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The 7th IEEE International Conference on Data Science and Advanced Analytics

6-9 October 2020
Sydney, Australia

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The 7th IEEE International Conference on
Data Science and Advanced Analytics

6-9 October 2020
Sydney, Australia

Main Track Papers

Research Track

  • A Graph Convolutional Encoder and Decoder Model for Rumor
  • Hongbin Lin, Xianghua Fu and Xi Zhang

  • Period Estimation For Incomplete Time Series
  • Lin Zhang and Petko Bogdanov

  • OnlineBTD: Streaming Algorithms to Track the Block Term
  • Ekta Gujral and Evangelos Papalexakis

  • Learning Fair and Transferable Representations with Theoretical Guarantees
  • Luca Oneto, Michele Donini, Massimiliano Pontil and Andreas Maurer

  • Efficient Frequent Subgraph Mining in Transactional Databases
  • Pascal Welke

  • Accurately Quantifying a Billion Instances per Second
  • Waqar Hassan, André Maletzke and Gustavo Batista

  • Ensemble of Hierarchical Temporal Memory for Anomaly Detection
  • Farzaneh Shoeleh, Masoud Erfani, Duc-Phong Le and Ali A. Ghorbani

  • Joint Bayesian Variable Selection and Graph Estimation for Non-linear SVM with Application to Genomics Data
  • Wenli Sun, Changgee Chang and Qi Long

  • Shells within Minimum Enclosing Balls
  • Christian Bauckhage, Michael Bortz and Rafet Sifa

  • MRSweep: Distributed In-Memory Sweep-line for Scalable Object Intersection Problems
  • Tilemachos Pechlivanoglou, Mahmoud Alsaeed and Manos Papagelis

  • Weakly Supervised Person Search
  • Lan Yan, Wenbo Zheng, Chao Gou and Fei-Yue Wang

  • Dimensionality-adaptive K-center in Sliding Windows
  • Paolo Pellizzoni, Andrea Pietracaprina and Geppino Pucci

  • Body Pose and Deep Hand-shape Feature Based American Sign Language Recognition
  • Al Amin Hosain, Panneer Selvam Santhalingam, Parth Pathak, Huzefa Rangwala and Jana Kosecka

  • MEE: An Automatic Metric for Evaluation Using Embeddings for Machine Translation
  • Ananya Mukherjee, Hema Ala, Manish Shrivastava and Dipti Misra Sharma

  • Attributed Network Embedding with Community Preservation
  • Tong Huang, Lihua Zhou, Kevin Lü, Lizhen Wang and Guowang Du

  • Economic Worth-Aware Word Embeddings
  • Yusan Lin, Peifeng Yin and Wang-Chien Lee

  • Improving Product Placement in Retail with Generalized High-Utility Itemsets
  • Chinmay Bapna, Polepalli Krishna Reddy and Anirban Mondal

  • Estimating Countries’ Peace Index through the Lens of the World’s News as Monitored by GDELT
  • Vasiliki Voukelatou, Ioanna Miliou, Lorenzo Gabrielli, Luca Pappalardo and Fosca Giannotti

  • Block-Approximated Exponential Random Graphs
  • Florian Adriaens, Alexandru Mara, Jefrey Lijffijt and Tijl De Bie

  • Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?
  • Alexandru Mara, Jefrey Lijffijt and Tijl De Bie

  • Exploiting BERT with Global-Local Context and Label Dependency for Aspect Term Extraction
  • Qingxuan Zhang and Chongyang Shi

  • Discovering Maximal Periodic-Frequent Patterns in Very Large Temporal Databases
  • R. Uday Kiran, Yutaka Watanobe, Bhaskar Chowdary, Koji Zettsu, Masashi Toyoda and Masaru Kitsuregawa

  • Spatio-Temporal Functional Neural Networks
  • Aniruddha Rajendra Rao, Qiyao Wang, Haiyan Wang, Hamed Khorasgani and Chetan Gupta

  • SesameBERT: Attention for Anywhere
  • Ta-Chun Su and Hsiang-Chih Cheng

  • Optimal Data Placement for Data-Centric Algorithms on NVM-Based Hybrid Memory
  • Yongping Luo, Peiquan Jin and Shouhong Wan

  • AdvPL: Adversarial Personalized Learning
  • Wei Du and Xintao Wu

  • Coordinate Descent Method for Log-linear Model on Posets
  • Shota Hayashi, Mahito Sugiyama and Shin Matsushima

  • Positive Influence Maximization and Negative Influence Minimization in Signed Networks under Competitive Independent Cascade Model
  • Cheng-En Sung, Hao-Shang Ma and Jen-Wei Huang

  • Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport
  • Luu Huu Phuc, Koh Takeuchi, Makoto Yamada and Hisashi Kashima

  • Active Learning of SVDD Hyperparameter Values
  • Holger Trittenbach, Klemens Böhm and Ira Assent

  • Denoising of Magnetic Resonance Images with Deep Neural Regularizer Driven by Image Prior
  • Yazhou Zhu, Xiang Pan, Jing Zhu, Lihua Li and Yuan Liu

  • Interpretability and Refinement of Clustering
  • Felix Iglesias, Tanja Zseby and Arthur Zimek

  • CO2Vec: Embeddings of Co-Ordered Networks Based on Mutual Reinforcement
  • Meng-Fen Chiang, Ee-Peng Lim, Wang-Chien Lee and Philips Kokoh Prasetyo

  • Active Sampling for Learning Interpretable Surrogate Machine Learning Models
  • Amal Saadallah and Katharina Morik

  • FONDUE: Framework for Node Disambiguation Using Network Embeddings
  • Ahmad Mel, Bo Kang, Jefrey Lijffijt and Tijl De Bie

  • Mix2Vec: Unsupervised Mixed Data Representation
  • Chengzhang Zhu, Qi Zhang, Longbing Cao and Arman Abrahamyan

  • Near-duplicated Loss for Accurate Object Localization
  • He Liu, Xiaocheng Yang, Huaping Liu, Tao Kong and Fuchun Sun

  • Information Exposure From Relational Background Knowledge on Social Media
  • Shuo Liu, Lisa Singh and Kevin Tian

  • Sequence Learning with Side Dependencies
  • Zhiwei Wang, Hui Liu, Gale Yan Huang and Zitao Liu
    Application Track

  • RIC-NN: A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy
  • Kei Nakagawa, Masaya Abe and Junpei Komiyama

  • Driving with Data in the Motor City: Understanding and Predicting Fleet Maintenance Patterns
  • Josh Gardner, Jawad Mroueh, Natalia Jenuwine, Noah Waverdyck, Samuel Krassenstein, Arya Farahi and Danai Koutra

  • Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network
  • Md. Rezaul Karim, Bharathi Raja Chakravarthi, John P. McCrae and Michael Cochez

  • Boosting Fashion Image Attributes Classification Performance with MT-GAN Training Technique
  • Qun Li, Changbo Hu, Keng-Hao Chang and Ruofei Zhang

  • HANKE: Hierarchical Attention Networks for Knowledge Extraction in Political Science Domain
  • Erick Skorupa Parolin, Latifur Khan, Vito D’Orazio, Javier Osorio, Patrick Brandt and Jennifer Holmes

  • Precision Coupon Targeting with Dynamic Customer Triage
  • Chuanren Liu and Wenxiang Zhu

  • Automating and Analyzing Whole-Farm Carbon Models
  • Aditi Maheshwari, Curtis Dyreson, Jennifer Reeve, Vishal Sharma and Anthony Whaley

  • Probability of Default Estimation with a Reject Option
  • Lize Coenen, Ahmed K.A. Abdullah and Tias Guns

  • Profiling US Restaurants from Billions of Payment Card Transactions
  • Himel Dev and Hossein Hamooni

  • Embedding for Anomaly Detection on Health Insurance Claims
  • Jiaqi Lu, Benjamin C. M. Fung and William K. Cheung

  • Cross-Layer Profiling of Encrypted Network Data for Anomaly Detection
  • Fares Meghdouri, Felix Iglesias and Tanja Zseby

  • Interactive Machine Learning Tool for Clustering in Visual Analytics
  • Michael Thrun, Felix Pape and Alfred Ultsch

  • Stress Prediction from Head Motion
  • Hitoshi Kusano, Yuji Horiguchi, Yukino Baba and Hisashi Kashima

  • Using Data Science to Improve the Identification of Plant Nutritional Status
  • David Condaminet, Albrecht Zimmermann, Bastien Billiot, Bruno Cremilleux and Sylvain Pluchon

  • A Distance Metric for Sets of Events
  • Raphael Sahann, Claudia Plant and Torsten Möller

  • Matching Research Publications to the United Nations’ Sustainable Development Goals by Multi-Label-Learning with Hierarchical Categories
  • Rui Zhang, Maéva Vignes, Ulrich Steiner and Arthur Zimek

  • Why Should I Trust This Item? Explaining the Recommendations of any Model
  • Corentin Lonjarret, Céline Robardet, Marc Plantevit, Roch Auburtin and Martin Atzmueller

  • Cardea: An Open Automated Machine Learning Framework forElectronic Health Records
  • Sarah Alnegheimish, Najat Alrashed, Faisal Aleissa, Shahad Althobaiti, Donyu Liu, Mansour Alsaleh and Kalyan Veeramachaneni
    © Copyright | DSAA 2020