I just finished my first course (fairly rigorous and comprehensive) in machine learning and would like to write a research paper. I'm only an undergrad, so I've never written one before, nor do I have the familiarity with the field to be able to publish. I thought a good way to address both these problems would be to read research papers for several months before I try my hand at a problem. I was hoping for some advice for going about this; would the ideal way be to just sort arXiv by new and read anything that catches my interest? I've heard about Google Scholar but the results seem to be a lot broader and unfocused.
The Conference on Empirical Methods in Natural Language Processing (EMNLP) is one of the top natural language processing conferences in the world. In 2019, it is to be held in Hong Kong, China. There were 1,813 long paper submissions, of which 465 were accepted and 1,063 short paper submissions, of which 218 were accepted. A large number of these papers also published their code ( code download link). To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper.
He described what it would be like for Washington to witness the technology of our time: cars, airplanes, the international space station. You could tell him about the large hadron collider and the theory of relativity, said Urban, and play him music that was recorded 50 years ago. "And this is all before he's seen the internet," said Urban, "the magical wizard rectangle in my pocket that can do a trillion crazy levels of sorcery, like pull open a map that can show where we are on it with a paranormal blue dot." Or let you hold a conversation with someone in Japan, on the other side of the world.
NEW DELHI: Artificial Intelligence (AI) should be leveraged to provide quality solutions at scale across education, health, agriculture, infrastructure and mobility in smart cities, said Niti Aayog CEO Amitabh Kant. A paper titled'National Strategy for Artificial Intelligence', said, "AI for All will aim at enhancing and empowering human capabilities to address the challenges of access, affordability, shortage and inconsistency of skilled expertise." AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making. In the paper, Niti Aayog has decided to focus on five sectors that includes healthcare, agriculture, education, infrastructure and transportation that can benefit from adoption of AI in solving societal needs. Aiming to truly reap benefits of using AI in all and across sectors, the paper has identified barriers that need to be addressed to achieve success in the use of AI.