Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Abstract: Knowledge transfer among multiple networks, using predicted probabilities or intermediate-layer activations, has evolved significantly through extensive manual design, ranging from simple ...
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...
The calendar still says fall, but the atmosphere is skipping ahead to winter as a rush of Arctic air sends more than two dozen states into a brief deep freeze. It all starts this weekend in the ...
OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
Today, Indiana thrives as a hub for innovators, visionaries and bold thinkers who will shape our future. Our manufacturers, logistics networks and research universities propel the Midwest and America ...
A few years ago, I followed the life of a cheese curd, from milk on a dairy farm to fresh cheese in Ellsworth, Wis., to deep-fried glory at the Fair. On the Fairgrounds, though, there are plenty of ...
Pointing to Korea's rise in autos, the late Berkshire Hathaway vice chair argued that "only a total idiot" would be surprised to lose to competitors who outwork and outlearn you. He cited the example ...
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