base learner
Robust Mixture Learning when Outliers Overwhelm Small Groups
We study the problem of estimating the means of well-separated mixtures when an adversary may add arbitrary outliers.
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- North America > United States > Louisiana > Orleans Parish > New Orleans (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
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- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- Europe > Netherlands > South Holland > Delft (0.04)
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- Research Report > New Finding (1.00)
- Research Report > Experimental Study (1.00)
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- Information Technology (0.92)
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Supplementary Material
D.9 Parameter Size and Inference Speed . . . . . . . . . . . . . . . . . . . . . . . .
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach
In this paper, we propose an online convex optimization approach with two different levels of adaptivity. On a higher level, our approach is agnostic to the unknown types and curvatures of the online functions, while at a lower level, it can exploit the unknown niceness of the environments and attain problem-dependent guarantees.
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- Asia > China > Jiangsu Province > Nanjing (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
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- Asia > Japan > Honshū > Kansai > Osaka Prefecture > Osaka (0.05)
- North America > Canada > Quebec > Montreal (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Asia > China (0.04)
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- Research Report > New Finding (0.92)
- Workflow (0.67)
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- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.46)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.46)
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.45)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.34)
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- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Asia > China > Hong Kong (0.04)
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