Labeling training data is a key bottleneck in the modern machine learning pipeline. Recent weak supervision approaches combine labels from multiple noisy sources by estimating their accuracies without access to ground truth labels; however, estimating the dependencies among these sources is a critical challenge. We focus on a robust PCA-based algorithm for learning these dependency structures, establish improved theoretical recovery rates, and outperform existing methods on various real-world tasks. Under certain conditions, we show that the amount of unlabeled data needed can scale sublinearly or even logarithmically with the number of sources $m$, improving over previous efforts that ignore the sparsity pattern in the dependency structure and scale linearly in $m$. We provide an information-theoretic lower bound on the minimum sample complexity of the weak supervision setting. Our method outperforms weak supervision approaches that assume conditionally-independent sources by up to 4.64 F1 points and previous structure learning approaches by up to 4.41 F1 points on real-world relation extraction and image classification tasks.

He has demanded "goddamned steam" to power the Navy's aircraft carriers and prefers a wall to drones and other technology to secure the country's southern border. He has rejected the scientific consensus on climate change and repeatedly, wrongly, pointed to occasional wintry weather as proof that he's right. And this week, amid a safety scare involving Boeing's 737 MAX 8 and MAX 9 airplanes, President Trump complained that modern jets are "too complex to fly." He added: "I see it all the time in many products. Always seeking to go one unnecessary step further, when often old and simpler is far better."

Both developing babies and elderly adults share a common characteristic: the many cells making up their bodies are always on the move. As we humans commute to work, cells migrate through the body to get their jobs done. Biologists have long struggled to quantify the movement and changing morphology of cells through time, but now, scientists at the Okinawa Institute of Science and Technology Graduate University (OIST) have devised an elegant tool to do just that. Using machine learning, the researchers designed a software to analyze microscopic snapshots of migrating cells. They named the software Usiigaci, a Ryukyuan word that refers to tracing the outlines of objects, as the innovative tool detects the changing outlines of individual cells.

Esophagogastroduodenoscopy (EGD) is the pivotal procedure in the diagnosis of upper gastrointestinal lesions.1 High-quality endoscopy delivers better health outcomes.2 However, there are significant variations in EGD performance among endoscopists, impairing the discovery rate of gastric cancers (GC) and precursor lesions.3 The diagnosis rate of early GC in China is still under 20% and similar results are seen in most part of the world.4 5 While further expanding endoscopic technology, it is vital to raise the quality of everyday endoscopy. Ensuring competence is a seminal prerequisite for discovering lesions in EGD.6 Plenty of guidelines or expert consensus have been reached to optimise EGD examination.7 The American Society for Gastrointestinal Endoscopy (ASGE) and American College of Gastroenterology (ACG) developed safety and quality indicators for EGD.8–10

China is poised to overtake the United States in artificial intelligence with a surge in academic research on the key technology, an analysis published Wednesday showed. The analysis by the Allen Institute for Artificial Intelligence showed China has already surpassed the US in published papers on AI--although many of these were considered "medium-quality" or "low-quality." But the researchers said China is likely to top the US in the most-cited 50 percent of papers this year, the most-cited 10 percent of papers next year, and in the top one percent by 2025. The findings highlight concerns in Washington and Silicon Valley that China is racing ahead of the US in key areas of technology such as autonomous vehicles, virtual reality and fifth-generation wireless networks. Allen Institute researchers Field Cady and Oren Etzioni said the surge in AI investment in China began more than a decade ago, well before the 2017 announcement by Beijing that it planned to become the world leader in the sector by 2030.

Sheer cliff faces present a traversal challenge for most wheeled robots on the market, but researchers at the University of Tokyo say they've developed a two-robot framework that works pretty reliably in their testing. In a newly published paper on the preprint server Arxiv.org "[We] propose a novel cooperative system for an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) which utilizes the UAV not only as a flying sensor but also as a tether attachment device," the authors of the paper explain. "[It enhances] the poor traversability of the UGV by not only providing a wider range of scanning and mapping from the air, but also by allowing the UGV to climb steep terrains with the winding of the tether." The UGV is permanently attached via mechanized winch and cable to the UAV, a custom-made quadcopter with an Nvidia Jetson TX2 chipset, a flight controller, and a raft of sensors including a modular fisheye camera, time-of-flight sensor, inertial measurement unit (IMU), and laser sensor.

China is poised to overtake the United States in artificial intelligence with a surge in academic research on the key technology, an analysis published Wednesday showed. The analysis by the Allen Institute for Artificial Intelligence showed China has already surpassed the US in published papers on AI -- although many of these were considered "medium-quality" or "low-quality." But the researchers said China is likely to top the US in the most-cited 50 percent of papers this year, the most-cited 10 percent of papers next year, and in the top one percent by 2025. The findings highlight concerns in Washington and Silicon Valley that China is racing ahead of the US in key areas of technology such as autonomous vehicles, virtual reality and fifth-generation wireless networks. Allen Institute researchers Field Cady and Oren Etzioni said the surge in AI investment in China began more than a decade ago, well before the 2017 announcement by Beijing that it planned to become the world leader in the sector by 2030.

HEJERE, ETHIOPIA - Canada joined much of the world in barring the Boeing 737 Max 8 jet from its airspace on Wednesday, saying satellite tracking data show possible but unproven similarities between the Ethiopian Airliner crash that killed 157 people and a previous crash involving the model five months ago. The decision left the U.S. as one of the few remaining countries to allow the planes to keep flying. Canadian Transport Minister Marc Garneau said a comparison of vertical fluctuations found a "similar profile" to the Lion Air crash that killed 187 people in October. Garneau emphasized that the data are not conclusive but crossed a threshold that prompted Canada to bar the Max 8. He said the new information indicated the Ethiopian Airliner jet's automatic system kicked in to force the nose of the aircraft down after computer software determined it was too high.

While it may not lead to the next Cold War, the growing rivalry between the United States and China has certainly led to some frosty competition between the great powers. This is especially true of the tech sector, where some analysts liken the U.S. and China's heavy strategic investments in cybersecurity, quantum computing, 5G, and artificial intelligence to a digital arms race, one that, because of China's long-term positioning and access to vast amounts of data to train on, that country will win. But Anne-Marie Slaughter argues that when it comes to the world-shifting technology of artificial intelligence, the narrative isn't so simple. She explains why she is putting her money on the United States. Great power conflict isn't the only thing we at Future Tense have been fretting about this week.

An extended 5km (3.1 miles) no-fly zone for drones has come into force around airports in the UK after reported sightings at Gatwick, Heathrow and Dublin airports in recent months grounded hundreds of flights and left thousands stranded. Previously, only a 1km (0.6 mile) exclusion zone was in place. But despite the negative reputation they have received, the use of drones isn't all bad. From finding missing people to delivering takeaways, here are some of the ways the unmanned aircraft can be beneficial. A Norfolk man who went missing in June last year was only found when a police drone spotted him stuck on a marsh.