SIGMOD 2021

link

anomaly detection

• Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries

  Susik Yoon (KAIST); Yooju Shin (KAIST); Jae-Gil Lee (KAIST)$^{\star}$; Byung Suk Lee (University of Vermont)

• GPU-Accelerated Graph Label Propagation for Real-Time Fraud Detection

  chang ye (Singapore Management University)$^{\star}$; Yuchen Li (Singapore Management University); Bingsheng He (National University of Singapore); Zhao Li (Alibaba Group); Jianling Sun (Zhejiang University)

• Fast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach

  Daichi Amagata (Osaka University)$^{\star}$; Makoto Onizuka (Osaka University); Takahiro Hara (Osaka University, Japan)

• RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection

  Qingsong Wen (Alibaba DAMO Academy)$^{\star}$; Kai He (Alibaba DAMO Academy); Liang Sun (Alibaba Group); Yingying Zhang (Alibaba Group); Min Ke (Alibaba Group); Huan Xu (Alibaba Group)

• On Saving Outliers for Better Clustering over Noisy DataShaoxu Song (Tsinghua University)$^{\star}$; Fei Gao (Tsinghua University); Ruihong Huang (Tsinghua University); Yihan Wang (Tsinghua University)

causal analysis

• Clonos: Consistent Causal Recovery for Highly-Available Streaming Dataflows
  Pedro Silvestre (TU Delft); Marios Fragkoulis (TU Delft)$^{\star}$; Diomidis Spinellis (TU Delft); Asterios Katsifodimos (TU Delft)

heterogeneous

• EquiTensors: Learning Fair Integrations of Heterogeneous Urban Data

  An Yan (University of Washington)$^{\star}$; Bill G Howe (University of Washington)

• Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce

  Xupeng Miao (Peking University)$^{\star}$; Xiaonan Nie (Peking University); Yingxia Shao (BUPT); Zhi Yang (Peking University); Jiawei Jiang (ETH Zurich); Lingxiao Ma (Peking University); Bin Cui (Peking University)

NDSS 2021

accept papers: link

• Evading Voltage-Based Intrusion Detection on Automotive CAN

  Rohit Bhatia (Purdue University); Vireshwar Kumar (Indian Institute of Technology Delhi); Khaled Serag and Z. Berkay Celik (Purdue University); Mathias Payer (EPFL); Dongyan Xu (Purdue University)

• Differential Training: A Generic Framework to Reduce Label Noises for Android Malware Detection

  Jiayun Xu (School of Information Systems, Singapore Management University, Singapore); Yingjiu Li (University of Oregon); Robert H. Deng (School of Information Systems, Singapore Management University, Singapore)

ESEC/FSE 2021 (CCF-A)

• Detecting and Localizing Keyboard Accessibility Failures in Web Applications

  Paul T. Chiou, Ali S. Alotaibi, William G.J. Halfond

• Explaining Mispredictions of ML Models

  Jürgen Cito, Isil Dillig, Vijayaraghavan Murali, Seohyun Kim, Satish Chandra

• Feature Trace Recording

  Paul Maximilian Bittner, Alexander Schultheiß, Thomas Thüm, Timo Kehrer, Jeffrey M. Young, Lukas Linsbauer

• Identifying Bad Software Changes via Multimodal Anomaly Detection for Online Service Systems

  Nengwen Zhao, Junjie Chen, Zhaoyang Yu, Honglin Wang, Jiesong Li, Bin Qiu, Hongyu Xu, Wenchi Zhang, Kaixin Sui, Dan Pei

ICSE 2021 (CCF-A)

• AUTOTRAINER: An Automatic DNN Training Problem Detection and Repair SystemTechnical Track

  Xiaoyu Zhang, Juan Zhai, Shiqing Ma, Chao Shen

• Interpretation-enabled Software Reuse Detection Based on a Multi-Level Birthmark ModelTechnical Track

  Xi Xu, Qinghua Zheng, Zheng Yan, Ming Fan, Ang Jia, Ting Liu

• Semi-supervised Log-based Anomaly Detection via Probabilistic Label EstimationArtifact ReusableTechnical TrackArtifact Available

  Lin Yang, Junjie Chen, Zan Wang, Weijing Wang, Jiajun Jiang, Xuyuan Dong, Wenbin Zhang

ASE 2021 (CCF-A)

ISSRE 2021