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LogBERT: Log Anomaly Detection via BERT
Detecting anomalous events in online computer systems is crucial to prot...
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Achieving User-Side Fairness in Contextual Bandits
Personalized recommendation based on multi-arm bandit (MAB) algorithms h...
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Fairness-aware Agnostic Federated Learning
Federated learning is an emerging framework that builds centralized mach...
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Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities
Insider threats, as one type of the most challenging threats in cyberspa...
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Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy
When we enforce differential privacy in machine learning, the utility-pr...
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Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process
The darknet markets are notorious black markets in cyberspace, which inv...
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Achieving Differential Privacy in Vertically Partitioned Multiparty Learning
Preserving differential privacy has been well studied under centralized ...
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Fairness through Equality of Effort
Fair machine learning is receiving an increasing attention in machine le...
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PC-Fairness: A Unified Framework for Measuring Causality-based Fairness
A recent trend of fair machine learning is to define fairness as causali...
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Insider Threat Detection via Hierarchical Neural Temporal Point Processes
Insiders usually cause significant losses to organizations and are hard ...
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Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness
In this paper, we propose a novel Heterogeneous Gaussian Mechanism (HGM)...
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Fairness-aware Classification: Criterion, Convexity, and Bounds
Fairness-aware classification is receiving increasing attention in the m...
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SAFE: A Neural Survival Analysis Model for Fraud Early Detection
Many online platforms have deployed anti-fraud systems to detect and pre...
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FairGAN: Fairness-aware Generative Adversarial Networks
Fairness-aware learning is increasingly important in data mining. Discri...
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On Discrimination Discovery and Removal in Ranked Data using Causal Graph
Predictive models learned from historical data are widely used to help c...
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One-Class Adversarial Nets for Fraud Detection
Many online applications, such as online social networks or knowledge ba...
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Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning
In this paper, we focus on developing a novel mechanism to preserve diff...
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Preserving Differential Privacy in Convolutional Deep Belief Networks
The remarkable development of deep learning in medicine and healthcare d...
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Wikipedia Vandal Early Detection: from User Behavior to User Embedding
Wikipedia is the largest online encyclopedia that allows anyone to edit ...
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Task-specific Word Identification from Short Texts Using a Convolutional Neural Network
Task-specific word identification aims to choose the task-related words ...
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Achieving non-discrimination in prediction
Discrimination-aware classification is receiving an increasing attention...
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