Search Results - "Erfani, Sarah M."

High Intrinsic Dimensionality Facilitates Adversarial Attack: Theoretical Evidence by Amsaleg, Laurent, Bailey, James, Barbe, Amelie, Erfani, Sarah M., Furon, Teddy, Houle, Michael E., Radovanovic, Milos, Nguyen, Xuan Vinh

“…Machine learning systems are vulnerable to adversarial attack. By applying to the input object a small, carefully-designed perturbation, a classifier can be…”
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LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection by Xia, Siqi, Rajasegarar, Sutharshan, Pan, Lei, Leckie, Christopher, Erfani, Sarah M., Chan, Jeffrey

“…Anomaly detection in graphs is increasingly used to reveal fraud, fakes, security attacks and unusual behaviours in networks, such as social networks,…”
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High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning by Erfani, Sarah M., Rajasegarar, Sutharshan, Karunasekera, Shanika, Leckie, Christopher

“…High-dimensional problem domains pose significant challenges for anomaly detection. The presence of irrelevant features can conceal the presence of anomalies…”
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Hybrid Quantum-Classical Generative Adversarial Network for High-Resolution Image Generation by Tsang, Shu Lok, West, Maxwell T., Erfani, Sarah M., Usman, Muhammad

“…Quantum machine learning (QML) has received increasing attention due to its potential to outperform classical machine learning methods in problems, such as…”
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Adversarial Coreset Selection for Efficient Robust Training by Dolatabadi, Hadi M., Erfani, Sarah M., Leckie, Christopher

“…It has been shown that neural networks are vulnerable to adversarial attacks: adding well-crafted, imperceptible perturbations to their input can modify their…”
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Efficient Unsupervised Parameter Estimation for One-Class Support Vector Machines by Ghafoori, Zahra, Erfani, Sarah M., Rajasegarar, Sutharshan, Bezdek, James C., Karunasekera, Shanika, Leckie, Christopher

“…One-class support vector machines (OCSVMs) are very effective for semisupervised anomaly detection. However, their performance strongly depends on the settings…”
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LN-SNE: Log-Normal Distributed Stochastic Neighbor Embedding for Anomaly Detection by Ghafoori, Zahra, Erfani, Sarah M., Bezdek, James C., Karunasekera, Shanika, Leckie, Christopher

“…We present a new unsupervised dimensionality reduction technique, called LN-SNE, for anomaly detection. LN-SNE generates a parametric embedding by means of…”
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Online cluster validity indices for performance monitoring of streaming data clustering by Moshtaghi, Masud, Bezdek, James C., Erfani, Sarah M., Leckie, Christopher, Bailey, James

“…Cluster analysis is used to explore structure in unlabeled batch data sets in a wide range of applications. An important part of cluster analysis is validating…”
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Towards quantum enhanced adversarial robustness in machine learning by West, Maxwell T., Tsang, Shu-Lok, Low, Jia S., Hill, Charles D., Leckie, Christopher, Hollenberg, Lloyd C. L., Erfani, Sarah M., Usman, Muhammad

“…Machine learning algorithms are powerful tools for data-driven tasks such as image classification and feature detection. However, their vulnerability to…”
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Benchmarking adversarially robust quantum machine learning at scale by West, Maxwell T., Erfani, Sarah M., Leckie, Christopher, Sevior, Martin, Hollenberg, Lloyd C. L., Usman, Muhammad

“…Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology, and industry. Despite their…”
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Distributed Nonlinear Model Predictive Control and Reinforcement Learning by Saeed, Ifrah, Alpcan, Tansu, Erfani, Sarah M., Yilmaz, M. Berkay

“…Coordinating two or more dynamic systems such as autonomous vehicles or satellites in a distributed manner poses an important research challenge. Multiple…”
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Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms by Fahiman, Fateme, Bezdek, James C., Erfani, Sarah M., Palaniswami, Marimuthu, Leckie, Christopher

“…The existence of large volumes of time series data in many applications has motivated data miners to investigate specialized methods for mining time series…”
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Mining Rare Recurring Events in Network Traffic using Second Order Contrast Patterns by Alipourchavary, Elaheh, Erfani, Sarah M., Leckie, Christopher

“…Data mining techniques such as contrast pattern mining provide a promising approach to detecting and characterizing changes in network traffic. However, a…”
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Neural Architecture Search via Combinatorial Multi-Armed Bandit by Huang, Hanxun, Ma, Xingjun, Erfani, Sarah M., Bailey, James

“…Neural Architecture Search (NAS) has gained significant popularity as an effective tool for designing high performance deep neural networks (DNNs). NAS can be…”
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Deep Learning and One-class SVM based Anomalous Crowd Detection by Yang, Meng, Rajasegarar, Sutharshan, Erfani, Sarah M., Leckie, Christopher

“…Anomalous event detection in videos is an important and challenging task. This paper proposes a deep representation approach to the problem, which extracts and…”
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Support vector machines resilient against training data integrity attacks by Weerasinghe, Sandamal, Erfani, Sarah M., Alpcan, Tansu, Leckie, Christopher

“…•Support Vector Machines are designed to withstand noise in data.•But they are vulnerable to integrity attacks by adversaries.•Projecting data to lower…”
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Local Intrinsic Dimensionality Signals Adversarial Perturbations by Weerasinghe, Sandamal, Abraham, Tamas, Alpcan, Tansu, Erfani, Sarah M., Leckie, Christopher, Rubinstein, Benjamin I. P.

“…The vulnerability of machine learning models to adversarial perturbations has motivated a significant amount of research under the broad umbrella of…”
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Defending Support Vector Machines Against Data Poisoning Attacks by Weerasinghe, Sandamal, Alpcan, Tansu, Erfani, Sarah M., Leckie, Christopher

“…Support Vector Machines (SVMs) are vulnerable to targeted training data manipulations such as poisoning attacks and label flips. By carefully manipulating a…”
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Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections by Rathore, Punit, Bezdek, James C., Erfani, Sarah M., Rajasegarar, Sutharshan, Palaniswami, Marimuthu

“…Random projection is a popular method for dimensionality reduction due to its simplicity and efficiency. In the past few years, random projection and fuzzy…”
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Robust and Accurate Short-Term Load Forecasting: A Cluster Oriented Ensemble Learning Approach by Fahiman, Fateme, Erfani, Sarah M., Leckie, Christopher

“…One of the most critical tasks for operating a power system is load forecasting in order to keep balance between demand and supply and for planning…”
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