Jia Wu

Dr

  • 1476 Citations
  • 22 h-Index
20082021

Research output per year

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Research Outputs

  • 1476 Citations
  • 22 h-Index
  • 66 Conference proceeding contribution
  • 60 Article
  • 2 Review article
  • 1 Editorial
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Conference proceeding contribution
2020

ReInCre: enhancing collaborative filtering recommendations by incorporating user rating credibility

Kermany, N. R., Zhao, W., Yang, J. & Wu, J., 2020, Web Information Systems Engineering: WISE 2019 Workshop, Demo, and Tutorial, Revised Selected Papers. U, L. H., Yang, J., Cai, Y., Karlapalem, K., Liu, A. & Huang, X. (eds.). Singapore: Springer, Springer Nature, p. 64-72 9 p. (Communications in Computer and Information Science; vol. 1155 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2019

Automatic knowledge graph construction: a report on the 2019 ICDM/ICBK Contest

Wu, X., Wu, J., Fu, X., Li, J., Zhou, P. & Jiang, X., 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). Los Alamitos, CA: Institute of Electrical and Electronics Engineers (IEEE), p. 1540-1545 6 p. (Proceedings - IEEE International Conference on Data Mining, ICDM).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

CoTrRank: Trust evaluation of users and tweets

Li, P., Zhao, W., Yang, J. & Wu, J., Aug 2019, Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019. Kraus, S. (ed.). International Joint Conferences on Artificial Intelligence, Vol. 2019-August. p. 6542-6544 3 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Open Access

Deep structure learning for rumor detection on Twitter

Huang, Q., Zhou, C., Wu, J., Wang, M. & Wang, B., 2019, 2019 International Joint Conference on Neural Networks, IJCNN 2019. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 8 p. (Proceedings of the International Joint Conference on Neural Networks; vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

DeepTrust: a deep user model of homophily effect for trust prediction

Wang, Q., Zhao, W., Yang, J., Wu, J., Hu, W. & Xing, Q., 1 Nov 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). Institute of Electrical and Electronics Engineers (IEEE), p. 618-627 10 p. 8970846

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Evolutionary community detection in dynamic social networks

Liu, F., Wu, J., Zhou, C. & Yang, J., 1 Jul 2019, 2019 International Joint Conference on Neural Networks, IJCNN 2019. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), Vol. 2019-July. p. 1-7 7 p. N-20102

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

GroExpert: a novel group-aware experts identification approach in crowdsourcing

Xing, Q., Zhao, W., Yang, J., Wu, J., Wang, Q. & Wang, M., 2019, Proceedings of 20th International Conference of Web Information Systems Engineering - WISE 2019. Cheng, R., Mamoulis, N., Sun, Y. & Huang, X. (eds.). Cham, Switzerland: Springer, p. 3-17 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11881 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Guiding cross-lingual entity alignment via adversarial knowledge embedding

Lin, X., Yang, H., Wu, J., Zhou, C. & Wang, B., 2019, Proceedings - 19th IEEE International Conference on Data Mining, ICDM 2019. Wang, J., Shim, K. & Wu, X. (eds.). Los Alamitos, CA: Institute of Electrical and Electronics Engineers (IEEE), p. 429-438 10 p. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2019-November).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Link prediction with signed latent factors in signed social networks

Xu, P., Hu, W., Wu, J. & Du, B., 2019, KDD 2019 - Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY: Association for Computing Machinery (ACM), p. 1046-1054 9 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Smooth Deep Network Embedding

Zheng, M., Zhou, C., Wu, J. & Guo, L., 2019, 2019 International Joint Conference on Neural Networks, IJCNN 2019. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 8 p. (Proceedings of the International Joint Conference on Neural Networks; vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Social trust network embedding

Xu, P., Hu, W., Wu, J., Liu, W., Du, B. & Yang, J., 2019, Proceedings, 19th IEEE International Conference on Data Mining. Wang, J., Shim, K. & Wu, X. (eds.). Los Alamitos, CA: Institute of Electrical and Electronics Engineers (IEEE), p. 678-687 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2018

Active discriminative network representation learning

Gao, L., Yang, H., Zhou, C., Wu, J., Pan, S. & Hu, Y., 2018, Proceedings of the 27th International Joint Conference on Artificial Intelligence. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 2142-2148 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

4 Citations (Scopus)

A deep framework for Cross-Domain and Cross-System Recommendations

Zhu, F., Wang, Y., Chen, C., Liu, G., Orgun, M. & Wu, J., 2018, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18). Lang, J. (ed.). Freiburg: International Joint Conferences on Artificial Intelligence, p. 3711-3717 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Open Access
10 Citations (Scopus)

A deep learning health data analysis approach: automatic 3D prostate MR segmentation with densely-connected volumetric ConvNets

Zhu, Q., Du, B., Wu, J. & Yan, P., 1 Jul 2018, 2018 International Joint Conference on Neural Networks (IJCNN). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 1-6 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

4 Citations (Scopus)

A novel deep learning approach: stacked evolutionary auto-encoder

Cai, Y., Cai, Z., Zeng, M., Liu, X., Wu, J. & Wang, G., 1 Jul 2018, 2018 International Joint Conference on Neural Networks (IJCNN). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 1-8 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Brain EEG time series selection: a novel graph-based approach for classification

Dai, C., Wu, J., Pi, D. & Cui, L., 1 Jan 2018, Proceedings of the 2018 SIAM International Conference on Data Mining. Ester, M. & Pedreschi, D. (eds.). Philadelphia: Society for Industrial and Applied Mathematics Publications, p. 558-566 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

DAliM: Machine learning based intelligent lucky money determination for large-scale e-commerce businesses

Fu, M., Wong, C. M., Zhu, H., Huang, Y., Li, Y., Zheng, X., Wu, J., Yang, J. & Vong, C. M., 1 Jan 2018, Service-Oriented Computing: 16th International Conference, ICSOC 2018, Proceedings. Yu, Q., Pahl, C., Vukovic, M. & Yin, J. (eds.). Switzerland: Springer-VDI-Verlag GmbH & Co. KG, p. 740-755 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11236 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)

Deep structure learning for fraud detection

Wang, H., Zhou, C., Wu, J., Dang, W., Zhu, X. & Wang, J., 27 Dec 2018, 2018 IEEE International Conference on Data Mining, ICDM 2018. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), Vol. 2018-November. p. 567-576 10 p. 8594881

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

FraudNE: a joint embedding approach for fraud detection

Zheng, M., Zhou, C., Wu, J., Pan, S., Shi, J. & Guo, L., 10 Oct 2018, 2018 International Joint Conference on Neural Networks, IJCNN 2018: Proceedings. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 1-8 8 p. 8489585

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)

Individual interest and trust driving collective intelligence awareness for social recommendation

Cui, L., Wang, C., Wu, J., Yang, J. & Sheng, M., 10 Oct 2018, 2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings. Institute of Electrical and Electronics Engineers (IEEE), Vol. 2018-July. 6 p. 8489633

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Nonlocal patch based t-SVD for image inpainting: algorithm and error analysis

Song, L., Du, B., Zhang, L., Zhang, L., Wu, J. & Li, X., 1 Jan 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. Menlo Park, California: Association for the Advancement of Artificial Intelligence, p. 2419-2426 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Probabilistic Graph Embedding for unsupervised domain adaptation

Xiao, P., Du, B., Yun, S., Lit, X., Zhang, Y. & Wu, J., 26 Nov 2018, 2018 24th International Conference on Pattern Recognition, ICPR 2018. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), Vol. 2018-August. p. 1283-1288 6 p. 8546005

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Recommendation with multi-source heterogeneous information

Gao, L., Yang, H., Wu, J., Zhou, C., Lu, W. & Hu, Y., 2018, Proceedings of the 27th International Joint Conference on Artificial Intelligence. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 3378-3384 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

6 Citations (Scopus)

Self-representative manifold concept factorization with adaptive neighbors for clustering

Ma, S., Zhang, L., Hu, W., Zhang, Y., Wu, J. & Li, X., 2018, Proceedings of the 27th International Joint Conference on Artificial Intelligence. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 2539-2545 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

3 Citations (Scopus)

Social recommendation with an essential preference space

Liu, C. Y., Zhou, C., Wu, J., Hu, Y. & Guo, L., 1 Jan 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. Association for the Advancement of Artificial Intelligence, p. 346-353 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

16 Citations (Scopus)

TLR: transfer latent representation for unsupervised domain adaptation

Xiao, P., Du, B., Wu, J., Zhang, L., Hu, R. & Li, X., 8 Oct 2018, 2018 IEEE International Conference on Multimedia and Expo, ICME 2018. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), Vol. 2018-July. p. 1-6 6 p. 8486513

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)

VCF: velocity correlation filter, towards space-borne satellite video tracking

Shao, J., Du, B., Wu, C., Wu, J., Hu, R. & Li, X., 8 Oct 2018, 2018 IEEE International Conference on Multimedia and Expo, ICME 2018. Institute of Electrical and Electronics Engineers (IEEE), Vol. 2018-July. p. 1-6 6 p. 8486451

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

3 Citations (Scopus)
2017

A brain network inspired algorithm: Pre-trained Extreme Learning Machine

Zhang, Y., Wu, J., Cai, Z. & Jiang, S., 2017, Neural information processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14–18, 2017, Proceedings, Part V. Liu, D., Xie, S., Li, Y., Zhao, D. & El-Alfy, E-S. M. (eds.). Cham, Switzerland: Springer, Springer Nature, p. 14-23 10 p. (Lecture Notes in Computer Science; vol. 10638).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

3 Citations (Scopus)

Collaborative dynamic sparse topic regression with user profile evolution for item recommendation

Gao, L., Wu, J., Zhou, C. & Hu, Y., 2017, AAAI 2017: Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. Palo Alto, CA: Association for the Advancement of Artificial Intelligence, p. 1316-1322 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

21 Citations (Scopus)

CPMF: A collective pairwise matrix factorization model for upcoming event recommendation

Liu, C. Y., Zhou, C., Wu, J., Xie, H., Hu, Y. & Guo, L., 30 Jun 2017, IJCNN 2017: Proceedings of the 2017 International Joint Conference on Neural Networks. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 1532-1539 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

9 Citations (Scopus)

Dynamic island model based on spectral clustering in genetic algorithm

Meng, Q., Wu, J., Ellis, J. & Kennedy, P. J., 30 Jun 2017, IJCNN 2017: Proceedings of the 2017 International Joint Conference on Neural Networks. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 1724-1731 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)
2016

A recursive method for big network influence estimation

Lu, W. X., Zhou, C., Wu, J., Liu, C-Y., Gao, L. & Hu, Y., 31 Oct 2016, IJCNN 2016: Proceedings of the 2016 International Joint Conference on Neural Networks. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 4709-4714 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Bernoulli random forests: Closing the gap between theoretical consistency and empirical soundness

Yisen, W., Qingtao, T., Xia, S-T., Wu, J. & Zhu, X., 2016, IJCAI 2016: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Brewka, G. (ed.). Palo Alto, CA: Association for the Advancement of Artificial Intelligence, p. 2167-2173 7 p. (IJCAI International Joint Conference on Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

7 Citations (Scopus)

Collaborative social group influence for event recommendation

Gao, L., Wu, J., Qiao, Z., Zhou, C., Yang, H. & Hu, Y., 24 Oct 2016, CIKM 2016: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. New York, NY: Association for Computing Machinery, p. 1941-1944 4 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

22 Citations (Scopus)

Direct discriminative bag mapping for multi-instance learning

Wu, J., Pan, S., Zhang, P. & Zhu, X., 2016, AAAI 2016: Proceedings of the 30th AAAI Conference on Artificial Intelligence. Palo Alto, CA: Association for the Advancement of Artificial Intelligence, p. 4274-4275 2 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Evolutionary lazy learning for Naive Bayes classification

Bai, Y., Wang, H., Wu, J., Zhang, Y., Jiang, J. & Long, G., 31 Oct 2016, IJCNN 2016: Proceedings of the 2016 International Joint Conference on Neural Networks. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 3124-3129 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Global and local influence-based social recommendation

Zhang, Q., Wu, J., Yang, H., Lu, W., Long, G. & Zhang, C., 24 Oct 2016, CIKM 2016: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. New York, NY: Association for Computing Machinery, p. 1917-1920 4 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

9 Citations (Scopus)

Inferring latent network from cascade data for dynamic social recommendation

Zhang, Q., Wu, J., Zhang, P., Long, G., Tsang, I. W. & Zhang, C., 2016, ICDM 2016: Proceedings of the 16th IEEE International Conference on Data Mining. Bonchi, F., Domingo-Ferrer, J., Baeza-Yates, R., Zhou, Z-H. & Wu, X. (eds.). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 669-678 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

5 Citations (Scopus)

Joint structure feature exploration and regularization for multi-task graph classification

Pan, S., Wu, J., Zhuy, X., Zhang, C. & Yuz, P. S., 22 Jun 2016, ICDE 2016: Proceedings of the 2016 IEEE 32nd International Conference on Data Engineering. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 1474-1475 2 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

3 Citations (Scopus)

Mining subcascade features for cascade outbreak prediction in big networks

Wang, H., Wu, J., Zhou, C., Ji, Z. & Wu, J., 31 Oct 2016, IJCNN 2016: Proceedings of the 2016 International Joint Conference on Neural Networks. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 3942-3949 8 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

5 Citations (Scopus)

Multi-instance graphical transfer clustering for traffic data learning

Xue, S., Lu, J., Wu, J., Zhang, G. & Xiong, L., 31 Oct 2016, IJCNN 2016: Proceedings of the 2016 International Joint Conference on Neural Networks. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 4390-4395 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Multiple-instance learning with evolutionary instance selection

Zhang, Y., Wu, J., Zhou, C., Zhang, P. & Cai, Z., 2016, Database systems for advanced applications: 21st International Conference, DASFAA 2016 Dallas, TX, USA, April 16–19, 2016. Proceedings, Part I. Navathe, S. B., Wu, W., Shekhar, S., Du, X., Wang, X. S. & Xiong, H. (eds.). Springer, Springer Nature, p. 229-241 13 p. (Lecture Notes in Computer Science; vol. 9642).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)

On the minimum differentially resolving set problem for diffusion source inference in networks

Zhou, C., Lu, W-X., Zhang, P., Wu, J., Hu, Y. & Guo, L., 2016, AAAI 2016: Proceedings of the 30th AAAI Conference on Artificial Intelligence. Palo Alto, CA: Association for the Advancement of Artificial Intelligence, p. 79-85 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

8 Citations (Scopus)

Semi-data-driven network coarsening

Gao, L., Wu, J., Yang, H., Qiao, Z., Zhou, C. & Hu, Y., 2016, IJCAI 2016: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Brewka, G. (ed.). Palo Alto, CA: Association for the Advancement of Artificial Intelligence, p. 1483-1489 7 p. (IJCAI International Joint Conference on Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)

Training deep neural networks on imbalanced data sets

Wang, S., Liu, W., Wu, J., Cao, L., Meng, Q. & Kennedy, P. J., 31 Oct 2016, IJCNN 2016: Proceedings of the 2016 International Joint Conference on Neural Networks. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 4368-4374 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

76 Citations (Scopus)

Tri-party deep network representation

Pan, S., Wu, J., Zhu, X., Zhang, C. & Wang, Y., 2016, IJCAI 2016: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Brewka, G. (ed.). Palo Alto, CA: Association for the Advancement of Artificial Intelligence, p. 1895-1901 7 p. (IJCAI International Joint Conference on Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

112 Citations (Scopus)

Unsupervised feature learning from time series

Qin, Z., Wu, J., Hong, Y., Tian, Y. & Chengqi, Z., 2016, IJCAI 2016: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Brewka, G. (ed.). Palo Alto, CA: Association for the Advancement of Artificial Intelligence, p. 2322-2328 7 p. (IJCAI International Joint Conference on Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

16 Citations (Scopus)
2015

A memetic algorithm based extreme learning machine for classification

Zhang, Y., Cai, Z., Wu, J., Wang, X. & Liu, X., 28 Sep 2015, 2015 International Joint Conference on Neural Networks, IJCNN 2015. Institute of Electrical and Electronics Engineers (IEEE), Vol. 2015-September. 8 p. 7280383

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

5 Citations (Scopus)

Mining top-k minimal redundancy frequent patterns over uncertain databases

Wang, H., Zhang, P., Wu, J. & Pan, S., 1 Jan 2015, Neural Information Processing: 22nd International Conference, ICONIP 2015, Proceedings, Part IV. Arik, S., Huang, T., Lai, W. K. & Liu, Q. (eds.). Cham: Springer-VDI-Verlag GmbH & Co. KG, p. 111-119 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9492).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Multi-graph-view learning for complicated object classification

Wu, J., Pan, S., Zhu, X., Cai, Z. & Zhang, C., 1 Jan 2015, IJCAI 2015 - Proceedings of the 24th International Joint Conference on Artificial Intelligence. Yang, Q. & Wooldridge, M. (eds.). International Joint Conferences on Artificial Intelligence, Vol. 2015-January. p. 3953-3959 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

6 Citations (Scopus)