Common modifications include:(i)tuning attack parameters (e.g., number ofsteps),(ii)replacing network components to simplify the attack (e.g., removing randomization or non-differentiable components), and(iii) replacing the loss function optimized by the attack.

Thank you for the suggestions. Basedonourexperimental results,Rankmaxwaspronetooverfitting onthesmaller20 dataset (as discussed line 269), but this can be remedied using early stopping on a cross-validation set.

Archaeologists say they located a Black Death burial site containing some of a village's 12,000 dead. Breakthroughs, discoveries, and DIY tips sent six days a week. The Black Death () killed as much as half of Europe's total population between 1346 and 1353, so there are a of bodies buried across the continent. For example, contemporary accounts from Thuringia--a state in central Germany--report that about 12,000 plague victims died around Erfurt amid the city's outbreak in 1350. But despite multiple accounts attesting to this devastation, none of the 11 mass graves could be pinpointed for centuries.

This paper develops an approximation to the (effective) $p$-resistance and applies it to multi-class clustering. Spectral methods based on the graph Laplacian and its generalization to the graph $p$-Laplacian have been a backbone of non-euclidean clustering techniques. The advantage of the $p$-Laplacian is that the parameter $p$ induces a controllable bias on cluster structure. The drawback of $p$-Laplacian eigenvector based methods is that the third and higher eigenvectors are difficult to compute. Thus, instead, we are motivated to use the $p$-resistance induced by the $p$-Laplacian for clustering. For $p$-resistance, small $p$ biases towards clusters with high internal connectivity while large $p$ biases towards clusters of small "extent," that is a preference for smaller shortest-path distances between vertices in the cluster. However, the $p$-resistance is expensive to compute. We overcome this by developing an approximation to the $p$-resistance. We prove upper and lower bounds on this approximation and observe that it is exact when the graph is a tree. We also provide theoretical justification for the use of $p$-resistance for clustering. Finally, we provide experiments comparing our approximated $p$-resistance clustering to other $p$-Laplacian based methods.

As companies struggle to find ways to take on the nationwide labor shortage, automation has become increasingly appealing. Initially seen as a job killer, automation may actually be the answer to ongoing worker shortages, particularly in the manufacturing sector, which is projected to have 2.1 million unfilled jobs by 2030, according to a May 2021 study by Deloitte and the National Association of Manufacturers (NAM). "You've got to start thinking that robots can do some of these jobs," Lauren Hein, head of advisor relations at ROBO Global, an investment firm specializing in automation investment, told Yahoo Finance Live (video above). In July 2022, there were nearly six million unemployed workers but 10 million vacant jobs, according to the U.S. Chamber of Commerce. Rather than waiting to find enough workers to fill that void, Hein suggested automation as a reasonable alternative.

As populations age, more and more people are asking how best to organise care for the elderly in future. Trained staff will be important, as will technology and innovation – which may include artificial intelligence (AI). Some people get fearful when talk turns to AI, a topic riddled with misconceptions. At the end of the day, what it means is the attempt to map human decisions using computers, says Andreas Hein, an expert in assistance systems at Oldenburg University in Germany. In a medicine or health care setting, that means providing doctors and nurses suggestions that a computer has created based on data.

Last year, the BBC reported that 800 million global workers will lose their jobs to robotic automation by 2030. This statistic, from a McKinsey Global Institute study, led to countless headlines asking, will robots take your job? The study found that robots will eliminate some jobs, but also create new ones. As the field develops, European roboticists are busy investigating how factory robots could create new opportunities for workers in manufacturing jobs. The MANUWORK project is collaborating with non-profit group Lantegi Batuak in Spain, which helps to incorporate people with disabilities into the world of work.

The graph Laplacian plays key roles in information processing of relational data, and has analogies with the Laplacian in differential geometry. In this paper, we generalize the analogy between graph Laplacian and differential geometry to the hypergraph setting, and propose a novel hypergraph p-Laplacian. Unlike the existing two-node graph Laplacians, this generalization makes it possible to analyze hypergraphs, where the edges are allowed to connect any number of nodes. Moreover, we propose a semi-supervised learning method based on the proposed hypergraph p-Laplacian, and formalize them as the analogue to the Dirichlet problem, which often appears in physics. We further explore theoretical connections to normalized hypergraph cut on a hypergraph, and propose normalized cut corresponding to hypergraph p-Laplacian. The proposed p-Laplacian is shown to outperform standard hypergraph Laplacians in the experiment on a hypergraph semi-supervised learning and normalized cut setting.

Last week Obsidian dangled the smallest scraps of a new project: Tyranny, a new isometric CRPG built in the Pillars of Eternity engine. A world where the battle between good and evil already took place, and evil won. Here's the trailer again, in case you need a refresher: Pretty light on the details, eh? Luckily we got a half-hour demo of the project at GDC. The key takeaway: Tyranny might share the same engine as Pillars of Eternity, but that's about all. This is a wild project.