Shadow or no shadow, the rodents have a special set of ecological skills. Breakthroughs, discoveries, and DIY tips sent six days a week. Despite advances in meteorological technology, we still keep a close eye on a rodent's burrow every February 2 for a weather forecast. While groundhogs --also called woodchucks--have been associated with the end of winter and beginning of spring for centuries, there's more to know about our rodent friends than their amateur Al Roker'ing. Unlike bears, groundhogs are true hibernators.

Synthetic data generation has become essential for securely sharing and analyzing sensitive data sets. Traditional anonymization techniques, however, often fail to adequately preserve privacy. We introduce the Tabular Auto-Regressive Generative Network (TabularARGN), a neural network architecture specifically designed for generating high-quality synthetic tabular data. Using a discretization-based auto-regressive approach, TabularARGN achieves high data fidelity while remaining computationally efficient. We evaluate TabularARGN against existing synthetic data generation methods, showing competitive results in statistical similarity, machine learning utility, and detection robustness. We further perform an in-depth privacy evaluation using systematic membership-inference attacks, highlighting the robustness and effective privacy-utility balance of our approach.

Andrew Yang will not forestall the robot apocalypse from the Oval Office, but he may get to do it from New York City Hall. In the 2020 Democratic presidential primary, the former entrepreneur's quirky campaign found a surprisingly robust audience, attracted by Yang's warnings about automation and his promise to mail every American a "freedom dividend" (or, at least, by his math jokes and laid-back, open collar). In the end, the Yang Gang only got their guy as far as the New Hampshire primary. But thanks in part to the name recognition and national network of donors he accrued during that race, Yang is actually leading the polls this year's contest to be the Democratic candidate for New York City mayor. On Friday, Henry Grabar and Jordan Weissmann, two of Slate's native New Yorkers, convened to debate whether this is a good thing. Their debate has been edited and condensed for clarity.

Fox News Flash top headlines for Jan. 29 are here. Check out what's clicking on Foxnews.com. Punxsutawney Phil undergoes "great stress" every year on Groundhog Day and should be replaced by a robot, the leader of PETA says. Ingrid Newkirk writes in a letter to the furry celebrity's Groundhog Club that Phil deserves a break and should be allowed to retire. The request, posted on PETA's website, comes ahead of Sunday's annual ceremony which will determine whether spring arrives early this year.

The trailer is equipped with computers, chairs, video cameras, generators, lasers, nuts and bolts, and two items that turn out to be crucial: garbage bags and toilet paper. What's missing is one female coupler. Robotics Institute research engineer James P. Teza performs some last-minute surgery, soldering two cables together, and Groundhog drives down the ramp out of the trailer, approaching the mouth of the mine. Remaining inside the trailer are the computers that will display the maps and images Groundhog sends back from its journey, the same visuals that will be exhibited at the conference in Charleston before and during Whittaker's talk. Using the laser-generated maps as his guide, Baker steers the robot using the computer's arrow keys to turn right or left and the home key to go straight ahead.

Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and a target language decoder, making promising translation performance. However, as a newly emerged approach, the method has some limitations. An NMT system usually has to apply a vocabulary of certain size to avoid the time-consuming training and decoding, thus it causes a serious out-of-vocabulary problem. Furthermore, the decoder lacks a mechanism to guarantee all the source words to be translated and usually favors short translations, resulting in fluent but inadequate translations. In order to solve the above problems, we incorporate statistical machine translation (SMT) features, such as a translation model and an n-gram language model, with the NMT model under the log-linear framework. Our experiments show that the proposed method significantly improves the translation quality of the state-ofthe-art NMT system on Chinese-to-English translation tasks. Our method produces a gain of up to 2.33 BLEU score on NIST open test sets.