منابع مشابه
Online Machine Learning in Big Data Streams
The area of online machine learning in big data streams covers algorithms that are (1) distributed and (2) work from data streams with only a limited possibility to store past data. The first requirement mostly concerns software architectures and efficient algorithms. The second one also imposes nontrivial theoretical restrictions on the modeling methods: In the data stream model, older data is...
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A novel online dynamic value system for machine learning is proposed in this paper. The proposed system has a dual network structure: data processing network (DPN) and information evaluation network (IEN). The DPN is responsible for numerical data processing, including input space transformation and online dynamic data fitting. The IEN evaluates results provided by DPN. A dynamic three-curve fi...
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1. In the context of classification, ` is typically a convex surrogate loss function in the sense that (i) w → `(w, (x, y)) is convex for any example (x, y) and (ii) `(w, (x, y)) is larger than the true prediction error given by 1y〈w,x〉≤0 for any example (x, y). In general, we introduce this surrogate loss function because it would be difficult to solve (1) computationally. On the other hand, c...
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Max-margin and kernel methods are dominant approaches to solve many tasks in machine learning. However, the paramount question is how to solve model selection problem in these methods. It becomes urgent in online learning context. Grid search is a common approach, but it turns out to be highly problematic in real-world applications. Our approach is to view max-margin and kernel methods under a ...
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For the experts problem (and its close relative B1/B∞ linear game) we have developed a deterministic method (Exponential Weights) and a randomized method (Follow the Perturbed Leader). Both the deterministic and randomized methods extend to other online prediction problems where the loss is linear in the decision of the learner and linear in the outcome. We have seen that the geometry of the tw...
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ژورنال
عنوان ژورنال: Ear & Hearing
سال: 2018
ISSN: 0196-0202
DOI: 10.1097/aud.0000000000000669