Week Ending 03.10.19
RESEARCH WATCH: 03.10.19
Over the past week, 307 new papers were published in "Computer Science".
The paper discussed most in the news over the past week was "Spectre is here to stay: An analysis of side-channels and speculative execution" by Ross Mcilroy et al (Feb 2019), which was referenced 22 times, including in the article Cheap as chips: There's no such thing as a free lunch any Moore in The Register. The paper author, Ross Mcilroy, was quoted saying "This class of flaws are deeper and more widely distributed than perhaps any security flaw in history, affecting billions of CPUs in production across all device classes".
Leading researcher Sergey Levine (University of California, Berkeley) came out with "Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching".
This week was active for "Computer Science - Artificial Intelligence", with 107 new papers.
The paper discussed most in the news over the past week was by a team at DeepMind: "TF-Replicator: Distributed Machine Learning for Researchers" by Peter Buchlovskyet al (Feb 2019), which was referenced 4 times, including in the article Google's distributed computing for dummies trains ResNet-50 in under half an hour in ZDNet.
Leading researcher Yoshua Bengio (Université de Montréal) came out with "Interpolation Consistency Training for Semi-Supervised Learning".
Over the past week, 199 new papers were published in "Computer Science - Computer Vision and Pattern Recognition".
The paper discussed most in the news over the past week was "Predictive Inequity in Object Detection" by Benjamin Wilson et al (Feb 2019), which was referenced 62 times, including in the article Self-Driving Cars Are 'More Likely' To Hit And Kill Non-White Pedestrians in Forbes.com. The paper author, Jamie Morgenstern (University of Pennsylvania), was quoted saying "The main takeaway from our work is that vision systems that share common structures to the ones we tested should be looked at more closely".
Leading researcher Pieter Abbeel (University of California, Berkeley) published "Domain Randomization for Active Pose Estimation".
Over the past week, 23 new papers were published in "Computer Science - Computers and Society".
This week was active for "Computer Science - Human-Computer Interaction", with 24 new papers.
This week was active for "Computer Science - Learning", with 187 new papers.
The paper discussed most in the news over the past week was "Predictive Inequity in Object Detection" by Benjamin Wilson et al (Feb 2019), which was referenced 62 times, including in the article Self-Driving Cars Are 'More Likely' To Hit And Kill Non-White Pedestrians in Forbes.com. The paper author, Jamie Morgenstern (University of Pennsylvania), was quoted saying "The main takeaway from our work is that vision systems that share common structures to the ones we tested should be looked at more closely".
Leading researcher Yoshua Bengio (Université de Montréal) came out with "Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future".
This week was active for "Computer Science - Multiagent Systems", with 20 new papers.
The paper discussed most in the news over the past week was "Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents" by Joseph Suarez et al (Mar 2019), which was referenced 4 times, including in the article Battle of the AI Agents: Atari Versus MMORPG in ZDNet.Over the past week, 35 new papers were published in "Computer Science - Neural and Evolutionary Computing".
Leading researcher Kyunghyun Cho (New York University) came out with "Continual Learning via Neural Pruning".
Over the past week, 35 new papers were published in "Computer Science - Neural and Evolutionary Computing".
Leading researcher Kyunghyun Cho (New York University) came out with "Continual Learning via Neural Pruning"
This week was very active for "Computer Science - Robotics", with 86 new papers.
The paper discussed most in the news over the past week was "Touching to See and Seeing to Feel: Robotic Cross-modal SensoryData Generation for Visual-Tactile Perception" by Jet-Tsyn Lee et al (Feb 2019), which was referenced 1 time, including in the article Generating cross-modal sensory data for robotic visual-tactile perception in PhysOrg.com. The paper author, Dr. Luo, was quoted saying "We take texture perception as an example: visual input images of a cloth texture are used to generate a pseudo tactile reading of the same piece of cloth; conversely, tactile readings of a cloth are employed to predict a visual image of the same cloth".
Leading researcher Sergey Levine (University of California, Berkeley) came out with "Skew-Fit: State-Covering Self-Supervised Reinforcement Learning". This paper was also shared the most on social media with three tweets.