Things to Do in L.A. Tap to enable a layout that focuses on the article. The Dodgers of esports: How L.A.'s Liquid Guild won the attention of over 100,000 people The top "WoW" guilds around the world, including Team Liquid, race to be the first to defeat highest-difficulty bosses. This is read by an automated voice. Please report any issues or inconsistencies here . Los Angeles-based Team Liquid won the "World of Warcraft" world championship for the fourth consecutive time, defeating Germany's Echo guild in a monthlong competition watched by more than 100,000 viewers.

Randomized smoothing is a powerful framework for making models provably robust against small changes to their inputs - by guaranteeing robustness of the majority vote when randomly adding noise before classification.

In this analysis, we assume that evaluating the GP prior mean and kernel functions (and the corresponding derivatives) takesO(1)time. For each fantasy model, we need to compute the posterior mean and covariance matrix for the L points (x,w1:L), on which we draw the sample paths. This results in a total cost ofO(KML2)to generate all samples. The SAA approach trades a stochastic optimization problem with a deterministic approximation, which can be efficiently optimized. Suppose that we are interested in the optimization problemminxEω[h(x,ω)].

Attention Network (GA T), a popular GNN architecture in which a node's neighborhood aggregation is weighted by parameterized attention coefficients.

However,such predictions, although usually accurate, can be arbitrarily poor.

How the candy makers at Hammond's Candies have made the sweet treats for over 100 years. Decembmer 26 is National Candy Cane Day. Breakthroughs, discoveries, and DIY tips sent every weekday. Candy canes are a holiday staple with roots dating back to the 1600s. The story suggests that in 1670, a choirmaster in Cologne, Germany, gave children these sugary sticks shaped like a shepherd's staff for the long nativity church service.

Disseminators of disinformation often seek to attract attention or evoke emotions - typically to gain influence or generate revenue - resulting in distinctive rhetorical patterns that can be exploited by machine learning models. In this study, we explore linguistic and rhetorical features as proxies for distinguishing disinformative texts from other health and life-science text genres, applying both large language models and classical machine learning classifiers. Given the limitations of existing datasets, which mainly focus on fact checking misinformation, we introduce Four Shades of Life Sciences (FSoLS): a novel, labeled corpus of 2,603 texts on 14 life-science topics, retrieved from 17 diverse sources and classified into four categories of life science publications. The source code for replicating, and updating the dataset is available on GitHub: https://github.com/EvaSeidlmayer/FourShadesofLifeSciences