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Publication History 2017
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Conference Paper
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Journal Article
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Conference Paper
B.-J. Hou, L. Zhang, and Z.-H. Zhou.
Learning with feature evolvable streams
.
In: Advances in Neural Information Processing Systems 30 (NIPS'17)
, Long Beach, CA, 2017.
C. Qian, J.-C. Shi, Y. Yu, K. Tang, and Z.-H. Zhou.
Subset selection under noise
.
In: Advances in Neural Information Processing Systems 30 (NIPS'17)
, Long Beach, CA, 2017.
L. Zhang, T. Yang, J. Yi, R. Jin, and Z.-H. Zhou.
Improved dynamic regret for non-degeneracy functions
.
In: Advances in Neural Information Processing Systems 30 (NIPS'17)
, Long Beach, CA, 2017.
Jing-Cheng Shi, Chao Qian, and Yang Yu.
Evolutionary Multi-objective Optimization Made Faster by Sequential Decomposition
.
In: Proceedings of the 2017 IEEE Congress on Evolutionary Computation (CEC'17)
, San Sebastian, Spain, 2017.
Y. Zhu, K. M. Ting, and Z.-H. Zhou.
New class adaptation via instance generation in one-pass class incremental learning
.
In: Proceedings of the 17th IEEE International Conference on Data Mining (ICDM'17)
, New Orleans, LA, 2017.
D. Ding, M. Zhang, S.-Y. Li, J. Tang, X. Chen, and Z.-H. Zhou.
BayDNN: Friend recommendation with Bayesian personalized ranking deep neural network
.
In: Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM'17)
, Singapore, 2017.
W.-Z. Dai, S. H. Muggleton, J. Wen, A. Tamaddoni-Nezhad, and Z.-H. Zhou.
Logic vision: One-shot meta-intepretive learning from real images
.
In: Proceedings of the 25th International Conference on Inductive Logic Programming (ILP'17)
, Orleans, France, 2017.
L. Zhang, T. Yang, R. Jin.
Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n^2 )-type of Risk Bounds
.
In: Proceedings of the 2017 edition of the Conference On Learning Theory (COLT'17)
, Amsterdam, Netherlands.
T. Yang, Q. Lin, L. Zhang.
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
.
In: Proceedings of the 34th International Conference on Machine Learning (ICML'17)
, Sydney, Australia, 2017.
X.-Z. Wu and Z.-H. Zhou.
A unified view of multi-label performance measures
.
In: Proceedings of the 34th International Conference on Machine Learning (ICML'17)
, Sydney, Australia, 2017.
T. Zhang and Z.-H. Zhou.
Multi-class optimal distribution machine
.
In: Proceedings of the 34th International Conference on Machine Learning (ICML'17)
, Sydney, Australia, 2017.
H.-Y. Zhou and J.-X. Wu.
Content-Based Image Recovery
In: Proc. Pacific-Rim Conference on Multimedia (PCM 2017)
, Harbin, China, October 2017.
C.-L. Zhang, J.-H. Luo, Xiu-Shen Wei, J.-X. Wu.
In Defense of Fully Connected Layers in Visual Representation Transfer?
In: Proc. Pacific-Rim Conference on Multimedia (PCM 2017)
, Harbin, China, October 2017.
H.-Y. Zhou, Bin-Bin Gao, J.-X. Wu.
Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors
In: Proc. International Conference on Computer Vision (ICCV 2017)
, Venice, Italy, October 2017.
J.-H. Luo, J.-X. Wu, Weiyao Lin.
ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression
In: Proc. International Conference on Computer Vision (ICCV 2017)
, Venice, Italy, October 2017.
H.-Y. Zhou, Bin-Bin Gao, J.-X. Wu.
Sunrise or Sunset: Selective Comparison Learning for Subtle Attribute Recognition
.
In: Proc. The 28th British Machine Vision Conference (BMVC 2017)
, London, UK, September 2017.
Y. Yang, D.-C. Zhan, Y. Fan, Y. Jiang.
Instance Specific Discriminative Modal Pursuit: A Serialized Approach
.
In: Proceedings of the 9th Asian Conference on Machine Learning (ACML'17)
, Seoul, Korea, 2017.
H.-J. Ye, D.-C. Zhan, X.-M. Si, Y. Jiang.
Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
Y. Yang, D.-C. Zhan, X.-Y. Guo, Y. Jiang.
Modal Consistency based Pre-trained Multi-Model Reuse
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
Y. Zhang, Y. Jiang.
Multimodal Linear Discriminant Analysis via Structural Sparsity
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
X. Huo, M. Li.
Enhancing the Unified Features to Locate Buggy Files by Exploiting the Sequential Nature of Source Code
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
H.-H. Wei, M. Li.
Supervised Deep Features for Software Functional Clone Detection Exploiting Lexical and Syntactical Information in Source Code
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
Y. Yu, W.-Y. Qu, N. Li, Z. Guo.
Open Category Classification by Adversarial Sample Generation
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
W.-J. Zhou, Y. Yu, M.-L. Zhang.
Binary Linear Compression for Multi-label Classification
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
J.-W. Yang, Y. Yu, X.-P. Zhang.
Life-Stage Modeling by Customer-Manifold Embedding
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
C. Qian, J.-C. Shi, Y. Yu, K. Tang.
On Subset Selection with General Cost Constraints
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
J. Zhang, Y. Sun, S.-J. Huang, N. Cam-Tu, X. Wang, X.-Y. Dai, J. Chen, Y. Yu.
AGRA: An Analysis-Generation-Ranking Framework for Automatic Abbreviation from Paper Titles
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
X. Yan, L. Zhang, W.-J. Li.
Semi-Supervised Deep Hashing with a Bipartite Graph
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
Y. Xiao, Z. Li, T. Yang, L. Zhang.
SVD-free Convex-Concave Approaches for Nuclear Norm Regularization
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
Z.-H. Zhou and J. Feng.
Deep forest: Towards an alternative to deep neural networks
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
M. Xu and Z.-H. Zhou. Incomplete label distribution learning.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
Y.-L. Zhang and Z.-H. Zhou.
Multi-instance learning with key instance shift
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
B.-J. Hou, L. Zhang, and Z.-H. Zhou.
Storage fit learning with unlabeled data
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
S.-J. Huang, J.-L. Chen, X. Mu, and Z.-H. Zhou.
Cost-effective active learning from diverse labelers
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
W. Wang, X.-Y. Guo, S.-Y. Li, Y. Jiang, and Z.-H. Zhou.
Obtaining high-quality label by distinguishing between easy and hard items in crowdsourcing
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
C. Qian, J.-C. Shi, Y. Yu, K. Tang, and Z.-H. Zhou.
Optimizing ratio of monotone set functions
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
X.-S. Wei, C.-L. Zhang, Y. Li, C.-W. Xie, J. Wu, C. Shen, and Z.-H. Zhou.
Deep descriptor transforming for image co-localization
.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)
, Melbourne, Australia, 2017.
A.-S. Ni and M. Li.
Cost-effective build outcome prediction using cascaded classifiers
.
In: Proceedings of the 14th International Conference on Mining Software Repositories (MSR'17)
, Buenous Aires, Argentina, 2017.
Q.-Y. Jiang and W.-J. Li.
Deep Cross-Modal Hashing
.
In: Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR'17)
, Honolulu, Hawaii, 2017.
P. Zhao, Y. Jiang, and Z.-H. Zhou.
Multi-view matrix completion for clustering with side information
.
In: Proceedings of the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'17)
, LNAI, Jeju, Korea, 2017.
H. Qian and Y. Yu.
Solving high-dimensional multi-objective optimization problems with low effective dimensions
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17)
, San Francisco, CA, 2017.
Y.-Q. Hu, H. Qian, and Y. Yu.
Sequential classification-based optimization for direct policy search
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17)
, San Francisco, CA, 2017.
J. Zhang, and L. Zhang.
Efficient Stochastic Optimization for Low-Rank Distance Metric Learning
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
Y. Xu, H. Yang, L. Zhang, and T. Yang.
Efficient Non-oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
Z. Li, T. Yang, L. Zhang, and R. Jin.
A Two-stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
W.-Z. Dai and Z.-H. Zhou.
Combining logic abduction and statistical induction: Discovering written primitives with human knowledge
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
J. Feng and Z.-H. Zhou.
DeepMIML network
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
Y.-F. Li, H.-W. Zha, and Z.-H. Zhou.
Construct safe prediction from multiple regressors
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
Y. Zhu, K. M. Ting, and Z.-H. Zhou.
Discover multiple novel labels in multi-instance multi-label learning
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
Y. Yang, D.-C. Zhan, Y. Fan, Y. Jiang, and Z.-H. Zhou.
Deep learning for fixed model reuse
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
X. Mu, F. Zhu, J. Du, E.-P. Lim, and Z.-H. Zhou.
Streaming classification with emerging new class by class matrix sketching
.
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI'17)
, San Francisco, CA, 2017.
Top
Journal Article and Book
Z.-H. Zhou.
A brief introduction to weakly supervised learning
.
National Science Review
, in press.
C. Qian, J.-C. Shi, K. Tang, and Z.-H. Zhou.
Constrained monotone k-submodular function maximization using multi-objective evolutionary algorithms with theoretical guarantee
.
IEEE Transactions on Evolutionary Computation
, in press.
C. Qian, Y. Yu, K. Tang, Y. Jin, X. Yao, and Z.-H. Zhou.
On the effectiveness of sampling for evolutionary optimization in noisy environments
.
Evolutionary Computation
, in press.
C. Qian, Y. Yu, and Z.-H. Zhou.
Analyzing evolutionary optimization in noisy environments
.
Evolutionary Computation
, in press.
X. Mu, K. M. Ting, and Z.-H. Zhou.
Classification under streaming emerging new classes: A solution using completely-random trees
.
IEEE Transactions on Knowledge and Data Engineering
, 2017, 29(8): 1605-1618.
B.-B. Gao, C. Xing, C.-W. Xie, J. Wu, and X. Geng.
Deep Label Distribution Learning with Label Ambiguity
.
IEEE Transactions on Image Processing
, 26(6), 2017: 2825-2838.
X.-S. Wei, J.-H. Luo, J.n Wu, and Z.-H. Zhou.
Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval
.
IEEE Transactions on Image Processing
, 26(6), 2017: 2868-2881.
W. Lin, Y. Shen, J. Yan, M.g Xu, J. Wu, J. Wang, and K. Lu.
Learning Correspondence Structures for Person Re-identification
.
IEEE Transactions on Image Processing
, 26(5), 2017: 2438-2453.
G. Lin, F. Liu, C. Shen, J. Wu, H.-T. Shen.
Structured Learning of Binary Codes with Column Generation for Optimizing Ranking Measures
.
International Journal of Computer Vision
, 123(2), 2017: 287-308.
J.-H. Luo, W. Zhou, J. Wu.
Image Categorization with Resource Constraints: Introduction, Challenges and Advances
.
Frontiers of Computer Science
, 11(1), 2017: pp. 13-26.
C. Qian, Y. Yu, K. Tang, Y. Jin, X. Yao, and Z.-H. Zhou.
On the Effectiveness of Sampling for Evolutionary Optimization in Noisy Environments
.
Evolutionary Computation
, 2017, in press.
D.-C. Zhan, J. Tang, and Z.-H. Zhou.
Online Game Props Recommendation with Real Assessments
.
Complex & Intelligent Systems
. 2017, DOI: 10.1007/s40747-016-0031-7
S. Yang, and L. Zhang.
Non-redundant Multiple Clustering by Nonnegative Matrix Factorization
.
Machine Learning
, 106(5): 695 - 712, 2017.
X.-S. Wei, J. Wu, and Z.-H. Zhou.
Scalable algorithms for multi-instance learning
.
IEEE Transactions on Neural Networks and Learning Systems
, 2017, 28(4): 975-987.
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