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DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning.

, , , , and . SemEval@NAACL-HLT, page 305-312. Association for Computational Linguistics, (2018)

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DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning., , , , and . SemEval@NAACL-HLT, page 305-312. Association for Computational Linguistics, (2018)Manifold Learning of Overcomplete Feature Spaces in a Multimodal Biometric Recognition System of Iris and Palmprint., , and . CRV, page 191-196. IEEE Computer Society, (2017)Dimensionality Reduction and Visualization by Doubly Kernelized Unit Ball Embedding., and . Canadian Conference on AI, volume 10832 of Lecture Notes in Computer Science, page 224-230. Springer, (2018)Nonlinear Dimensionality Reduction by Unit Ball Embedding (UBE) and Its Application to Image Clustering., and . ICMLA, page 983-988. IEEE Computer Society, (2016)Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification., , , , , , and . ESANN, (2017)Fast PMI-Based Word Embedding with Efficient Use of Unobserved Patterns., and . AAAI, page 7031-7038. AAAI Press, (2019)Spectral Word Embedding with Negative Sampling., and . AAAI, page 5481-5487. AAAI Press, (2018)Fusing Iris, Palmprint and Fingerprint in a Multi-biometric Recognition System., , , , and . CRV, page 327-334. IEEE Computer Society, (2016)Anomaly detection in maritime data based on geometrical analysis of trajectories., , , and . FUSION, page 1100-1105. IEEE, (2015)A Disaster Invariant Feature for localization., , , and . IROS, page 1096-1101. IEEE, (2010)