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Machine Learning and Knowledge Discovery in Databases: Research Track

Overview of attention for book
Cover of 'Machine Learning and Knowledge Discovery in Databases: Research Track'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes
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    Chapter 2 Real: A Representative Error-Driven Approach for Active Learning
  4. Altmetric Badge
    Chapter 3 Knowledge-Driven Active Learning
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    Chapter 4 ActiveGLAE: A Benchmark for Deep Active Learning with Transformers
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    Chapter 5 DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification
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    Chapter 6 Quantifying Robustness to Adversarial Word Substitutions
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    Chapter 7 Enhancing Adversarial Training via Reweighting Optimization Trajectory
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    Chapter 8 Adversarial Imitation Learning with Controllable Rewards for Text Generation
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    Chapter 9 Towards Minimising Perturbation Rate for Adversarial Machine Learning with Pruning
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    Chapter 10 Adversarial Sample Detection Through Neural Network Transport Dynamics
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    Chapter 11 CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection
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    Chapter 12 Graph-Level Anomaly Detection via Hierarchical Memory Networks
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    Chapter 13 Semi-supervised Learning from Active Noisy Soft Labels for Anomaly Detection
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    Chapter 14 Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal
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    Chapter 15 DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection
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    Chapter 16 Marvolo: Programmatic Data Augmentation for Deep Malware Detection
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    Chapter 17 A Transductive Forest for Anomaly Detection with Few Labels
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    Chapter 18 Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction
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    Chapter 19 SpotGAN: A Reverse-Transformer GAN Generates Scaffold-Constrained Molecules with Property Optimization
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    Chapter 20 Spatio-Temporal Pyramid Networks for Traffic Forecasting
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    Chapter 21 A Passage Retrieval Transformer-Based Re-Ranking Model for Truthful Consumer Health Search
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    Chapter 22 KESHEM: Knowledge Enabled Short Health Misinformation Detection Framework
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    Chapter 23 Dynamic Thresholding for Accurate Crack Segmentation Using Multi-objective Optimization
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    Chapter 24 Co-supervised Pre-training of Pocket and Ligand
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    Chapter 25 Decompose, Then Reconstruct: A Framework of Network Structures for Click-Through Rate Prediction
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    Chapter 26 DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data
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    Chapter 28 Cooperative Bayesian Optimization for Imperfect Agents
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    Chapter 29 Leveraging Variational Autoencoders for Multiple Data Imputation
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    Chapter 30 A New Framework for Classifying Probability Density Functions
  31. Altmetric Badge
    Chapter 31 Learning Conditional Instrumental Variable Representation for Causal Effect Estimation
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    Chapter 32 A KNN-Based Non-Parametric Conditional Independence Test for Mixed Data and Application in Causal Discovery
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    Chapter 33 PEACE: Cross-Platform Hate Speech Detection - A Causality-Guided Framework
  34. Altmetric Badge
    Chapter 34 Estimating Treatment Effects Under Heterogeneous Interference
  35. Altmetric Badge
    Chapter 35 Regularization for Uplift Regression
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    Chapter 36 Powered Dirichlet Process - Controlling the “Rich-Get-Richer” Assumption in Bayesian Clustering
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    Chapter 37 Contrastive Hierarchical Clustering
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    Chapter 38 Contrastive Learning with Cluster-Preserving Augmentation for Attributed Graph Clustering
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    Chapter 39 k-SubMix: Common Subspace Clustering on Mixed-Type Data
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    Chapter 40 Transformer-Based Contrastive Multi-view Clustering via Ensembles
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    Chapter 41 A Deep Dynamic Latent Block Model for the Co-Clustering of Zero-Inflated Data Matrices
  42. Altmetric Badge
    Chapter 42 cuSLINK: Single-Linkage Agglomerative Clustering on the GPU
  43. Altmetric Badge
    Chapter 43 Socially Fair Center-Based and Linear Subspace Clustering
  44. Altmetric Badge
    Chapter 44 Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations
Attention for Chapter 11: CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection
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About this Attention Score

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Chapter title
CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-Level Anomaly Detection
Chapter number 11
Book title
Machine Learning and Knowledge Discovery in Databases: Research Track
Published in
arXiv, January 2023
DOI 10.1007/978-3-031-43412-9_11
Book ISBNs
978-3-03-143411-2, 978-3-03-143412-9
Authors

Li, Jindong, Xing, Qianli, Wang, Qi, Chang, Yi, Jindong Li, Qianli Xing, Qi Wang, Yi Chang

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 May 2024.
All research outputs
#17,068,427
of 25,859,234 outputs
Outputs from arXiv
#316,806
of 950,960 outputs
Outputs of similar age
#258,010
of 480,803 outputs
Outputs of similar age from arXiv
#9,546
of 29,397 outputs
Altmetric has tracked 25,859,234 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 950,960 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 480,803 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29,397 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.