu Kong:
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning. ACM Multimedia 2020: 2682-2690 - [c56]Weishi Shi, Xujiang Zhao, Feng Chen, Qi Yu:
Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning. NeurIPS 2020 - [c55]Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, Anne R. Haake:
Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich Domains. NeurIPS 2020 - [c54]Jai W. Kang, Qi Yu, Edward P. Holden, Erik Golen, Michael McQuaid:
Analytics Prevalent Undergraduate IT Program. SIGITE 2020: 26-31 - [e6]Sami Yangui, Athman Bouguettaya, Xiao Xue, Noura Faci, Walid Gaaloul, Qi Yu, Zhangbing Zhou, Nathalie Hernandez, Elisa Yumi Nakagawa:
Service-Oriented Computing - ICSOC 2019 Workshops - WESOACS, ASOCA, ISYCC, TBCE, and STRAPS, Toulouse, France, October 28-31, 2019, Revised Selected Papers. Lecture Notes in Computer Science 12019, Springer 2020, ISBN 978-3-030-45988-8 [contents] - [i4]Weishi Shi, Samuel A. Malachowsky, Yasmine N. El-Glaly, Qi Yu, Daniel E. Krutz:
Presenting and Evaluating the Impact of Experiential Learning in Computing Accessibility Education. CoRR abs/2002.06445 (2020) - [i3]Jeffrey Palmerino, Qi Yu, Travis Desell, Daniel E. Krutz:
Improving the Decision-Making Process of Self-Adaptive Systems by Accounting for Tactic Volatility. CoRR abs/2004.11302 (2020) - [i2]Wentao Bao, Qi Yu, Yu Kong:
Object-Aware Centroid Voting for Monocular 3D Object Detection. CoRR abs/2007.09836 (2020) - [i1]Wentao Bao, Qi Yu, Yu Kong:
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning. CoRR abs/2008.00334 (2020)
2010 – 2019
- 2019
- [j43]Kishan KC, Rui Li, Feng Cui, Qi Yu, Anne R. Haake:
GNE: a deep learning framework for gene network inference by aggregating biological information. BMC Syst. Biol. 13-S(2): 38:1-38:14 (2019) - [j42]Hongbing Wang, Shunshun Peng, Qi Yu:
A parallel refined probabilistic approach for QoS-aware service composition. Future Gener. Comput. Syst. 98: 609-626 (2019) - [j41]Hongbing Wang, Huanhuan Fei, Qi Yu, Wei Zhao, Jia Yan, Tianjing Hong:
A motifs-based Maximum Entropy Markov Model for realtime reliability prediction in System of Systems. J. Syst. Softw. 151: 180-193 (2019) - [j40]Hongbing Wang, Yong Tao, Qi Yu, Tianjing Hong, Chen Xin, Qin Wu:
Personalized service selection using Conditional Preference Networks. Knowl. Based Syst. 164: 292-308 (2019) - [j39]Hongbing Wang, Mingzhu Gu, Qi Yu, Yong Tao, Jiajie Li, Huanhuan Fei, Jia Yan, Wei Zhao, Tianjing Hong:
Adaptive and large-scale service composition based on deep reinforcement learning. Knowl. Based Syst. 180: 75-90 (2019) - [j38]Eduardo Lima, Weishi Shi, Xumin Liu, Qi Yu:
Integrating Multi-level Tag Recommendation with External Knowledge Bases for Automatic Question Answering. ACM Trans. Internet Techn. 19(3): 34:1-34:22 (2019) - [j37]Hongbing Wang, Lei Wang, Qi Yu, Zibin Zheng:
Learning the Evolution Regularities for BigService-Oriented Online Reliability Prediction. IEEE Trans. Serv. Comput. 12(3): 398-411 (2019) - [c53]Moayad Alshangiti, Hitesh Sapkota, Pradeep K. Murukannaiah, Xumin Liu, Qi Yu:
Why is Developing Machine Learning Applications Challenging? A Study on Stack Overflow Posts. ESEM 2019: 1-11 - [c52]Weishi Shi, Qi Yu:
Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning. ICML 2019: 5769-5778 - [c51]Jeffrey Palmerino, Qi Yu, Travis Desell, Daniel E. Krutz:
Improving the Decision-Making Process of Self-Adaptive Systems by Accounting for Tactic Volatility. ASE 2019: 949-961 - [c50]Weishi Shi, Qi Yu:
Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning. NeurIPS 2019: 2282-2291 - [c49]Jai W. Kang, Qi Yu, Edward P. Holden, Xumin Liu:
Complementing Course Contents Between IT/CS: A Case Study on Database Courses. SIGITE 2019: 10-15 - [e5]Xiao Liu, Michael Mrissa, Liang Zhang, Djamal Benslimane, Aditya Ghose, Zhongjie Wang, Antonio Bucchiarone, Wei Zhang, Ying Zou, Qi Yu:
Service-Oriented Computing - ICSOC 2018 Workshops - ADMS, ASOCA, ISYyCC, CloTS, DDBS, and NLS4IoT, Hangzhou, China, November 12-15, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11434, Springer 2019, ISBN 978-3-030-17641-9 [contents] - 2018
- [j36]Xumin Liu, Moayad Alshangiti, Chen Ding, Qi Yu:
Log sequence clustering for workflow mining in multi-workflow systems. Data Knowl. Eng. 117: 1-17 (2018) - [j35]Ervine Zheng, Gustavo Yukio Kondo, Stephen J. Zilora, Qi Yu:
Tag-aware dynamic music recommendation. Expert Syst. Appl. 106: 244-251 (2018) - [j34]Hongbing Wang, Yong Tao, Qi Yu, Xin Lin, Tianjing Hong:
Incorporating both qualitative and quantitative preferences for service recommendation. J. Parallel Distributed Comput. 114: 46-69 (2018) - [j33]Hongbing Wang, Lei Wang, Qi Yu, Zibin Zheng, Zhengping Yang:
A proactive approach based on online reliability prediction for adaptation of service-oriented systems. J. Parallel Distributed Comput. 114: 70-84 (2018) - [j32]Hongbing Wang, Danrong Yang, Qi Yu, Yong Tao:
Integrating modified cuckoo algorithm and creditability evaluation for QoS-aware service composition. Knowl. Based Syst. 140: 64-81 (2018) - [j31]Hongbing Wang, Zhengping Yang, Qi Yu, Tianjing Hong, Xin Lin:
Online reliability time series prediction via convolutional neural network and long short term memory for service-oriented systems. Knowl. Based Syst. 159: 132-147 (2018) - [j30]Hongbing Wang, Chao Yu, Lei Wang, Qi Yu:
Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences. IEEE Trans. Serv. Comput. 11(4): 644-657 (2018) - [c48]Weishi Shi, Qi Yu:
An Efficient Many-Class Active Learning Framework for Knowledge-Rich Domains. ICDM 2018: 1230-1235 - [c47]Nse Obot, Laura OrMalley, Ifeoma Nwogu, Qi Yu, Weishi Shi, Xuan Guo:
From Novice to Expert Narratives of Dermatological Disease. PerCom Workshops 2018: 131-136 - [c46]Jai W. Kang, Qi Yu, Erik Golen, Edward P. Holden:
IT Curriculum: Coping with Technology Trends & Industry Demands. SIGITE 2018: 44-49 - [e4]Claus Pahl, Maja Vukovic, Jianwei Yin, Qi Yu:
Service-Oriented Computing - 16th International Conference, ICSOC 2018, Hangzhou, China, November 12-15, 2018, Proceedings. Lecture Notes in Computer Science 11236, Springer 2018, ISBN 978-3-030-03595-2 [contents] - 2017
- [j29]Athman Bouguettaya, Munindar P. Singh, Michael N. Huhns, Quan Z. Sheng, Hai Dong, Qi Yu, Azadeh Ghari Neiat, Sajib Mistry, Boualem Benatallah, Brahim Medjahed, Mourad Ouzzani, Fabio Casati, Xumin Liu, Hongbing Wang, Dimitrios Georgakopoulos, Liang Chen, Surya Nepal, Zaki Malik, Abdelkarim Erradi, Yan Wang, M. Brian Blake, Schahram Dustdar, Frank Leymann, Michael P. Papazoglou:
A service computing manifesto: the next 10 years. Commun. ACM 60(4): 64-72 (2017) - [j28]Hongbing Wang, Peisheng Ma, Qi Yu, Danrong Yang, Jiajie Li, Huanhuan Fei:
Combining quantitative constraints with qualitative preferences for effective non-functional properties-aware service composition. J. Parallel Distributed Comput. 100: 71-84 (2017) - [j27]Hongbing Wang, Xin Chen, Qin Wu, Qi Yu, Xingguo Hu, Zibin Zheng, Athman Bouguettaya:
Integrating Reinforcement Learning with Multi-Agent Techniques for Adaptive Service Composition. ACM Trans. Auton. Adapt. Syst. 12(2): 8:1-8:42 (2017) - [j26]Xumin Liu, Weishi Shi, Arpeet Kale, Chen Ding, Qi Yu:
Statistical Learning of Domain-Specific Quality-of-Service Features from User Reviews. ACM Trans. Internet Techn. 17(2): 22:1-22:24 (2017) - [j25]Hongbing Wang, Lei Wang, Qi Yu, Zibin Zheng, Athman Bouguettaya, Michael R. Lyu:
Online Reliability Prediction via Motifs-Based Dynamic Bayesian Networks for Service-Oriented Systems. IEEE Trans. Software Eng. 43(6): 556-579 (2017) - [c45]Hongbing Wang, Mingzhu Gu, Qi Yu, Huanhuan Fei, Jiajie Li, Yong Tao:
Large-Scale and Adaptive Service Composition Using Deep Reinforcement Learning. ICSOC 2017: 383-391 - [c44]Hongbing Wang, Zhengping Yang, Qi Yu:
Online Reliability Prediction via Long Short Term Memory for Service-Oriented Systems. ICWS 2017: 81-88 - [c43]Shunshun Peng, Hongbing Wang, Qi Yu:
Estimation of Distribution with Restricted Boltzmann Machine for Adaptive Service Composition. ICWS 2017: 114-121 - [c42]Weishi Shi, Xumin Liu, Qi Yu:
Correlation-Aware Multi-Label Active Learning for Web Service Tag Recommendation. ICWS 2017: 229-236 - [c41]Xuan Guo, Rui Li, Qi Yu, Anne R. Haake:
Modeling Physicians' Utterances to Explore Diagnostic Decision-making. IJCAI 2017: 3700-3706 - [c40]Jai W. Kang, Qi Yu, Erik Golen:
Teaching IoT (Internet of Things) Analytics. SIGITE 2017: 135-140 - [e3]Khalil Drira, Hongbing Wang, Qi Yu, Yan Wang, Yuhong Yan, François Charoy, Jan Mendling, Mohamed Mohamed, Zhongjie Wang, Sami Bhiri:
Service-Oriented Computing - ICSOC 2016 Workshops - ASOCA, ISyCC, BSCI, and Satellite Events, Banff, AB, Canada, October 10-13, 2016. Revised Selected Papers. Lecture Notes in Computer Science 10380, Springer 2017, ISBN 978-3-319-68135-1 [contents] - 2016
- [j24]Xuan Guo, Qi Yu, Rui Li, Cecilia Ovesdotter Alm, Cara Calvelli, Pengcheng Shi, Anne R. Haake:
Intelligent medical image grouping through interactive learning. Int. J. Data Sci. Anal. 2(3-4): 95-105 (2016) - [j23]Hongbing Wang, Xiaojun Wang, Xingzhi Zhang, Qi Yu, Xingguo Hu:
Effective service composition using multi-agent reinforcement learning. Knowl. Based Syst. 92: 151-168 (2016) - [j22]Michael Sheng, Athanasios V. Vasilakos, Qi Yu, Lina You:
Guest Editorial: Big Data Analytics and the Web. IEEE Trans. Big Data 2(3): 189 (2016) - [c39]Hongbing Wang, Xingzhi Zhang, Qi Yu:
Integrating POMDP and SARSA( \lambda λ ) for Service Composition with Incomplete Information. ICSOC 2016: 677-684 - [c38]