erm
Variance-Reduced Stochastic Gradient Descent on Streaming Data
Ellango Jothimurugesan, Ashraf Tahmasbi, Phillip Gibbons, Srikanta Tirthapura
Neural Information Processing Systems http://nips.cc/
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Gradient Descent (0.88)
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- Research Report > New Finding (0.92)
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LFME: A Simple Framework for Learning from Multiple Experts in Domain Generalization
Extensive experiments on benchmarks from different DG tasks demonstrate that LFME is consistently beneficial to the baseline and can achieve comparable performance to existing arts.
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- Research Report > Experimental Study (1.00)
- Research Report > New Finding (0.67)
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- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.05)
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.68)
On Human-Aligned Risk Minimization
Liu Leqi, Adarsh Prasad, Pradeep K. Ravikumar
Humans diminishes weightF ( ), theeventE = I {, i.e.
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- North America > United States > Pennsylvania > Allegheny County > Pittsburgh (0.16)
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Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions
Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang, Rong Jin, Tianbao Yang
Error bound conditions (EBC) are properties that characterize the growth of an objectivefunction when apoint ismovedawayfrom theoptimal set.
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- Asia > China (0.04)
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