You Only Train Once: Differentiable Subset Selection for Omics Data
Daphn\'e Chopard, Jorge da Silva Gon\c{c}alves, Irene Cannistraci, Thomas M. Sutter, Julia E. Vogt
https://arxiv.org/abs/2512.17678 https://arxiv.org/pdf/2512.17678 https://arxiv.org/html/2512.17678
arXiv:2512.17678v1 Announce Type: new
Abstract: Selecting compact and informative gene subsets from single-cell transcriptomic data is essential for biomarker discovery, improving interpretability, and cost-effective profiling. However, most existing feature selection approaches either operate as multi-stage pipelines or rely on post hoc feature attribution, making selection and prediction weakly coupled. In this work, we present YOTO (you only train once), an end-to-end framework that jointly identifies discrete gene subsets and performs prediction within a single differentiable architecture. In our model, the prediction task directly guides which genes are selected, while the learned subsets, in turn, shape the predictive representation. This closed feedback loop enables the model to iteratively refine both what it selects and how it predicts during training. Unlike existing approaches, YOTO enforces sparsity so that only the selected genes contribute to inference, eliminating the need to train additional downstream classifiers. Through a multi-task learning design, the model learns shared representations across related objectives, allowing partially labeled datasets to inform one another, and discovering gene subsets that generalize across tasks without additional training steps. We evaluate YOTO on two representative single-cell RNA-seq datasets, showing that it consistently outperforms state-of-the-art baselines. These results demonstrate that sparse, end-to-end, multi-task gene subset selection improves predictive performance and yields compact and meaningful gene subsets, advancing biomarker discovery and single-cell analysis.
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More than 50 Amazon employees seeking to unionize
walked off the job early Tuesday morning at a Riverside delivery facility, according to the Teamsters.
The overnight walkout marked what union leaders say is the beginning of a new organizing drive for Amazon workers in the Inland Empire,
under which workers are demanding better working conditions and pay for the value they bring to the e-commerce giant.
Workers at the Krameria Avenue facility in Riverside, dubbed DJT6 …
email_company: Manufacturing company email (2010)
A network of emails among employee email addresses at a mid-sized manufacturing company. Each directed edge represents an email sent from address i to address j. Edges are timestamped, and occurred over a 6 month period in an unspecified year.
This network has 167 nodes and 82927 edges.
Tags: Social, Communication, Unweighted, Multigraph, Timestamps
Amazon Threat Intelligence observed sustained targeting of global infrastructure between 2021-2025, with particular focus on the energy sector, by Russian state-sponsored threat actors.
https://aws.amazon.com/blogs/security/
Somebody using #Jellyfin Mobile on iOS on an iPhone ? Does yours play in the background? On mine the music stops as soon as I switch to another app. Background refresh is enabled for the app.
A breakthrough for renewable energy storage: Italian company GES has developed a manganese-hydrogen battery that could reshape the grid.
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Revised January 8, 2026: Simulation of prosthetic vision with the PRIMA system and enhancement of face representation https://arxiv.org/abs/2503.11677 retinal implant
Flock Surveillance
refers to the camera and data systems developed by Flock Safety,
-- a private technology company that provides automated license plate recognition and
vehicle-tracking networks to
police departments, homeowners’ associations, and private businesses across the U.S.
🔥This system enables mass tracking of drivers and data sharing across police and private networks
without sufficient oversight,
raising serious concerns about privacy, …
Jaguar Land Rover confirms staff data stolen in cyberattack https://therecord.media/jaguar-land-rover-confirms-staff-data-stolen-cyberattack
Another crazy week is in the can, so before you head out for the weekend, don't miss today's Metacurity for the most critical developments you should know, including
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