In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …

With the rapid development of deep learning techniques, deep convolutional neural
networks (DCNNs) have become more important for object detection. Compared with …

Nuclear fusion power delivered by magnetic-confinement tokamak reactors holds the
promise of sustainable and clean energy. The avoidance of large-scale plasma instabilities …

Stock market prediction is one of the most challenging problems which has been distressing
both researchers and financial analysts for more than half a century. To tackle this problem …

Membership Inference Attack (MIA) determines the presence of a record in a machine
learning model's training data by querying the model. Prior work has shown that the attack is …

This paper presents a novel method, termed Bridge to Answer, to infer correct answers for
questions about a given video by leveraging adequate graph interactions of heterogeneous …

This is the first comprehensive introduction to Support Vector Machines (SVMs), a new
generation learning system based on recent advances in statistical learning theory. SVMs …

This important text and reference for researchers and students in machine learning, game
theory, statistics and information theory offers a comprehensive treatment of the problem of …

Different evaluation measures assess different characteristics of machine learning
algorithms. The empirical evaluation of algorithms and classifiers is a matter of on-going …

We present a family of margin based online learning algorithms for various prediction tasks.
In particular we derive and analyze algorithms for binary and multiclass categorization …