Week Ending 06.30.19
RESEARCH WATCH: 06.30.19
Over the past week, 947 new papers were published in "Computer Science".
The paper discussed most in the news over the past week was "Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts"by Joseph Bullock et al (Jun 2019), which was referenced 101 times, including in the article Do we need new human rights in the era of fake information? in Medium.com. The paper got social media traction with 98 shares. A Twitter user, @naumenko_roman, said "Some savings in budget thanks to the cloud. "The language model was trained in under 13 hours on NVIDIA K80 GPUs, costing as little as $7.80 on AWS spot instances."", while @lolitataub commented "AI speech generator anyone? ... "matchethe style and cadence of real UN speeches roughly 90% of the time."".
Leading researcher Yoshua Bengio (Université de Montréal) published "Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives" The authors propose a policy design that decomposes into primitives, similarly to hierarchical reinforcement learning, but without a high - level meta - policy. @gastronomy tweeted "> Reinforcement learning agents that operate in diverse and complex environments can benefit from the structured decompositio".
The paper shared the most on social media this week is by a team at Google: "Learning Data Augmentation Strategies for Object Detection" by Barret Zoph et al (Jun 2019) with 372 shares. The authors study the impact of data augmentation on object detection. @miguelgfierro (Miguel González-Fierro) tweeted "Data augmentation is going to be key in the following years, this is a very nice advance".
This week was active for "Computer Science - Artificial Intelligence", with 98 new papers.
The paper discussed most in the news over the past week was "Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts"by Joseph Bullock et al (Jun 2019)
Leading researcher Yoshua Bengio (Université de Montréal) published "Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives"
The paper shared the most on social media this week is by a team at DeepMind: "Regularized Hierarchical Policies for Compositional Transfer in Robotics" by Markus Wulfmeier et al (Jun 2019) with 215 shares. @DeepMindAI (DeepMind) tweeted "Data-efficiency is one of the principal challenges for applying reinforcement learning on physical systems. We use hierarchical models to strengthen transfer while mitigating negative interference - saving weeks of training time for physical robots".
Over the past week, 168 new papers were published in "Computer Science - Computer Vision and Pattern Recognition".
The paper discussed most in the news over the past week was by a team at University at Albany: "Hiding Faces in Plain Sight: Disrupting AI Face Synthesis with Adversarial Perturbations" by Yuezun Li et al (Jun 2019), which was referenced 33 times, including in the article Detecting deepfakes by looking closely reveals a way to protect against them in AfricanDiasporaLeaders.com. The paper got social media traction with 11 shares. The authors develop technologies to defend individuals from becoming victims of recent AI synthesized fake videos by sabotaging would - be training data.
Leading researcher Devi Parikh (Georgia Institute of Technology) published "RUBi: Reducing Unimodal Biases in Visual Question Answering".
The paper shared the most on social media this week is by a team at Google: "Learning Data Augmentation Strategies for Object Detection" by Barret Zoph et al (Jun 2019)
Over the past week, 23 new papers were published in "Computer Science - Computers and Society".
The paper discussed most in the news over the past week was by a team at Massachusetts Institute of Technology: "Tackling Climate Change with Machine Learning" by David Rolnick et al (Jun 2019), which was referenced 19 times, including in the article AI can help fight climate change — here’s eight ways how in The Verge. The paper author, David Rolnick (Massachusetts Institute of Technology), was quoted saying "Climate change does not present one problem, it presents multiple problems. AI is only one of the tools that can have an impact in the fight to mitigate the effects of climate change". The paper also got the most social media traction with 1372 shares. The authors describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. On Twitter, @ikdeepl said "Yikes “In 2006, at least two Scottish seafood firms flew hundreds of metric tons of shrimp from Scotland to China and Thailand for peeling, then back to Scotland for sale – because they could save on labor costs”".
The paper shared the most on social media this week is "Artificial Intelligence: the global landscape of ethics guidelines" by Anna Jobin et al (Jun 2019) with 141 shares. @socbe (Chris Buehler) tweeted "Very important groundwork done here by and on #AIEthics. Keep going! #mustread #digitaleEthik".
This week was active for "Computer Science - Human-Computer Interaction", with 34 new papers.
The paper shared the most on social media this week is "Interactive Subspace Exploration on Generative Image Modelling" by Toby Chong Long Hin et al (Jun 2019) with 54 shares. @mairoart (mAIro) tweeted "Today's celebration day! One of my works of art is a little part of an amazing paper, thank you Toby Chong Long Hin for adding me".
This week was very active for "Computer Science - Learning", with 314 new papers.
The paper discussed most in the news over the past week was by a team at Massachusetts Institute of Technology: "Tackling Climate Change with Machine Learning" by David Rolnick et al (Jun 2019)
Leading researcher Yoshua Bengio (Université de Montréal) published "Perceptual Generative Autoencoders".
The paper shared the most on social media this week is by a team at Google: "Learning Data Augmentation Strategies for Object Detection" by Barret Zoph et al (Jun 2019)
Over the past week, 12 new papers were published in "Computer Science - Multiagent Systems".
Over the past week, 19 new papers were published in "Computer Science - Neural and Evolutionary Computing".
The paper discussed most in the news over the past week was by a team at University of Oxford: "Stacked Capsule Autoencoders" by Adam R. Kosiorek et al (Jun 2019), which was referenced 2 times, including in the article AI capsule system achieves state-of-the-art image classification results in TaableNote News. The paper got social media traction with 281 shares. A user, @jgvfwstone, tweeted "Stacked Capsule Autoencoders Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton, June 2019. This is reminiscent of sound ideas on "instantiation parameters" in Hinton's earliest papers, but with 21st century computational power".
This week was active for "Computer Science - Robotics", with 53 new papers.
The paper discussed most in the news over the past week was by a team at University of Maryland: "DensePeds: Pedestrian Tracking in Dense Crowds Using Front-RVO and Sparse Features" by Rohan Chandra et al (Jun 2019), which was referenced 2 times, including in the article AI uses camera footage to track pedestrians in dense crowds in TaableNote News. The paper was shared 1 time in social media.
The paper shared the most on social media this week is by a team at DeepMind: "Regularized Hierarchical Policies for Compositional Transfer in Robotics" by Markus Wulfmeier et al (Jun 2019)