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09/12/2023
GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection
Logs play a crucial role in system monitoring and debugging by recording...
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09/07/2023
Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty
Open Information Extraction (OIE) task aims at extracting structured fac...
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05/30/2023
Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models
Large language models (LLMs) have significantly advanced the field of na...
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05/18/2023
Incremental Causal Graph Learning for Online Unsupervised Root Cause Analysis
The task of root cause analysis (RCA) is to identify the root causes of ...
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02/03/2023
Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization
In this paper, we propose REASON, a novel framework that enables the aut...
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07/29/2021
Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection
Detecting abnormal activities in real-world surveillance videos is an im...
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05/17/2021
Learning Disentangled Representations for Time Series
Time-series representation learning is a fundamental task for time-serie...
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04/08/2021
FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems
We present FACESEC, a framework for fine-grained robustness evaluation o...
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03/26/2021
Unsupervised Document Embedding via Contrastive Augmentation
We present a contrasting learning approach with data augmentation techni...
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03/03/2021
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series
Forecasting on sparse multivariate time series (MTS) aims to model the p...
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10/26/2020
T^2-Net: A Semi-supervised Deep Model for Turbulence Forecasting
Accurate air turbulence forecasting can help airlines avoid hazardous tu...
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08/31/2020
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection
Discrete event sequences are ubiquitous, such as an ordered event series...
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06/19/2020
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning
Outlier detection is an important data mining task with numerous practic...
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05/15/2020
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
Detecting anomalies in dynamic graphs is a vital task, with numerous pra...
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12/18/2019
Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation
Recently, recommender systems have been able to emit substantially impro...
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10/17/2019
Heterogeneous Graph Matching Networks
Information systems have widely been the target of malware attacks. Trad...
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05/09/2019
Adversarial Defense Framework for Graph Neural Network
Graph neural network (GNN), as a powerful representation learning model ...
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12/10/2018
Deep Program Reidentification: A Graph Neural Network Solution
Program or process is an integral part of almost every IT/OT system. Can...
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08/25/2017
Accelerating Dependency Graph Learning from Heterogeneous Categorical Event Streams via Knowledge Transfer
Dependency graph, as a heterogeneous graph representing the intrinsic re...
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08/26/2016