Companies are getting hacked every single day.” If the NSA is perturbed by the rise in cyberattacks, which it apparently is, ...

Abstract: Traditional operations, e.g. graph edit distance (GED), are no longer suitable for processing the massive quantities of graph-structured data now available, due to their irregular structures ...

Quantum computers, systems that process information leveraging quantum mechanical effects, could soon outperform classical computers on some complex computational problems. These computers rely on ...

ABSTRACT: A new nano-based architectural design of multiple-stream convolutional homeomorphic error-control coding will be conducted, and a corresponding hierarchical implementation of important class ...

Quantum computing has the potential to revolutionize a wide range of scientific fields, including cryptography, drug discovery, climate modeling, finance, and artificial intelligence. Unlike classical ...

Numerous microarchitectural optimizations unlocked tremendous processing power for deep neural networks that in turn fueled the AI revolution. With the exhaustion of such optimizations, the growth of ...

Abstract: Hamming code and Extended Hamming code are linear error-correcting codes used for detecting and correcting errors in digital data transmission. They help in maintaining data integrity and ...

Directed greybox fuzzing (DGF) is an effective method to detect vulnerabilities of the specified target code. Nevertheless, there are three main issues in the existing DGFs. First, the target ...

Under-representation of women in computing persists, despite energetic reform efforts. To guide strategies for change, we need deeper insight into the changing dynamics of gender bias. Analyzing ...

It has been proposed that machine learning techniques can benefit from symbolic representations and reasoning systems. We describe a method in which the two can be combined in a natural and direct way ...

Deep neural networks (DNN) are becoming fundamental learning devices for extracting information from data in a variety of real-world applications and in natural and social sciences. The learning ...

We present a simple yet effective deep learning framework to create the hash-like binary codes for fast image retrieval. We add a latent-attribute layer in the deep CNN to simultaneously learn domain ...