Week Ending 4.5.2020
RESEARCH WATCH: 4.5.2020
Over the past week, 85 new papers were published in "Computer Science - Artificial Intelligence".
The paper discussed most in the news over the past week was by a team at Google: "Learning to Walk in the Real World with Minimal Human Effort" by Sehoon Ha et al (Feb 2020), which was referenced 51 times, including in the article Exploring Nature-Inspired Robot Agility in Google AI Blog. The paper author, Jie Tan (Google), was quoted saying "Now is still the early days of research. Next, we plan to test our learning system on a wide range of robots and in a more diverse set of environments". The paper got social media traction with 138 shares. The investigators develop a system for learning legged locomotion policies with deep RL in the real world with minimal human effort. A user, @popular_ML, tweeted "The most popular ArXiv tweet in the last 24h", while @hafiz_coolman said "You can download the article from this link. On the right, there is PDF in hyperlink. It is nice to know what is the challenges and technique used".
The paper shared the most on social media this week is by a team at Microsoft: "Suphx: Mastering Mahjong with Deep Reinforcement Learning" by Junjie Li et al (Mar 2020) with 213 shares. @hardmaru (hardmaru) tweeted "Mastering Mahjong with Deep Reinforcement Learning 🀄 Their system “rated above 99.99% of all the officially ranked human players. First time that a computer program outperforms most top human players in Mahjong.” Sure, but can it beat my grandmother?".
The most influential Twitter user discussing papers is Bob E. Hayes who shared "The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence" by Gary Marcus (Feb 2020) and said: "The Next Decade in AI: Four Steps Towards Robust #ArtificialIntelligence | #deeplearning".
This week was very active for "Computer Science - Computer Vision and Pattern Recognition", with 317 new papers.
The paper discussed most in the news over the past week was "Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis" by Ophir Gozes et al (Mar 2020), which was referenced 22 times, including in the article Healthcare Centers are Turning to AI to Combat Covid-19 in Analytics Insight. The paper author, Dr Bernheim, was quoted saying "Protocols are in place following CT scanning of a known or suspected COVID-19 patient to ensure that risk of transmission to future patients is minimized." The paper got social media traction with 53 shares. A Twitter user, @AtoAndyKing, posted "But (exactly) the same figure for the Chinese only experiment I think? My concerns are more that (1) these are all hospitalised patients, so presumably severe symptoms and easy to detect using other means, (2) is it realistic to use CT as a diagnostic tool for #COVID19?".
Leading researcher Abhinav Gupta (Carnegie Mellon University) published "Articulation-aware Canonical Surface Mapping".
The paper shared the most on social media this week is by a team at Google: "Learning to See Through Obstructions" by Yu-Lun Liu et al (Apr 2020) with 492 shares. @aquigley (aquigley) tweeted "One day this will be built into cameras and people will be impressed for a day, and then just wonder why cameras didn’t always just work this way".
The most influential Twitter user discussing papers is Bob E. Hayes who shared "The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence" by Gary Marcus (Feb 2020)
This week was active for "Computer Science - Computers and Society", with 31 new papers.
The paper discussed most in the news over the past week was by a team at Boston University: "Anonymous Collocation Discovery:Taming the Coronavirus While Preserving Privacy" by Ran Canetti et al (Mar 2020), which was referenced 6 times, including in the article Researchers propose method to track coronavirus through smartphones while protecting privacy in ZDNet. The paper author, Ari Trachtenberg (Boston University), was quoted saying "When a person is tested positive for COVID-19, the person could choose (through the administrating medical professional) to voluntarily share their list of random numbers -- either their own generated numbers or the numbers that the app observed". The paper got social media traction with 40 shares. A user, @ikubjas, tweeted "Anonymous Collocation Discovery: Taming the Coronavirus While Preserving Privacy. Idea is to broadcast random tokens and when diagnosed, these tokens are broadcast. Everyone can then compare the received tokens to see if a "contagious" token is stored".
The paper shared the most on social media this week is "The Covid19Impact Survey: Assessing the Pulse of the COVID-19 Pandemic in Spain via 24 questions" by Nuria Oliver et al (Apr 2020) with 164 shares. The researchers describe the results of analyzing a large - scale survey, called the Covid19Impact survey, to assess citizens feedback on four areas related to the COVID-19 pandemic in Spain : social contact behavior, financial impact, working situation and health status. @jfabregab (Jordi Fabrega) tweeted "Over 18% reported having had close contact with someone infected by the coronavirus. - Respondents left their homes for: supermarkets and pharmacy (47.9%), going to work (31.9%) - 19.8% had lost a significant part of their savings, and 6.5% had lost their job".
The most influential Twitter user discussing papers is Bob E. Hayes who shared "The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence" by Gary Marcus (Feb 2020)
This week was active for "Computer Science - Human-Computer Interaction", with 31 new papers.
This week was very active for "Computer Science - Learning", with 357 new papers.
The paper discussed most in the news over the past week was by a team at Google: "Learning to Walk in the Real World with Minimal Human Effort" by Sehoon Ha et al (Feb 2020)
Leading researcher Sergey Levine (University of California, Berkeley) published "Learning Agile Robotic Locomotion Skills by Imitating Animals", which had 25 shares over the past 2 days. @fdellaert tweeted "Awesome work!". This paper was also shared the most on social media with 146 tweets. @fdellaert (Frank Dellaert) tweeted "Awesome work!".
This week was active for "Computer Science - Multiagent Systems", with 23 new papers.
The paper discussed most in the news over the past week was by a team at The University of Sydney: "Modelling transmission and control of the COVID-19 pandemic in Australia" by Sheryl L. Chang et al (Mar 2020), which was referenced 46 times, including in the article Australians must continue to stay home, or 'flattening the curve' could turn into this in ABC Online. The paper author, Mikhail Prokopenko (The University of Sydney), was quoted saying "If we want to control the spread of COVID-19 – rather than letting the disease control us – at least eighty per cent of the Australian population must comply with strict social distancing measures for at least four months". The paper also got the most social media traction with 575 shares. The investigators develop an agent - based model for a fine - grained computational simulation of the ongoing COVID-19 pandemic in Australia. On Twitter, @arthaey observed "This paper models 80-90% social distancing compliance is needed, & only works while we KEEP doing it, until a vaccine: (blue line is 70% compliance, red 80%, yellow 90%; spikes later are when social distancing is lifted)".
Over the past week, 34 new papers were published in "Computer Science - Neural and Evolutionary Computing".
This week was very active for "Computer Science - Robotics", with 67 new papers.
The paper discussed most in the news over the past week was by a team at Google: "Learning to Walk in the Real World with Minimal Human Effort" by Sehoon Ha et al (Feb 2020)
Leading researcher Sergey Levine (University of California, Berkeley) published "Learning Agile Robotic Locomotion Skills by Imitating Animals"