IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models (LMs) taken from Natural Language Processing (NLP). These LMs reach for new prediction frontiers at low inference costs. Here, we ...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we p...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
One of the most prominent attributes of Neural Networks (NNs) constitutes their capability of learning to extract robust and descriptive features from high dimensional data, like images. Hence, such an ability renders their exploitation as feature ex...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
In this paper, we consider how to incorporate psychophysical measurements of human visual perception into the loss function of a deep neural network being trained for a recognition task, under the assumption that such information can reduce errors. A...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
A unique cognitive capability of humans consists in their ability to acquire new knowledge and skills from a sequence of experiences. Meanwhile, artificial intelligence systems are good at learning only the last given task without being able to remem...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
In this work, we propose a novel Convolutional Neural Network (CNN) architecture for the joint detection and matching of feature points in images acquired by different sensors using a single forward pass. The resulting feature detector is tightly cou...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Support vector machines (SVM) have drawn wide attention for the last two decades due to its extensive applications, so a vast body of work has developed optimization algorithms to solve SVM with various soft-margin losses. To distinguish all, in this...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
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...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
It is appealing but challenging to achieve real-time deep neural network (DNN) inference on mobile devices, because even the powerful modern mobile devices are considered as "resource-constrained" when executing large-scale DNNs. It necessitates the ...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Action segmentation is the task of predicting the actions for each frame of a video. As obtaining the full annotation of videos for action segmentation is expensive, weakly supervised approaches that can learn only from transcripts are appealing. In ...