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ORCID25th ICONIP 2018: Siem Reap, Cambodia
- Long Cheng, Andrew Chi-Sing Leung, Seiichi Ozawa:
Neural Information Processing - 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13-16, 2018, Proceedings, Part III. Lecture Notes in Computer Science 11303, Springer 2018, ISBN 978-3-030-04181-6
Embedding Learning
- Subba Reddy Oota, Naresh Manwani, Raju S. Bapi
:
fMRI Semantic Category Decoding Using Linguistic Encoding of Word Embeddings. 3-15 - Weixin Zeng, Jiuyang Tang, Xiang Zhao, Bin Ge, Weidong Xiao:
Named Entity Disambiguation via Probabilistic Graphical Model with Embedding Features. 16-27 - Maoyuan Zhang, Qi Wang, Zhou Xu, Jianping Zhu, Shuyuan Sun, Yang Wen:
Category-Embodied Knowledge Embedding. 28-37 - Xiaohui Luo, Li Zhang, Fanzhang Li, Chengxiang Hu:
Unsupervised Ensemble Learning Based on Graph Embedding for Image Clustering. 38-47 - Shengyue Luo, Wei Fang:
Potential Probability of Negative Triples in Knowledge Graph Embedding. 48-58 - Zhenyu Yang, Wei Liu, Zongtian Liu:
Event Causality Identification by Modeling Events and Relation Embedding. 59-68 - Qi Yang, Ruixuan Li, Yuhua Li, Qilei Liu:
Topic-Bigram Enhanced Word Embedding Model. 69-81 - Hosang Yu, Gil-Jin Jang, Minho Lee:
Hybridized Character-Word Embedding for Korean Traditional Document Translation. 82-89 - Denis Sedov, Zhirong Yang:
Word Embedding Based on Low-Rank Doubly Stochastic Matrix Decomposition. 90-100 - Qianqi Fang, Ling Liu, Junliang Yu, Junhao Wen:
Meta-path Based Heterogeneous Graph Embedding for Music Recommendation. 101-113 - Md. Mostafizur Rahman, Atsuhiro Takasu:
Knowledge Graph Embedding via Entities' Type Mapping Matrix. 114-125 - Wenfeng Liu, Peiyu Liu, Jing Yi, Yuzhen Yang, Weitong Liu, Nana Li:
A Sentence Similarity Model Based on Word Embeddings and Dependency Syntax-Tree. 126-137
Transfer Learning
- Jyoti Maggu, Angshul Majumdar:
Semi-coupled Transform Learning. 141-150 - Chang Shu, Xi Chen, Chong Yu, Hua Han:
A Refined Spatial Transformer Network. 151-161 - Jyoti Maggu, Emilie Chouzenoux, Giovanni Chierchia, Angshul Majumdar:
Convolutional Transform Learning. 162-174 - Jie Hang, Keji Han, Yun Li:
Delving into Diversity in Substitute Ensembles and Transferability of Adversarial Examples. 175-187 - Ravi Shankar Devanapalli, V. Susheela Devi:
Transfer Learning Using Progressive Neural Networks and NMT for Classification Tasks in NLP. 188-197 - Zhilong Deng, Fan Liu, Jiangjiang Zhao, Qiang Wei, Shaoning Pang, Yue Leng:
Deep Transfer Learning via Minimum Enclosing Balls. 198-207 - Qian Zhang, Dianshuang Wu, Jie Lu, Guangquan Zhang:
Cross-domain Recommendation with Probabilistic Knowledge Transfer. 208-219 - Ke-Jia Chen, Kai Zhang, Xi-Lin Jiang, Yunyun Wang:
Transfer Learning with Active Queries for Relational Data Modeling Across Multiple Information Networks. 220-229 - Rakesh Kumar Sanodiya, Sriparna Saha, Jimson Mathew, Prateek Bangwal:
Semi-supervised Transfer Metric Learning with Relative Constraints. 230-241 - Hua Zuo, Guangquan Zhang, Jie Lu:
Fuzzy Domain Adaptation Using Unlabeled Target Data. 242-250
Reinforcement Learning
- Ye Huang, Chaochen Gu, Kaijie Wu, Xinping Guan:
Reinforcement Learning Policy with Proportional-Integral Control. 253-264 - Dongfang Zhao, Jiafeng Liu, Rui Wu, Dansong Cheng, Xianglong Tang:
Data-Efficient Reinforcement Learning Using Active Exploration Method. 265-276 - Song Chen, Xiaofang Zhang, Jin-Jin Wu, Di Liu:
Averaged-A3C for Asynchronous Deep Reinforcement Learning. 277-288 - Jianpeng Lin, Zhiping Peng, Delong Cui:
Deep Reinforcement Learning for Multi-resource Cloud Job Scheduling. 289-302 - Yifan Li, Yuchun Fang:
Accelerating Spatio-Temporal Deep Reinforcement Learning Model for Game Strategy. 303-312 - Jatin Goyal, Abhijith Madan, Akshay Narayan, Shrisha Rao:
ASD: A Framework for Generation of Task Hierarchies for Transfer in Reinforcement Learning. 313-325 - Yuanheng Zhu, Dongbin Zhao:
Driving Control with Deep and Reinforcement Learning in The Open Racing Car Simulator. 326-334 - Yingying Zhu, Hui Yang, Jianmin Jiang, Qiang Huang:
An Adaptive Box-Normalization Stock Index Trading Strategy Based on Reinforcement Learning. 335-346 - Shanchuan Wan, Tomoyuki Kaneko:
Heterogeneous Multi-task Learning of Evaluation Functions for Chess and Shogi. 347-358 - Tulika Saha, Dhawal Gupta, Sriparna Saha, Pushpak Bhattacharyya:
Reinforcement Learning Based Dialogue Management Strategy. 359-372
Other Learning Approaches
- Miao Cheng, Zunren Liu, Hongwei Zou, Ah Chung Tsoi:
A Family of Maximum Margin Criterion for Adaptive Learning. 375-387 - Hideaki Ishibashi, Kazushi Higa, Tetsuo Furukawa:
Multi-task Manifold Learning Using Hierarchical Modeling for Insufficient Samples. 388-398 - Ying Li, Yabo Zhang, Yaxin Peng:
Enhanced Metric Learning via Dempster-Shafer Evidence Theory. 399-410 - Guangzhen Liu, Jun Hu, An Zhao, Mingyu Ding, Yuqi Huo, Zhiwu Lu:
InsightGAN: Semi-Supervised Feature Learning with Generative Adversarial Network for Drug Abuse Detection. 411-422 - Ali Braytee, Ali Anaissi, Paul J. Kennedy:
Sparse Feature Learning Using Ensemble Model for Highly-Correlated High-Dimensional Data. 423-434 - Jing Zhao, Shaoning Pang, Iman Tabatabaei Ardekani, Yuji Sekiya, Daisuke Miyamoto:
Task and Instance Quadratic Ordering for Active Online Multitask Learning. 435-447 - Huifang Ma, Fang Liu, Qin Xia, Li Yu:
Learning from Titles to Recommend Keywords for Academic Papers. 448-459 - Yuqi Huo, Mingyu Ding, An Zhao, Jun Hu, Ji-Rong Wen, Zhiwu Lu:
Zero-Shot Learning with Superclasses. 460-472 - Jingjing Fei, Jing Zhao, Shiliang Sun, Yan Liu:
Active Learning Methods with Deep Gaussian Processes. 473-483 - Radu Tudor Ionescu, Andrei Madalin Butnaru:
Transductive Learning with String Kernels for Cross-Domain Text Classification. 484-496 - Fangzhou Xiong, Zhiyong Liu, Xu Yang:
Overcoming Catastrophic Forgetting with Self-adaptive Identifiers. 497-505 - Xiaolong Zou, Zilong Ji, Xiao Liu, Tiejun Huang, Yuanyuan Mi, Dahui Wang, Si Wu:
Learning, Storing, and Disentangling Correlated Patterns in Neural Networks. 506-514 - Jun Yuan, Neng Gao, Lei Wang, Zeyi Liu:
MultNet: An Efficient Network Representation Learning for Large-Scale Social Relation Extraction. 515-524 - Shotaro Akaho, Hideitsu Hino, Neneka Nara, Noboru Murata:
Geometrical Formulation of the Nonnegative Matrix Factorization. 525-534 - Keishi Sando, Shotaro Akaho, Noboru Murata, Hideitsu Hino:
Information Geometric Perspective of Modal Linear Regression. 535-545 - Zehua Zeng, Cong Xue, Neng Gao, Lei Wang, Zeyi Liu:
Learning from Audience Intelligence: Dynamic Labeled LDA Model for Time-Sync Commented Video Tagging. 546-559 - Zhihui Hu, Yubin Jiang, Xinghong Ling, Quan Liu:
Accurate Q-Learning. 560-570 - Jingzhuo Yang, Yu Wang, Qinghua Hu:
Monotonicity Extraction for Monotonic Bayesian Networks Parameter Learning. 571-581 - Yingyao Wang, Jianhua Dai, Hong Shi:
Dynamic Maintenance of Decision Rules for Decision Attribute Values' Changing. 582-592 - Yansheng Zhai, Jianhua Dai, Hong Shi:
Label Distribution Learning Based on Ensemble Neural Networks. 593-602 - Zilong Ji, Xiaolong Zou, Xiao Liu, Tiejun Huang, Yuanyuan Mi, Si Wu:
Neural Information Processing in Hierarchical Prototypical Networks. 603-611 - Ali Anaissi, Young Lee, Mohamad Naji:
Regularized Tensor Learning with Adaptive One-Class Support Vector Machines. 612-624 - Yezi Liu:
Semi-supervised Multi-label Dimensionality Reduction via Low Rank Representation. 625-637 - Hideaki Ishibashi:
Visualization Method of Viewpoints Latent in a Dataset. 638-647 - Ludovic Platon, Farida Zehraoui, Fariza Tahi:
Localized Multiple Sources Self-Organizing Map. 648-659 - Simon Moura, Amir Asarbaev, Massih-Reza Amini, Yury Maximov:
Heterogeneous Dyadic Multi-task Learning with Implicit Feedback. 660-672 - Shota Utsumi, Keisuke Kameyama:
Parallel Cooperative Ensemble Learning by Adaptive Data Weighting and Error-Correcting Output Codes. 673-683
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