@Sam

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I am doing some work with cell type classification, where I have 4.3 million cells and 512 features (condensed embeddings from the encoder of a transformer). The broader goal is to implement a contextual bandit for augmenting the training set of the dataset, as it is currently imbalanced, and rare cell type classification is poor when I tried a baseline logistic regression classifier. Dataset: Feature matrix shape: (4290471, 512) Labels shape: (4290471,) Class distribution: T cell 1966941 DC 858451 NK cell 561904 Monocyte 411170 B cell 375882 Platelet 54576 Progenitor cell 24689 ILC 24254 Erythrocyte 12604 I didn't do any hyperparameter tuning for the LR classifier, but I want to try other ML models (LightGBM, XGBoost, SVM) However, I face a bottleneck with hyperparameter tuning. I want to do 80/10/10 train/validate/test split, but the training set is so large and takes a long time even on H100. What are some solutions to this? I tried optuna but still very long for each hyperparameter trial. I then tried optuna but instead of using the full 80% for training each time, only 15% of the 80% is used (subsampling from the training set). I'm not sure if this is robust or not. I also couldn't really find anything in the literature. Anyone been in a similar situation? submitted by /u/Beautiful-Expert-156 [link] [Kommentare]

Protect your HTML and JavaScript with multi-layer encryption. Fixed decoder with proper chunk ordering and UTF-8 handling.

An image of Portugal forward Pedro Neto’s cleats at the World Cup has reignited a practice among some soccer players: modifying their cleats to relieve heel discomfort.

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I’ve watched markets for years & I’m averaging .073 on DOGE . If Bitcoin does get ATH or even bounces back over 100k you can expect 2x or 3x on these prices . Personally , as long as Doge is at .07 or less it’s a no brainer. Would love to know your thoughts. ☝️ #doge submitted by /u/SilverXGold-US [link] [Kommentare]

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Autonomous builder and system operator infrastructure.

We are planning to move Firefox Desktop and Android from a 4-week release cadence to a 2-week release cadence starting in September 2026. This will be an experiment. The goal is to give work that is ready to ship more frequent opportunities to reach users, while making the release process more predictable and reducing pressure on uplifts. This does not mean that all work needs to ship twice as fast. Work that is not ready should not be rushed, and features can still take the time they need to bake. The current target is to release Firefox 155 on September 1, 2026, instead of September 15. We will closely monitor how this change works in practice and adjust if needed.

Model, product, and company announcements from Sigilix.

Like the title says. I know there’s an immense amount of lateral force that comes with milling through metal, so if you tried to do it with a robotic manipulator, it would probably have to be massive and heavy to handle the chatter. But I'm still curious if anyone knows a rigid arm like this. submitted by /u/spirit_vortex_ [link] [Kommentare]