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LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision
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LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision

Thorsten Wittkopp
Philipp Wiesner
Dominik Scheinert
Alexander Acker
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Papers citing "LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision"

8 / 8 papers shown
Title
A2Log: Attentive Augmented Log Anomaly Detection
A2Log: Attentive Augmented Log Anomaly Detection
Thorsten Wittkopp
Alexander Acker
S. Nedelkoski
Jasmin Bogatinovski
Dominik Scheinert
Wu Fan
O. Kao
56
22
0
20 Sep 2021
Decentralized Federated Learning Preserves Model and Data Privacy
Decentralized Federated Learning Preserves Model and Data Privacy
Thorsten Wittkopp
Alexander Acker
51
20
0
01 Feb 2021
Self-Attentive Classification-Based Anomaly Detection in Unstructured Logs
Self-Attentive Classification-Based Anomaly Detection in Unstructured Logs
S. Nedelkoski
Jasmin Bogatinovski
Alexander Acker
Jorge Cardoso
O. Kao
64
129
0
21 Aug 2020
Text Classification Algorithms: A Survey
Text Classification Algorithms: A Survey
Kamran Kowsari
K. Meimandi
Mojtaba Heidarysafa
Sanjana Mendu
Laura E. Barnes
Donald E. Brown
74
1,298
0
17 Apr 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
94,891
0
11 Oct 2018
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
713
131,652
0
12 Jun 2017
Data Programming: Creating Large Training Sets, Quickly
Data Programming: Creating Large Training Sets, Quickly
Alexander Ratner
Christopher De Sa
Sen Wu
Daniel Selsam
Christopher Ré
185
716
0
25 May 2016
A bagging SVM to learn from positive and unlabeled examples
A bagging SVM to learn from positive and unlabeled examples
F. Mordelet
Jean-Philippe Vert
105
288
0
05 Oct 2010

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