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ORCID21st ICDM 2021: Auckland, New Zealand - Workshops
- 2021 International Conference on Data Mining, ICDM 2021 - Workshops, Auckland, New Zealand, December 7-10, 2021. IEEE 2021, ISBN 978-1-6654-2427-1
- Minghao Chen, Jiale Zheng:
Incorporating Adjacent User Modeling into Session-based Recommendation with Graph Neural Networks. 1-9 - Alexander Dallmann, Johannes Kohlmann, Daniel Zoller, Andreas Hotho:
Sequential Item Recommendation in the MOBA Game Dota 2. 10-17 - Wei Jiang, Fangquan Lin, Jihai Zhang, Cheng Yang, Hanwei Zhang, Ziqiang Cui
:
Dynamic Sequential Recommendation: Decoupling User Intent from Temporal Context. 18-26 - Domokos M. Kelen, András A. Benczúr:
A probabilistic perspective on nearest neighbor for implicit recommendation. 27-35 - Junbeom Kim, Sihyun Jeong, Goeon Park, Kihoon Cha, Ilhyun Suh, Byungkook Oh:
DynaPosGNN: Dynamic-Positional GNN for Next POI Recommendation. 36-44 - Tobias Koopmann, Konstantin Kobs, Konstantin Herud, Andreas Hotho:
CoBERT: Scientific Collaboration Prediction via Sequential Recommendation. 45-54 - Vladimir Provalov, Elizaveta Stavinova, Petr Chunaev:
SynEvaRec: A Framework for Evaluating Recommender Systems on Synthetic Data Classes. 55-64 - Shaina Raza, Syed Raza Bashir, Dora D. Liu, Usman Naseem:
Balanced News Neural Network for a News Recommender System. 65-74 - Joonyoung Yi, Beomsu Kim, Buru Chang:
Embedding Normalization: Significance Preserving Feature Normalization for Click-Through Rate Prediction. 75-84 - Wenxiong Wu, Yongli Cheng, Hong Jiang, Fang Wang, Xianghao Xu, Dan He, Jing Yu:
IBFM: An Instance-weight Balanced Factorization Machine for Sparse Prediction. 85-93 - Chuanyan Zhang, Xiaoguang Hong:
Challenging the Long Tail Recommendation on Heterogeneous Information Network. 94-101 - Shaoliang Zhang, Xuefeng Liu, Jianwei Niu, Huiyong Li:
ContentHE: Content-enhanced Network Embedding for Hashtag Representation. 102-109 - Yixing Chen, JingTao Yao:
Sentiment Analysis Using Part-of-Speech-Based Feature Extraction and Game-Theoretic Rough Sets. 110-117 - David Chong, Erl Lee, Matthew Fan, Pavan Holur, Shadi Shahsavari, Timothy R. Tangherlini, Vwani P. Roychowdhury:
A real-time platform for contextualized conspiracy theory analysis. 118-127 - Atrik Das, Kushal Sai Gunturi, Aditya Chandrasekhar, Abhinandan Padhi, Qian Liu:
Automated Pipeline for Sentiment Analysis of Political Tweets. 128-135 - Karol Gawron, Michal Pogoda, Norbert Ropiak, Michal Swedrowski, Jan Kocon:
Deep Neural Language-agnostic Multi-task Text Classifier. 136-142 - Jahedul Islam, Shubiour Shuvo, Tonmoy Sarker, Mohammad Zavid Parvez, Md Anisur Rahman:
Sentiment Analysis Framework Using Data Driven Approach. 143-150 - Dazhi Jiang, Runguo Wei, Hao Liu, Jintao Wen, Geng Tu, Lin Zheng, Erik Cambria:
A Multitask Learning Framework for Multimodal Sentiment Analysis. 151-157 - Amirmohammad Kazemeini, Sudipta Singha Roy, Robert E. Mercer, Erik Cambria:
Interpretable Representation Learning for Personality Detection. 158-165 - Jan Kocon, Jarema Radom, Ewa Kaczmarz-Wawryk, Kamil Wabnic, Ada Zajaczkowska, Monika Zasko-Zielinska:
AspectEmo: Multi-Domain Corpus of Consumer Reviews for Aspect-Based Sentiment Analysis. 166-173 - Ashok Kumar J, Erik Cambria, Tina Esther Trueman:
DUSE: A New Benchmark Dataset for Drug User Sentiment Extraction. 174-178 - Harsh Patel, Xulang Zhang, Qian Liu:
Enhancing Negation Scope Detection using Multitask Learning. 179-185 - Harsh Sakhrani, Saloni Parekh, Pratik Ratadiya:
Contextualized Embedding based Approaches for Social Media-specific Sentiment Analysis. 186-193 - Maoyuan Zhang, Jieqiong Zhang, Lisha Liu:
Modelling Context with Graph Convolutional Networks for Aspect-based Sentiment Analysis. 194-200 - Parag Agrawal, Priyadarshi, Vikrant Shimpi, Neha Behl, Deepa Vaidyanathan, Maitreya Natu:
Prediction Diagnostics - Addressing data veracity in predicting batch processes. 201-207 - Momoko Fujita, Akari Yamada, Mao Susuki, Hiroya Makino, Eisuke Kita:
Application of Machine Learning for Growth Environment Prediction in Agriculture. 208-213 - Giuliano Giuliani, Fabrizio Giuliani, Summer M. Husband:
A data-driven approach to predict hourly bill rates for US contingent workers. 214-221 - Yuta Kaneko:
A Time-series Analysis of How Google Trends Searches Affect Cryptocurrency Prices for Decentralized Finance and Non-Fungible Tokens. 222-227 - Hiun Kim, Jisu Jeong, Kyung-Min Kim, Dongjun Lee, Hyun Dong Lee, Dongpil Seo, Jeeseung Han, Dong Wook Park, Ji Ae Heo, Rak Yeong Kim:
Intent-based Product Collections for E-commerce using Pretrained Language Models. 228-237 - Hiroya Makino, Eisuke Kita:
Stochastic Schemata Exploiter-Based AutoML. 238-245 - Ryo Matsui, Taketo Naito, Suguru Yaginuma, Kazuhide Nakata:
Confident Collaborative Metric Learning. 246-253 - Amit Neil Ramkissoon, Wayne Goodridge:
Legitimacy: An Ensemble Learning Model for Credibility Based Fake News Detection. 254-261 - Fengmei Sun, Licheng Zhao, Yi Zuo, Yuta Kaneko:
Application of Fractal Analysis for Customer Classification Based on Path Data. 262-267 - Mahdi Tabassian, Robbert Verbeke, Tom Tourwé, Elena Tsiporkova:
Data-Driven Divide-and-Conquer for Estimating Build Times of 3D Objects. 268-277 - Zhao Wang, Yuusuke Nakano, Ken Nishimatsu:
The Vehicle Routing Problem with Time Windows and Time Costs. 278-287 - Weizheng Zhao, Yi Zuo, Licheng Zhao, Junhao Jiang:
Application of LSTM Models to Predict In-store Trajectory of Customers. 288-294 - Filip Guzy, Michal Wozniak, Bartosz Krawczyk:
Evaluating and Explaining Generative Adversarial Networks for Continual Learning under Concept Drift. 295-303 - Jesus L. Lobo, Javier Del Ser, Eneko Osaba:
Lightweight Alternatives for Hyper-parameter Tuning in Drifting Data Streams. 304-311 - Chang How Tan, Vincent C. S. Lee, Mahsa Salehi, Slaven Marusic, Srimal Jayawardena, Dion Lucke:
A Fully Unsupervised and Efficient Anomaly Detection Approach with Drift Detection Capability. 312-321 - Deeksha Aggarwal, J. Senthilnath, Uttam Kumar, Vivek Yadav, Sushant Kulkarni, Md Meftahul Ferdaus, Xiaoli Li:
SGDOL: Self-evolving Generative and Discriminative Online Learning for Data Stream Classification. 322-330 - Alessio Bernardo, Giacomo Ziffer, Emanuele Della Valle:
IEBench: Benchmarking Streaming Learners on Imbalanced Evolving Data Streams. 331-340 - Salvatore Greco, Tania Cerquitelli:
Drift Lens: Real-time unsupervised Concept Drift detection by evaluating per-label embedding distributions. 341-349 - Ruoyan Kong, Zhanlong Qiu, Yang Liu, Qi Zhao:
NimbleLearn: A Scalable and Fast Batch-mode Active Learning Approach. 350-359 - Johannes Langguth, Aigars Tumanis, Ariful Azad:
Incremental Clustering Algorithms for Massive Dynamic Graphs. 360-369 - Tung-Duong Mai, Kien Hoang, Aitolkyn Baigutanova, Gaukhartas Alina, Sundong Kim:
Customs Fraud Detection in the Presence of Concept Drift. 370-379 - Saulo Martiello Mastelini, Jacob Montiel, Heitor Murilo Gomes, Albert Bifet, Bernhard Pfahringer, André C. P. L. F. de Carvalho:
Fast and lightweight binary and multi-branch Hoeffding Tree Regressors. 380-388 - Huiyu Mu, Ruizhi Sun, Gang Yuan, Jiayao Li, Miao Wang:
Crowd behavior detection in videos using statistical physics. 389-397 - Philipp Scharpf, Chi Lap Hong, Oliver Duerr:
Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations. 398-404 - Xihui Wang, Pascale Kuntz, Frank Meyer, Vincent Lemaire:
Multi-Label kNN classifier with Online Dual Memory on data stream. 405-413 - Zhaohui Wang, Xiao Lin, Abhinav Mishra, Ram Sriharsha:
Online Changepoint Detection on a Budget. 414-420 - Guangtao Zheng, Aidong Zhang:
Few-Shot Class-Incremental Learning with Meta-Learned Class Structures. 421-430 - Anna Beer, Lisa Stephan, Thomas Seidl:
LUCKe - Connecting Clustering and Correlation Clustering. 431-440 - Julian Busch, Maximilian Hünemörder, Janis Held, Peer Kröger, Thomas Seidl:
Implicit Hough Transform Neural Networks for Subspace Clustering. 441-448 - Chris Connell, Yang Wang:
TensorMode Algorithm for Network Embedding in Dynamic Environments. 449-459 - Yash Garg:
ReTriM: Reconstructive Triplet Loss for Learning Reduced Embeddings for Multi-Variate Time Series. 460-465 - Shuo Liu, Liwen Xu:
Anomaly Detection with Dual Adversarial Training. 466-473 - Jürgen Prinzbach, Tobias Lauer, Nicolas Kiefer:
Accelerating Density-Based Subspace Clustering in High-Dimensional Data. 474-481 - Yamonporn Thummanusarn, Ata Kabán:
Random Projection Through the Lens of Data Complexity Indicators. 482-489 - Jing Yang, Gaojin Fan, Anbo Shen, Aiguo Wang:
Causal structure learning of nonlinear additive noise model based on streaming feature. 490-499 - Sathyanarayanan N. Aakur, Vineela Indla, Vennela Indla, Sai Narayanan, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis. 500-507 - Berk Yenidogan, Shreyasi Pathak, Jeroen Geerdink, Johannes H. Hegeman, Maurice van Keulen:
Multimodal Machine Learning for 30-Days Post-Operative Mortality Prediction of Elderly Hip Fracture Patients. 508-516 - Yun Zhao, Yuqing Wang, Junfeng Liu, Haotian Xia, Zhenni Xu, Qinghang Hong, Zhiyang Zhou, Linda R. Petzold:
Empirical Quantitative Analysis of COVID-19 Forecasting Models. 517-526 - Yogesh Kulkarni, Sayf Hussain Z, Krithi Ramamritham, Nivethitha Somu:
EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid. 527-536 - Sharath M. Shankaranarayana, Davor Runje:
Attention Augmented Convolutional Transformer for Tabular Time-series. 537-541 - Susumu Naito, Yasunori Taguchi, Kouta Nakata, Yuichi Kato:
Anomaly Detection for Multivariate Time Series on Large-scale Fluid Handling Plant Using Two-stage Autoencoder. 542-551 - Patrick Owusu, Armelle Brun, Shengrui Wang:
Towards Dynamic Structure Changes Detection in Financial Series via Causal Analysis. 552-557 - Topon Kumar Paul, Sreeharsha Raghavendra, Ken Ueno, Fang Ni, Hiromasa Shin, Kaneharu Nishino, Ryusei Shingaki:
Forecasting of Reservoir Inflow by the Combination of Deep Learning and Conventional Machine Learning. 558-565 - Md. Tanvir Alam, Amit Roy, Chowdhury Farhan Ahmed, Md. Ashraful Islam, Carson K. Leung:
Mining High Utility Subgraphs. 566-573 - Yangming Chen, Philippe Fournier-Viger, Farid Nouioua, Youxi Wu:
Sequence Prediction using Partially-Ordered Episode Rules. 574-580 - Cedric Kulbach, Steffen Thoma:
Personalized Neural Architecture Search. 581-590 - Jerry Chun-Wei Lin, Youcef Djenouri, Gautam Srivastava, Jimmy Ming-Tai Wu:
Large-Scale Closed High-Utility Itemset Mining. 591-598 - Mourad Nouioua, Philippe Fournier-Viger, Jun-Feng Qu, Jerry Chun-Wei Lin, Wensheng Gan, Wei Song:
CHUQI-Miner: Mining Correlated Quantitative High Utility Itemsets. 599-606 - Pamalla Veena, So Nakamura, Palla Likhitha, R. Uday Kiran, Yutaka Watanobe, Koji Zettsu:
A Unified Framework to Discover Partial Periodic-Frequent Patterns in Row and Columnar Temporal Databases. 607-614 - Wei Song, Caiyu Fang, Wensheng Gan:
TopUMS: Top-k Utility Mining in Stream Data. 615-622 - Chi-Jen Wu, Wei-Sheng Zeng, Jan-Ming Ho:
Optimal Segmented Linear Regression for Financial Time Series Segmentation. 623-630 - Corinna Coupette, Jyotsna Singh, Holger Spamann:
Simplify Your Law: Using Information Theory to Deduplicate Legal Documents. 631-638 - Jason T. Lam, Yuhao Chen, Farhana H. Zulkernine, Samuel Dahan:
Detection of Similar Legal Cases on Personal Injury. 639-646 - Sourav Mukherjee, David Widmark, Vince DiMascio, Tim Oates:
Determining Standard Occupational Classification Codes from Job Descriptions in Immigration Petitions. 647-652 - Stavroula Skylaki, Ali Oskooei, Omar Bari, Nadja Herger, Zac Kriegman:
Legal Entity Extraction using a Pointer Generator Network. 653-658 - Xingyu Cai, Yuchen Bian, Jiaji Huang, Boxiang Liu, Jiahong Yuan, Kenneth Church:
SSPF: a Simple and Scalable Parameter Free Clustering Method. 659-668 - Guojing Cong, Seung-Hwan Lim:
Versatile feature learning with graph convolutions and graph structures. 669-677 - Abdoul Wahab Diallo, Ndèye Niang, Mory Ouattara:
Sparse Subspace K-means. 678-685 - Wengang Guo, Kaiyan Lin, Wei Ye:
Deep Embedded K-Means Clustering. 686-694 - Ioannis A. Nellas, Sotiris K. Tasoulis, Vassilis P. Plagianakos:
Convolutional Variational Autoencoders for Image Clustering. 695-702 - Paul Riverain, Simon Fossier, Mohamed Nadif:
Model-based Poisson co-clustering for Attributed Networks. 703-710 - Da Sun Handason Tam, Siyue Xie, Wing Cheong Lau:
Graph Representation Learning with Adaptive Mixtures. 711-718 - Jun Wang, Jinghua Tan, Hanlei Jin, Shuo Qi:
Unsupervised graph-clustering learning framework for financial news summarization. 719-726 - Nicklas Sindlev Andersen, Marco Chiarandini, Stefan Jänicke, Panagiotis Tampakis, Arthur Zimek:
Detecting Wandering Behavior of People with Dementia. 727-733 - Johanna Baro, Mostepha Khouadjia:
Passenger flow forecasting on transportation network: sensitivity analysis of the spatiotemporal features. 734-741 - Anton Dereventsov, Ranga Raju Vatsavai, Clayton G. Webster:
On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks. 742-749 - Michiel Dhont, Elena Tsiporkova, Nicolás González-Deleito:
Deriving Spatio-temporal Trajectory Fingerprints from Mobility Data using Non-Negative Matrix Factorisation. 750-759 - Seyed Navid Mohammadi Foumani, Chang Wei Tan, Mahsa Salehi:
Disjoint-CNN for Multivariate Time Series Classification. 760-769 - Peter Van Hese, Henrique Cabral, Wouter Aerts, Elena Tsiporkova:
Functional Foot Segmentation Based on Plantar Pressure Measurements for Profiling Subjects Performing a Running Exercise. 770-777 - Ruixuan Yan, Agung Julius, Maria Chang, Achille Fokoue, Tengfei Ma, Rosario Uceda-Sosa:
STONE: Signal Temporal Logic Neural Network for Time Series Classification. 778-787 - Xucan Chen, Wei Cheng, Marie Ouellet, Yuan Li, David Maimon, Yubao Wu:
Identifying Darknet Vendor Wallets by Matching Feedback Reviews with Bitcoin Transactions. 788-797 - Fares Meghdouri, Félix Iglesias Vázquez, Tanja Zseby:
Shedding Light in the Tunnel: Counting Flows in Encrypted Network Traffic. 798-804 - Utkarsh Raghav, Elisa Martínez Marroquín, Wanli Ma:
Static Analysis for Android Malware detection with Document Vectors. 805-812 - Christina L. Ting, Nicholas Johnson, Uzoma Onunkwo, J. Derek Tucker:
Faster classification using compression analytics. 813-822 - Kaan Demir, Bach Hoai Nguyen, Bing Xue, Mengjie Zhang:
Multi-objective Feature Selection with a Sparsity-based Objective Function and Gradient Local Search for Multi-label Classification. 823-832 - Bach Hoai Nguyen, Bing Xue, Mengjie Zhang:
Automated and Efficient Sparsity-based Feature Selection via a Dual-component Vector. 833-842 - Juan Antonio Romero del Castillo, Domingo Ortiz-Boyer, Nicolás García-Pedrajas:
Instance selection for multi-label learning based on a scalable evolutionary algorithm. 843-851 - Harsh Sakhrani, Saloni Parekh, Pratik Ratadiya:
Transformer-based Hierarchical Encoder for Document Classification. 852-858 - Jiangshu Du, Yingtong Dou, Congying Xia, Limeng Cui, Jing Ma, Philip S. Yu:
Cross-lingual COVID-19 Fake News Detection. 859-862 - Haridimos Kondylakis, Angelina Kouroubali, Dimitrios G. Katehakis:
Patient Preferences: An Unexplored Area in the Post-Pandemic Era. 863-866 - Da Li, Shiho Ishitsubo, Katsuyuki Yamauchi, Panote Siriaraya, Shinsuke Nakajima, Yukiko Kawai:
A Sentiment-aware Delightful Walking Route Recommendation System Considering the Scenery and Season. 867-872 - Nidhi Mulay, Vikas Bishnoi, Yatin Katyal, Mohsen Bahrami, Esteban Moro, Ankur Saraswat, Alex Pentland:
Effects of stimulus checks on spending patterns of different economic groups. 873-877 - Taisei Ninomiya, Fujio Toriumi, Hiroka Zaitsu, Yusuke Miyake:
Analysis of User Behavior in a C2C Platform during COVID-19 Pandemic. 878-881 - Sudha Tushara Sadasivuni, Yanqing Zhang:
Analyzing the Bad-Words in tweets of Twitter users to discover the Mental Health Happiness Index and Feel-Good-Factors. 882-888 - Kenta Suzuki, Panote Siriaraya, Wan-Jou She, Ryotaro Tanaka, Da Li, Shinsuke Nakajima:
HappyRec: Evaluation of a "Happy Spot" Recommendation System Aimed at Improving Mental Well-Being. 889-892 - Zachary Yang, Anne Imouza, Kellin Pelrine, Sacha Levy, Jiewen Liu, Gabrielle Desrosiers-Brisebois, Jean-François Godbout, André Blais, Reihaneh Rabbany:
Online Partisan Polarization of COVID-19. 893-901 - Ruijin Jiang, Zhaohui Cheng:
Mixture Gaussian Prototypes for Few-Shot Learning. 902-908 - Xuchan Ju, Zhenghao Yan, Tianhe Wang:
Overview of Optimization Algorithms for Large-scale Support Vector Machines. 909-916 - Yong Shi, Xiaodong Xue, Yi Qu, Jiayu Xue, Linzi Zhang:
Machine Learning and Deep Learning Methods used in Safety Management of Nuclear Power Plants: A Survey. 917-924 - Ludwig Zellner, Janina Sontheim, Florian Richter, Gabriel Lindner, Thomas Seidl:
SCORER-Gap: Sequentially Correlated Rules for Event Recommendation Considering Gap Size. 925-934 - Chen Cao, Shihao Li, Shuo Yu, Zhikui Chen:
Fake Reviewer Group Detection in Online Review Systems. 935-942 - Bernat Coma-Puig, Josep Carmona:
A Human-in-the-Loop Approach based on Explainability to Improve NTL Detection. 943-950 - Mingliang Hou, Jing Ren, Falih Febrinanto, Ahsan Shehzad, Feng Xia:
Cross Network Representation Matching with Outliers. 951-958 - Jing Ren, Feng Xia, Yemeng Liu, Ivan Lee:
Deep Video Anomaly Detection: Opportunities and Challenges. 959-966 - Ken-Yu Lin, Roy Ka-Wei Lee, Wei Gao, Wen-Chih Peng:
Early Prediction of Hate Speech Propagation. 967-974 - Zhiyue Wu, Hongzuo Xu, Yijie Wang, Yongjun Wang:
Surrogate Supervision-based Deep Weakly-supervised Anomaly Detection. 975-982 - Yiming Li, Da Sun Handason Tam, Siyue Xie, Xiaxin Liu, Qiufang Ying, Wing Cheong Lau, Dah Ming Chiu, Shou Zhi Chen:
Temporal Graph Representation Learning for Detecting Anomalies in E-payment Systems. 983-990 - Andreas Lohrer, Jan Deller, Maximilian Hünemörder, Peer Kröger:
OAB - An Open Anomaly Benchmark Framework for Unsupervised and Semisupervised Anomaly Detection on Image and Tabular Data Sets. 991-1000 - Chakkrit Termritthikun, Lin Xu, Yemeng Liu, Ivan Lee:
Neural Architecture Search and Multi-Objective Evolutionary Algorithms for Anomaly Detection. 1001-1008 - Xinye Chen, Stefan Güttel:
A fast sorting-based aggregation method for symbolic time series representation. 1009-1016 - Kang Gu, Soroush Vosoughi, Temiloluwa Prioleau:
Feature Selection for Multivariate Time Series via Network Pruning. 1017-1024 - Ali Hammadeh, Amin Zayani, Andreas W. Kempa-Liehr:
Time Series Ordinal Regression for Supporting the Storage of Temperature Sensitive Medication in Domestic Refrigerators. 1025-1031 - Trent Henderson, Ben D. Fulcher:
An Empirical Evaluation of Time-Series Feature Sets. 1032-1038 - Anton Kovantsev, Petr Chunaev, Klavdiya Bochenina:
Evaluating Time Series Predictability via Transition Graph Analysis. 1039-1046 - Shuyan Liu, Yue Chen:
Comparison of Variant Principal Component Analysis Using New RNN-based Framework for Stock Prediction. 1047-1056 - Scott Simmons, Louis Jarvis, David Dempsey, Andreas W. Kempa-Liehr:
Data Mining on Extremely Long Time-Series. 1057-1066 - Atharv Yeolekar, Sagar Patel, Shreejaa Talla, Krishna Rukmini Puthucode, Azim Ahmadzadeh, Viacheslav M. Sadykov, Rafal A. Angryk:
Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 Methods. 1067-1076 - Boris Belyakov, Dmitry Sizykh:
Deep Reinforcement Learning Task for Portfolio Construction. 1077-1082 - Pierre Haritz, Lukas Pfahler, Thomas Liebig, Helena Kotthaus:
Self-Supervised Source Code Annotation from Related Research Papers. 1083-1084 - Smilla Hinterreiter:
A Gamified Approach To Automatically Detect Biased Wording And Train Critical Reading. 1085-1086 - Tianyi Li, Philippe Goupil, Josiane Mothe, Olivier Teste:
Early Detection of Atmospheric Turbulence for Civil Aircraft: A Data Driven Approach. 1087-1093 - YongKyung Oh, Sungil Kim:
Multi-channel Convolution Neural Network for Gas Mixture Classification. 1094-1095 - Timo Spinde:
An Interdisciplinary Approach for the Automated Detection and Visualization of Media Bias in News Articles. 1096-1103 - Jun Wang, Jinghua Tan, Jiujiu Chen, Hanlei Jin:
A Knowledge-aware and Time-sensitive Financial News Recommendation System Based on Firm Relation Derivation. 1104-1111 - Bo Xiao, Wuguannan Yao, Xiang Zhou:
Optimal Option Hedging with Policy Gradient. 1112-1119
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