Machine learning for fraud detection in e-Commerce: A research agenda
N Tax, KJ de Vries, M de Jong, N Dosoula… - … Machine Learning for …, 2021 - Springer
Fraud detection and prevention play an important part in ensuring the sustained operation of
any e-commerce business. Machine learning (ML) often plays an important role in these anti …
any e-commerce business. Machine learning (ML) often plays an important role in these anti …
Alignment for advanced machine learning systems
J Taylor, E Yudkowsky, P LaVictoire… - Ethics of artificial …, 2016 - books.google.com
Recent years' progress in artificial intelligence has prompted renewed interest in a question
posed by Russell and Norvig:“What if we succeed?” 1 If and when AI researchers succeed at …
posed by Russell and Norvig:“What if we succeed?” 1 If and when AI researchers succeed at …
Empirical investigation of active learning strategies
Many predictive tasks require labeled data to induce classification models. The data labeling
process may have a high cost. Several strategies have been proposed to optimize the …
process may have a high cost. Several strategies have been proposed to optimize the …
Active learning from imperfect labelers
We study active learning where the labeler can not only return incorrect labels but also
abstain from labeling. We consider different noise and abstention conditions of the labeler …
abstain from labeling. We consider different noise and abstention conditions of the labeler …
A secondary decomposition based hybrid structure with meteorological analysis for deterministic and probabilistic wind speed forecasting
Z Wu, L Xiao - Applied Soft Computing, 2019 - Elsevier
Accurate wind speed forecasting could ensure the reliability and controllability for the wind
power system. In this paper, a new hybrid structure based on meteorological analysis is …
power system. In this paper, a new hybrid structure based on meteorological analysis is …
Similarity-based active learning for image classification under class imbalance
C Zhang, W Tavanapong, G Kijkul… - … conference on data …, 2018 - ieeexplore.ieee.org
Many image classification tasks (eg, medical image classification) have a severe class
imbalance problem. Convolutional neural network (CNN) is currently a state-of-the-art …
imbalance problem. Convolutional neural network (CNN) is currently a state-of-the-art …
Noise-tolerant interactive learning using pairwise comparisons
We study the problem of interactively learning a binary classifier using noisy labeling and
pairwise comparison oracles, where the comparison oracle answers which one in the given …
pairwise comparison oracles, where the comparison oracle answers which one in the given …
Exact recovery of clusters in finite metric spaces using oracle queries
M Bressan, N Cesa-Bianchi… - … on Learning Theory, 2021 - proceedings.mlr.press
We investigate the problem of exact cluster recovery using oracle queries. Previous results
show that clusters in Euclidean spaces that are convex and separated with a margin can be …
show that clusters in Euclidean spaces that are convex and separated with a margin can be …
Active learning for multiple target models
We describe and explore a novel setting of active learning (AL), where there are multiple
target models to be learned simultaneously. In many real applications, the machine learning …
target models to be learned simultaneously. In many real applications, the machine learning …
Sample and computationally efficient learning algorithms under s-concave distributions
MFF Balcan, H Zhang - Advances in Neural Information …, 2017 - proceedings.neurips.cc
We provide new results for noise-tolerant and sample-efficient learning algorithms under $ s
$-concave distributions. The new class of $ s $-concave distributions is a broad and natural …
$-concave distributions. The new class of $ s $-concave distributions is a broad and natural …