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ORCID14th MLDM 2018: New York, NY, USA
- Petra Perner:
Machine Learning and Data Mining in Pattern Recognition - 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part I. Lecture Notes in Computer Science 10934, Springer 2018, ISBN 978-3-319-96135-4 - Aybüke Öztürk
, Stéphane Lallich, Jérôme Darmont, Sylvie Yona Waksman:
MaxMin Linear Initialization for Fuzzy C-Means. 1-15 - Valentina Sulimova, Alexander Zhukov, Olga Krasotkina, Vadim Mottl, Anatoly Markov:
Automatic Rail Flaw Localization and Recognition by Featureless Ultrasound Signal Analysis. 16-27 - Daoping Wang, Liangyue Xu, Amjad Younas:
Social Media Sentiment Analysis Based on Domain Ontology and Semantic Mining. 28-39 - Anshul Rai, Zackary Crosley, Srivignessh Pacham Sri Srinivasan:
Mining Associations in Large Graphs for Dynamically Incremented Marked Nodes. 40-48 - Hang Shi, Chengjun Liu:
A New Global Foreground Modeling and Local Background Modeling Method for Video Analysis. 49-63 - Rawan AlSaad, Somaya Al-Máadeed, Md. Abdullah Al Mamun, Sabri Boughorbel:
A Deep Learning Based Automatic Severity Detector for Diabetic Retinopathy. 64-76 - Dima Badawi, Hakan Altinçay:
Compact Representation of Documents Using Terms and Termsets. 77-84 - Shlomit Gur, Vasant G. Honavar:
PATENet: Pairwise Alignment of Time Evolving Networks. 85-98 - In-Cheol Kim, George R. Thoma:
Automated Identification of Potential Conflict-of-Interest in Biomedical Articles Using Hybrid Deep Neural Network. 99-112 - Mohammad Ghasemi Hamed, Ahmad Akbari:
Hierarchical Bayesian Classifier Combination. 113-125 - Manoel Alves de Almeida Neto, Roberta Andrade de Araújo Fagundes, Carmelo J. A. Bastos Filho:
Optimizing Support Vector Regression with Swarm Intelligence for Estimating the Concrete Compression Strength. 126-137 - Noha S. Tawfik, Marco R. Spruit:
Automated Contradiction Detection in Biomedical Literature. 138-148 - Matthias J. Feiler:
Following the Common Thread Through Word Hierarchies. 149-158 - Kazem Qazanfari, Abdou Youssef:
Document Clustering Using Local and Universal Knowledge. 159-173 - Ali Al Essa, Miad Faezipour:
Tweet Classification Using Sentiment Analysis Features and TF-IDF Weighting for Improved Flu Trend Detection. 174-186 - Wei Li, Waleed Meleis:
Adaptive Adjacency Kanerva Coding for Memory-Constrained Reinforcement Learning. 187-201 - Jiyun Chen, Jihong Wang, Xiaodan Wang, Yingyi Du, Huiyou Chang:
Predicting Drug Target Interactions Based on GBDT. 202-212 - Hao Zhang, Shinji Nakadai, Kenji Fukumizu:
From Black-Box to White-Box: Interpretable Learning with Kernel Machines. 213-227 - David Vengerov:
A Two-List Framework for Accurate Detection of Frequent Items in Data Streams. 228-243 - Shruti Kaushik, Abhinav Choudhury, Nataraj Dasgupta, Sayee Natarajan, Larry A. Pickett, Varun Dutt:
Evaluating Frequent-Set Mining Approaches in Machine-Learning Problems with Several Attributes: A Case Study in Healthcare. 244-258 - Soumadip Ghosh, Arnab Hazra, Bikramjit Choudhury, Payel Biswas, Amitava Nag:
A Comparative Study to the Bank Market Prediction. 259-268 - Stefan Thaler, Vlado Menkovski, Milan Petkovic:
Deep Metric Learning for Sequential Data Using Approximate Information. 269-282 - Christine Hines, Abdou Youssef:
Machine Learning Applied to Point-of-Sale Fraud Detection. 283-295 - Rina Singh, Jeffrey A. Graves, Douglas A. Talbert, William Eberle:
Prefix and Suffix Sequential Pattern Mining. 296-311 - Pattanapong Chantamit-o-pas, Madhu Goyal:
Long Short-Term Memory Recurrent Neural Network for Stroke Prediction. 312-323 - Sam Thomas, Nasseh Tabrizi:
Adversarial Machine Learning: A Literature Review. 324-334 - Haodi Jiang, Turki Turki, Sen Zhang, Jason T. L. Wang:
Reverse Engineering Gene Regulatory Networks Using Graph Mining. 335-349 - Weiping Pei, Youye Xie, Gongguo Tang:
Spammer Detection via Combined Neural Network. 350-364 - Meenu Ajith, Aswathy Rajendra Kurup:
Pedestrian Detection: Performance Comparison Using Multiple Convolutional Neural Networks. 365-379 - Meng-Sung Wu, Jun-Yi Lu:
Automated Machine Learning Algorithm Mining for Classification Problem. 380-392 - Xiaqiong Li, Xiaochun Wang, Xia Li Wang:
Enhancing Outlier Detection by an Outlier Indicator. 393-405 - Nataliya Sokolovska, Olga Permiakova, Sofia K. Forslund, Jean-Daniel Zucker:
A Semi-supervised Approach to Discover Bivariate Causality in Large Biological Data. 406-420 - Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker:
Risk Scores Learned by Deep Restricted Boltzmann Machines with Trained Interval Quantization. 421-435 - Roni Ben Ishay, Maya Herman, Chaim Yosefi:
A New Approach for Tuned Clustering Analysis. 436-452
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