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CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition

Neural Information Processing Systems

Skeleton-based multi-entity action recognition is a challenging task aiming to identify interactive actions or group activities involving multiple diverse entities. Existing models for individuals often fall short in this task due to the inherent distribution discrepancies among entity skeletons, leading to suboptimal backbone optimization. To this end, we introduce a Convex Hull Adaptive Shift based multi-Entity action recognition method (CHASE), which mitigates inter-entity distribution gaps and unbiases subsequent backbones. Specifically, CHASE comprises a learnable parameterized network and an auxiliary objective. The parameterized network achieves plausible, sample-adaptive repositioning of skeleton sequences through two key components.


What if Every Decision You Made Came With a Risk Score?

Slate

This story is part of Future Tense Fiction, a monthly series of short stories from Future Tense and Arizona State University's Center for Science and the Imagination about how technology and science will change our lives. By the time Tara returned from the protest, SafeT gauged her Wellness at 60% and Chase felt sick. For the last two hours he'd watched the number on his phone's app tick down, from safe green to warning yellow: 87%, 74%, 60%. On his newsfeed, masked chanters waved signs before the wire cage shielding the five megapipes that breached the marshy shore of Lake Michigan. Each pipe was owned by a consortium of Lakes United companies. Their great steel veins wormed the city, bearing water from LU to the drought-scarred West and South, whose nations paid more per acre-foot than Milwaukee's citizens ever could. On the feed Chase hadn't been able to see Tara or the sign she'd painted that morning: Our Lake, Our Water. What he had seen were the security corps of at least three consortia, clumped beneath their ever-circling camera-drones, bull-horning the chanters that they were risking corporate slander. If arrested, they'd be hauled off to one of the consortia's private prisons. There they could be coerced into confessing they were linebreakers, guerillas who spliced pipes to siphon off clean water to Milwaukee neighborhoods that couldn't afford consortia prices. Protestors sometimes returned from these prisons. Fingers numb, Chase had tapped SafeT to view the breakdown of Tara's Wellness aggregate into its individual components: risk of arrest (15%), risk of indictment (20%), risk of job loss (27%), risk of injury (31%). Even when she had texted home in 30 and he'd cleared her route in the SafeT map--low smoke risk, low contagion risk, 93% chance of safe arrival--his jaw only eased when she stepped through the door. Tara's thin face was ferocious, cheeks red against her yellow hair. Black grease spotted her strong hands. Over the decade they'd shared, he'd watched age sharpen her into herself. Now, impassioned, she was fiercely beautiful. He almost forgot her yellow number, until she saw him, and her smile sagged.


Laggards, leaders face digital transformation challenges

#artificialintelligence

The disparity between digital transformation leaders and laggards stems from a complex web of overlapping factors -- which often speak more to organizational issues than technical difficulties. Considerations in play include corporate history, IT philosophy, the ability to deliver on customer experience and a product vs. project mindset. A particularly important element separating a successful digital business from its competitors is a knack for translating small successes into enterprise-wide benefits. Indeed, overcoming digital transformation challenges at scale is crucial for realizing the promise of technology-infused business models, according to CIOs and industry analysts. Companies playing catch-up in the digital race must first focus on the essentials, such as customer experience, before moving on to more innovative pursuits.


Extend Spinnaker Automated Delivery with Machine Learning and Custom Pipeline Logic - The New Stack

#artificialintelligence

The open source Spinnaker is a continuous delivery tool originally developed by Netflix and Google, one that could be used to run a development pipeline for multiple cloud deployments. The software has found a home with the OpenStack community. Like OpenStack, Spinnaker streamlines and automates an inherently complex process of packaging resources in a heterogeneous environment. "In an ideal world, Spinnaker should live inside the OpenStack Foundation, because the approach that OpenStack has been solving problems in the infrastructure space is very similar to what Spinnaker does in the application delivery space" Boris Renski, co-founder of Mirantis, recently explained to us. Mirantis uses Spinnaker as a component of its recently launched-in-Beta commercially supported Mirantis Application Platform.