【机器学习】2021异常检测顶会论文一览
本文整理了 2021 年AAAI、ICML等顶会收录的异常检测领域的论文
paper | source | author |
---|---|---|
LREN: Low-Rank Embedded Network for Sample-Free Hyperspectral Anomaly Detection | AAAI | Kai Jiang, Weiying Xie, Jie Lei, Tao Jiang, Yunsong Li |
GAN Ensemble for Anomaly Detection | AAAI | Xiaohui Chen, Xu Han, Liping Liu |
Anomaly Attribution with Likelihood Compensation | AAAI | Tsuyoshi Ide, Amit Dhurandhar, Jiri Navratil, Moninder Singh, Naoki Abe |
Regularizing Attention Networks for Anomaly Detection in Visual Question Answering | AAAI | Regularizing Attention Networks for Anomaly Detection in Visual Question Answering |
Appearance-Motion Memory Consistency Network for Video Anomaly Detection | AAAI | Ruichu Cai, Hao Zhang, Wen Liu, Shenghua Gao, Zhifeng Hao |
Learning Semantic Context from Normal Samples for Unsupervised Anomaly Detection | AAAI | Xudong Yan, Huaidong Zhang, Xuemiao Xu, Xiaowei Hu, Pheng-Ann Heng |
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series | AAAI | Ailin Deng, Bryan Hooi |
Time Series Anomaly Detection with Multiresolution Ensemble Decoding | AAAI | Lifeng Shen, Zhongzhong Yu, Qianli Ma, James Tin-Yau Kwok |
Window Loss for Abnormal Finding Classification and Localization in X-Ray Image with Point-Base Annotat | AAAI | Xinyu Zhang, Yirui Wang, Chi Tung Cheng, Le Lu, Adam P Harrison, Jing Xiao, ChienHung Liao, Shun Miao |
Graph Neural Network to Dilute Outliers for Refactoring Monolith Application | AAAI | Utkarsh Desai, Sambaran Bandyopadhyay, Srikanth Tamilselvam |
Accelerated Combinatorial Search for Outlier Detection with Provable Bound on Sub-Optimality | AAAI | Guihong Wan, Haim Schweitzer |
Neighborhood Consensus Networks for Unsupervised Multi-View Outlier Detection | AAAI | Li Cheng, Yijie Wang, Xinwang Liu |
Outlier Impact Characterization for Time Series Data | AAAI | Jianbo Li, Lecheng Zheng, Yada Zhu, Jingrui He |
Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise | ICML | Vivek Farias (MIT) , Andrew Li (Carnegie Mellon University) ,Tianyi Peng (MIT) |
Transfer-Based Semantic Anomaly Detection | ICML | Lucas Deecke (University of Edinburgh) , Lukas Ruff (Aignostics) , Robert Vandermeulen (TU Berlin) , Hakan Bilen (University of Edinburgh) |
Neural Transformation Learning for Deep Anomaly Detection Beyond Images | ICML | Chen Qiu (TU Kaiserslautern/Bosch Center for Artificial Intelligence) , Timo Pfrommer (Bosch Center for Artificial Intelligence) , Marius Kloft (TU Kaiserslautern) , Stephan Mandt (University of California, Irivine) , Maja Rudolph (BCAI) |
Event Outlier Detection in Continuous Time | ICML | Siqi Liu (Borealis AI) , Milos Hauskrecht (University of Pittsburgh) |
Outlier-Robust Optimal Transport | ICML | Debarghya Mukherjee (University of Michigan) , Aritra Guha (Duke University) , Justin Solomon (MIT) , Yuekai Sun (University of Michigan) , Mikhail Yurochkin (IBM Research AI) |
DORO: Distributional and Outlier Robust Optimization | ICML | Runtian Zhai (Carnegie Mellon University) , Chen Dan (Carnegie Mellon University) , Zico Kolter (Carnegie Mellon University / Bosch Center for AI) , Pradeep Ravikumar (Carnegie Mellon University) |
SSD: A Unified Framework for Self-Supervised Outlier Detection | ICLR | Vikash Sehwag, Mung Chiang, Prateek Mittal |
DATE: Detecting Anomalies in Text Via Self-Supervision of Transformers | NAACL | Andrei Manolache, Florin Brad, Elena Burceanu |
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