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...
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...
Physicians currently spend a lot of time writing notes about patients and inserting them into electronic health record (EHR) systems. According to a 2016 study, doctors spend approximately two hours on administrative work for every hour spent with a patient. Thanks to...
Brian Mitchell and Linda Petzold, two researchers at the University of California, have recently applied model-free deep reinforcement learning to models of neural dynamics, achieving very promising results.
Researchers at Northwestern University, Microsoft Research India, and the Indian Institute of Technology Kharagpur have recently developed a model to predict whether a book will become a bestseller on Amazon within 15 days of its publication. Their model, outlined in...
Researchers at the Polish-Japanese Academy of Information Technology and Warsaw University of Technology have developed a deep alignment network (DAN) model to classify and visualize emotions. Their method was found to outperform state-of-the-art emotion...
Every day, millions of articles are published on social media and other platforms, receiving a vast amounts of clicks and shares from users navigating the web. Many of these articles contain useful information that, if extracted, could be used to compile knowledge...