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Missing Value Imputation Using a Semi-supervised Rank Aggregation Approach [chapter]

Edson T. Matsubara, Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria C. Monard
2008 Lecture Notes in Computer Science  
This paper presents Corai, an imputation algorithm which is an adaption of Co-training, a multi-view semi-supervised learning algorithm.  ...  A closely related research topic that has emerged as exciting research in ML over the last years is Semi-Supervised Learning (SSL) [2] .  ...  To deal with this problem, we proposed the use of ranking aggregation to select the best examples.  ... 
doi:10.1007/978-3-540-88190-2_27 fatcat:rdxq3i7htjfcrcaphwib6y7wre

Introducing LETOR 4.0 Datasets [article]

Tao Qin, Tie-Yan Liu
2013 arXiv   pre-print
LETOR is a package of benchmark data sets for research on LEarning TO Rank, which contains standard features, relevance judgments, data partitioning, evaluation tools, and several baselines.  ...  Datasets Setting Datasets Supervised ranking MQ2007 MQ2008 Semi-supervised ranking MQ2007-semi MQ2008-semi Rank aggregation MQ2007-agg MQ2008-agg Listwise ranking MQ2007-list MQ2008  ...  Here are several Semi-supervised ranking setting, a query is associated with a set of input ranked lists.  ... 
arXiv:1306.2597v1 fatcat:ceaqiybkxfgdlps7gmumqntali

Guest Editorial: Ad Hoc Web Multimedia Analysis with Limited Supervision

Yahong Han, Yi Yang, Jingdong Wang
2015 Multimedia tools and applications  
Comprehensive evaluation results are obtained that semi-supervised learning and multi-feature fusion are effective in video action recognition.  ...  As unlabeled multimedia data always accompany multimodal examples on the social website, the "Markov Random Field Based Fusion for Supervised and Semi-supervised Multi-modal Image Classification" (10.1007  ... 
doi:10.1007/s11042-014-2419-y fatcat:hqct5eabprg75pocgful4sqn5e

A Supervised Aggregation Framework for Multi-Document Summarization

Yulong Pei, Wenpeng Yin, Qifeng Fan, Lian'en Huang
2012 International Conference on Computational Linguistics  
In this paper, a novel supervised aggregation approach for summarization is proposed which combines different summarization methods including Lex-PageRank, LexHITS, manifold-ranking method and DivRank.  ...  Experiments are conducted on DUC2004 data set and the results demonstrate the effectiveness of the supervised aggregation method compared with typical ensemble approaches.  ...  ., 2011) proposed a semi-supervised rank aggregation approach and the work minimizes the weight disagreements of different rankers to learn the aggregation function.  ... 
dblp:conf/coling/PeiYFH12 fatcat:dsy7xcqhtjb2rj6ai5i3jnd2qa

Relevance aggregation projections for image retrieval

Wei Liu, Wei Jiang, Shih-Fu Chang
2008 Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08  
In this paper, we address the two issues and propose a novel effective method called Relevance Aggregation Projections (RAP) for learning potent subspace projections in a semi-supervised way.  ...  Through coupling the idea of relevance aggregation with semi-supervised learning, we formulate a constrained quadratic optimization problem to learn the subspace projections which entail semantic mining  ...  Training this kind of learning models is referred to as semi-supervised learning. In this section, we evaluate several semi-supervised subspace learning models with relevance feedback.  ... 
doi:10.1145/1386352.1386372 dblp:conf/civr/LiuJC08 fatcat:fdsfrs4rcnfvpfmnyuiqxagzke

Distributed Information Retrieval and Applications [chapter]

Fabio Crestani, Ilya Markov
2013 Lecture Notes in Computer Science  
- supervised Supervised Results Merging Linear Non-linear Semi- supervised Unsupervised Fabio Crestani and Ilya Markov Distributed Information Retrieval and Applications 45 Distributed Information  ...  - supervised Supervised Results Merging Linear Non-linear Semi- supervised Unsupervised Fabio Crestani and Ilya Markov Distributed Information Retrieval and Applications 46 Distributed Information  ...  Category is predictive for shopping. 3 Results presentation positions results on a page in a supervised manner. This is an intensively studied problem that is not completely solved.  ... 
doi:10.1007/978-3-642-36973-5_104 fatcat:tpja4islvndhjpwla4m7xlkkcy

Estimation of Individual Micro Data from Aggregated Open Data [article]

Han-mook Yoo, Han-joon Kim, Jonghoon Chun
2017 arXiv   pre-print
model, which is learned by semi-supervised learning.  ...  In this paper, we propose a method of estimating individual micro data from aggregated open data based on semi-supervised learning and conditional probability.  ...  In this paper, to overcome the limitations of the aggregated open data, we propose a method of estimating the individual micro data from the aggregated open data based on semi-supervised learning and conditional  ... 
arXiv:1712.06802v1 fatcat:rdqi7dmdqjhxnavhyfqa44lgju

Semi-supervised OWA aggregation for link-based similarity evaluation and alias detection

Tossapon Boongoen, Qiang Shen
2009 2009 IEEE International Conference on Fuzzy Systems  
Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection Tossapon Boongoen and Qiang Shen Abstract-Within the past decades, many fuzzy aggregation techniques, ordered  ...  Performance Evaluation 1) Efficiency of Semi-Supervised Method: Initially, it is important to examine the effectiveness of the semi-supervised method for modeling a stress function (i.e. selecting β value  ... 
doi:10.1109/fuzzy.2009.5277168 dblp:conf/fuzzIEEE/BoongoenS09 fatcat:6urrrh7gmbfwtd5swjxgc4p5ay

Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization

Jiyi Li, Yasushi Kawase, Yukino Baba, Hisashi Kashima
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
The existing semi-supervised approaches do not consider such use of qualification questions.  ...  ., asking the same question to multiple workers and aggregating their answers) and supervised approaches such as using worker performance on past tasks or injecting qualification questions into tasks in  ...  The qualification questions can also be used in statistical aggregation methods in a semi-supervised manner.  ... 
doi:10.24963/ijcai.2020/213 dblp:conf/ijcai/LiKBK20 fatcat:4h33t6ozd5eddmpp6al7hij3wi

A semi-supervised learning algorithm for relevance feedback and collaborative image retrieval

Daniel Carlos Guimarães Pedronette, Rodrigo T. Calumby, Ricardo da S. Torres
2015 EURASIP Journal on Image and Video Processing  
In our approach, supervised learning is performed taking advantage of relevance labels provided by users.  ...  Rank aggregation We also use the Pairwise Recommendation algorithm [9] in rank aggregation tasks. Our objective is to combine various descriptors so that retrieval results can be improved.  ...  Alternatively, rank aggregation techniques have also been used in unsupervised approaches.  ... 
doi:10.1186/s13640-015-0081-6 fatcat:uinx4wos7fab3o2gnwywdlrq7a

Detecting 11K Classes: Large Scale Object Detection Without Fine-Grained Bounding Boxes

Hao Yang, Hao Wu, Hao Chen
2019 2019 IEEE/CVF International Conference on Computer Vision (ICCV)  
In this paper, we propose a semi-supervised large scale fine-grained detection method, which only needs bounding box annotations of a smaller number of coarsegrained classes and image-level labels of large  ...  Weakly-supervised methods, on the other hand, only require image-level labels for training, but the performance is far below their fully-supervised counterparts.  ...  Weakly-Supervised Detection Stream with Soft-Attention Proposal Re-ranking A classical way to aggregate proposal scores is to use max or average pooling [38] .  ... 
doi:10.1109/iccv.2019.00990 dblp:conf/iccv/YangWC19 fatcat:euiavla6uvfs3id5sobuul6v5y

Rumor Detection by Propagation Embedding Based on Graph Convolutional Network

Dang Thinh Vu, Jason J. Jung
2021 International Journal of Computational Intelligence Systems  
In our model, supervised learning generally outperforms semi-supervised learning for all aggregator functions except for the pooling one.  ...  Comparison between semi-supervised and supervised models To compare semi-supervised and supervised learning methods when the size of a training dataset is small, we train the model with different sizes  ... 
doi:10.2991/ijcis.d.210304.002 fatcat:qofc42ntx5c2lbfm5d4v7dvjsu

Going Deeper into Semi-supervised Person Re-identification [article]

Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh
2021 arXiv   pre-print
To reduce the need for labeled data, we focus on a semi-supervised approach that requires only a subset of the training data to be labeled.  ...  We also propose a PartMixUp loss that improves the discriminative ability of learned part-based features for pseudo-labeling in semi-supervised settings.  ...  Method Market-1501 DukeMTMC CUHK03 Rank-1 mAP Rank-1 mAP Rank-1 Rank-5 Supervised BIL 75.1 53.3 65.0 49.4 48.3 73.6 Semi-supervised BIL 79.5 62.1 69.4 50.2 53.8 76.8 Semi-supervised  ... 
arXiv:2107.11566v1 fatcat:kpbuly4pzrgvblouuifuq6eoem

ProLFA: Representative Prototype Selection for Local Feature Aggregation [article]

Xingxing Zhang, Zhenfeng Zhu, Yao Zhao
2019 arXiv   pre-print
Furthermore, ProLFA is also provided with a powerful generalization ability to deal flexibly with the semi-supervised and fully supervised scenarios in local feature aggregation.  ...  In this paper, we propose a generic formulation to provide a systematical solution (named ProLFA) to aggregate local descriptors.  ...  in semi-supervised scenarios.  ... 
arXiv:1910.11010v1 fatcat:bppdyqcdrjerffy4qdoissk2ha

Multiview Semi-supervised Learning for Ranking Multilingual Documents [chapter]

Nicolas Usunier, Massih-Reza Amini, Cyril Goutte
2011 Lecture Notes in Computer Science  
We describe a semi-supervised multiview ranking algorithm that exploits a global agreement between viewspecific ranking functions on a set of unlabeled observations.  ...  We show that our proposed algorithm achieves significant improvements over both semi-supervised multiview classification and semi-supervised single-view rankers on a large multilingual collection of Reuters  ...  Semi-supervised Multiview Learning for Ranking We present the framework of multiview, semi-supervised ranking with bipartite feedback.  ... 
doi:10.1007/978-3-642-23808-6_29 fatcat:xdmqogqynje2tjfsdvzrfj4p7m
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