AIMC Topic: Artificial Intelligence

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Energy Efficient Execution of POMDP Policies.

IEEE transactions on cybernetics
Recent advances in planning techniques for partially observable Markov decision processes (POMDPs) have focused on online search techniques and offline point-based value iteration. While these techniques allow practitioners to obtain policies for fai...

Multilayer Joint Gait-Pose Manifolds for Human Gait Motion Modeling.

IEEE transactions on cybernetics
We present new multilayer joint gait-pose manifolds (multilayer JGPMs) for complex human gait motion modeling, where three latent variables are defined jointly in a low-dimensional manifold to represent a variety of body configurations. Specifically,...

Classification of lung cancer using ensemble-based feature selection and machine learning methods.

Molecular bioSystems
Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), sq...

Improving propensity score estimators' robustness to model misspecification using super learner.

American journal of epidemiology
The consistency of propensity score (PS) estimators relies on correct specification of the PS model. The PS is frequently estimated using main-effects logistic regression. However, the underlying model assumptions may not hold. Machine learning metho...

Identifying predictive features in drug response using machine learning: opportunities and challenges.

Annual review of pharmacology and toxicology
This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction ...

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Neural networks : the official journal of the International Neural Network Society
The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper....

Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

Artificial intelligence in medicine
BACKGROUND: Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappi...

Applying machine learning techniques for ADME-Tox prediction: a review.

Expert opinion on drug metabolism & toxicology
INTRODUCTION: Pharmacokinetics involves the study of absorption, distribution, metabolism, excretion and toxicity of xenobiotics (ADME-Tox). In this sense, the ADME-Tox profile of a bioactive compound can impact its efficacy and safety. Moreover, eff...

Approximate kernel competitive learning.

Neural networks : the official journal of the International Neural Network Society
Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is ...