AIMC Topic: Machine Learning

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EISA-Score: Element Interactive Surface Area Score for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling
Molecular surface representations have been advertised as a great tool to study protein structure and functions, including protein-ligand binding affinity modeling. However, the conventional surface-area-based methods fail to deliver a competitive pe...

Deep Ensemble Fake News Detection Model Using Sequential Deep Learning Technique.

Sensors (Basel, Switzerland)
Recently, fake news has been widely spread through the Internet due to the increased use of social media for communication. Fake news has become a significant concern due to its harmful impact on individual attitudes and the community's behavior. Res...

Recent Advances in Large Margin Learning.

IEEE transactions on pattern analysis and machine intelligence
This paper serves as a survey of recent advances in large margin training and its theoretical foundations, mostly for (nonlinear) deep neural networks (DNNs) that are probably the most prominent machine learning models for large-scale data in the com...

Learning Across Tasks for Zero-Shot Domain Adaptation From a Single Source Domain.

IEEE transactions on pattern analysis and machine intelligence
Domain adaptation techniques learn transferable knowledge from a source domain to a target domain and train models that generalize well in the target domain. Unfortunately, a majority of the existing techniques are only applicable to scenarios that t...

Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation Using Structurally Regularized Deep Clustering.

IEEE transactions on pattern analysis and machine intelligence
Unsupervised domain adaptation (UDA) is to learn classification models that make predictions for unlabeled data on a target domain, given labeled data on a source domain whose distribution diverges from the target one. Mainstream UDA methods strive t...

Poisoning Attack Against Estimating From Pairwise Comparisons.

IEEE transactions on pattern analysis and machine intelligence
As pairwise ranking becomes broadly employed for elections, sports competitions, recommendation, information retrieval and so on, attackers have strong motivation and incentives to manipulate or disrupt the ranking list. They could inject malicious c...

A Concise Yet Effective Model for Non-Aligned Incomplete Multi-View and Missing Multi-Label Learning.

IEEE transactions on pattern analysis and machine intelligence
In reality, learning from multi-view multi-label data inevitably confronts three challenges: missing labels, incomplete views, and non-aligned views. Existing methods mainly concern the first two and commonly need multiple assumptions to attack them,...

Importance Weight Estimation and Generalization in Domain Adaptation Under Label Shift.

IEEE transactions on pattern analysis and machine intelligence
We study generalization under labeled shift for categorical and general normed label spaces. We propose a series of methods to estimate the importance weights from labeled source to unlabeled target domain and provide confidence bounds for these esti...

Minimized Computations of Deep Learning Technique for Early Diagnosis of Diabetic Retinopathy Using IoT-Based Medical Devices.

Computational intelligence and neuroscience
Diabetes mellitus is the main cause of diabetic retinopathy, the most common cause of blindness worldwide. In order to slow down or prevent vision loss and degeneration, early detection and treatment are essential. For the purpose of detecting and cl...

Development and External Validation of a Machine Learning Model for the Early Prediction of Doses of Harmful Intracranial Pressure in Patients with Severe Traumatic Brain Injury.

Journal of neurotrauma
Treatment and prevention of elevated intracranial pressure (ICP) is crucial in patients with severe traumatic brain injury (TBI). Elevated ICP is associated with secondary brain injury, and both intensity and duration of an episode of intracranial hy...