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 ...

We have now moved into a purpose-built £40M new building at Upper Mountjoy in Durham, which is indicative of the major investment the University is making in Computer Science. The building also ...

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 ...

Abstract: An efficient solution to the large-scale recommender system is to represent users and items as binary hash codes in the Hamming space. Towards this end, existing methods tend to code users ...

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 ...