AIMC Topic: Algorithms

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Dynamical Channel Pruning by Conditional Accuracy Change for Deep Neural Networks.

IEEE transactions on neural networks and learning systems
Channel pruning is an effective technique that has been widely applied to deep neural network compression. However, many existing methods prune from a pretrained model, thus resulting in repetitious pruning and fine-tuning processes. In this article,...

Random Sketching for Neural Networks With ReLU.

IEEE transactions on neural networks and learning systems
Training neural networks is recently a hot topic in machine learning due to its great success in many applications. Since the neural networks' training usually involves a highly nonconvex optimization problem, it is difficult to design optimization a...

Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification.

IEEE transactions on neural networks and learning systems
Person re-identification (re-ID) favors discriminative representations over unseen shots to recognize identities in disjoint camera views. Effective methods are developed via pair-wise similarity learning to detect a fixed set of region features, whi...

Quaternion-Valued Twin-Multistate Hopfield Neural Networks With Dual Connections.

IEEE transactions on neural networks and learning systems
Dual connections (DCs) utilize the noncommutativity of quaternions and improve the noise tolerance of quaternion Hopfield neural networks (QHNNs). In this article, we introduce DCs to twin-multistate QHNNs. We conduct computer simulations to investig...

Adaptive Neural Control for a Class of Nonlinear Multiagent Systems.

IEEE transactions on neural networks and learning systems
This article studies the adaptive neural controller design for a class of uncertain multiagent systems described by ordinary differential equations (ODEs) and beams. Three kinds of agent models are considered in this study, i.e., beams, nonlinear ODE...

Robust Environmental Sound Recognition With Sparse Key-Point Encoding and Efficient Multispike Learning.

IEEE transactions on neural networks and learning systems
The capability for environmental sound recognition (ESR) can determine the fitness of individuals in a way to avoid dangers or pursue opportunities when critical sound events occur. It still remains mysterious about the fundamental principles of biol...

Artificial Intelligence in the assessment of diabetic retinopathy from fundus photographs.

Seminars in ophthalmology
: Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 million individuals. Consequently, an unprecedented number of patients will be at risk for vision loss from diabetic eye disease. This demand will almost ce...

Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Molecular diversity
Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification models to predict bioactivities of CysLT1 receptor antagonists. We built a dataset with 503 CysLT1 re...

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer.

International journal of radiation oncology, biology, physics
Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language p...

Application of a novel machine learning framework for predicting non-metastatic prostate cancer-specific mortality in men using the Surveillance, Epidemiology, and End Results (SEER) database.

The Lancet. Digital health
BACKGROUND: Accurate prognostication is crucial in treatment decisions made for men diagnosed with non-metastatic prostate cancer. Current models rely on prespecified variables, which limits their performance. We aimed to investigate a novel machine ...