Researchers at Imperial College London have developed a new method for coded caching that could improve the delivery of popular video content online. A research paper outlining their findings was pre-published on arXiv, outlining the technique and its performance in...
Researchers at Northwestern University, the University of Bath, and the University of Sydney have developed a new network approach to topic models, machine learning strategies that can discover abstract topics and semantic structures within text documents.
Researchers at New York University have recently devised a new cyber defense technique, which works by adding so-called "chaff bugs," non-exploitable bugs, rather than eliminating existing ones. A pre-print version of their inventive study was uploaded to ArXiv last...
Researchers at ETH Zürich's Autonomous Systems Lab have recently developed a map management process for visual localization systems, specifically designed for operations in outdoor environments involving several vehicles. Their study, presented at this year's...
Several real-world tasks have sparse rewards and this poses challenges for the development of reinforcement learning (RL) algorithms. A solution to this problem is to allow an agent to autonomously create a reward for itself, making rewards denser and more suitable...
Researchers at the Research Center for IT Innovation of Academia Sinica, in Taiwan, have recently developed a novel generative adversarial network (GAN) that has binary neurons at the output layer of the generator. This model, presented in a paper pre-published on...
A team of researchers at North Carolina State University has recently carried out an empirical analysis of the executable status of Python code snippets shared on GitHub. Their study, pre-published on arXiv, also presents Gistable, a new database of executable Python...
Humans have the innate ability to predict the effect of collisions, merely using their common sense. In many cases, humans can even predict the results of similar collisions in situations in which mass, friction, or other factors vary. Could machines also attain a...
Over the past few years, classical convolutional neural networks (cCNNs) have led to remarkable advances in computer vision. Many of these algorithms can now categorize objects in good quality images with high accuracy.
Hybrid systems are systems that exhibit both continuous and discrete dynamic behavior, allowing more flexibility in modeling dynamic phenomena. Hybrid systems modeling languages are widely used for the development of cyber-physical systems, in which control software...