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Model Perspective
Model Perspective
Aug 6, 2022 · Artificial Intelligence

How Kernel Functions Enable SVMs to Classify Non‑Linear Data

When training data from two classes overlap heavily, linear SVMs fail, so we map inputs into a high‑dimensional Hilbert (feature) space using kernel functions—such as linear, polynomial, radial basis, and Fourier kernels—to make the data linearly separable, formulate a quadratic programming problem, solve its convex dual, and construct a classifier for unknown samples.

Hilbert spaceMachine LearningSVM
0 likes · 2 min read
How Kernel Functions Enable SVMs to Classify Non‑Linear Data
JD Tech Talk
JD Tech Talk
Jun 3, 2020 · Artificial Intelligence

JD Digital Science Unveils Fast Secure Federated Learning Framework and Two Industry‑First Techniques

JD Digital Science introduced its fast secure federated learning framework, highlighted two pioneering technologies—a kernel‑based nonlinear federated learning algorithm and a distributed fast homomorphic encryption method—both accepted at KDD 2020, and discussed their industrial applications, privacy benefits, and regulatory relevance.

AI InfrastructureFederated LearningKDD2020
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JD Digital Science Unveils Fast Secure Federated Learning Framework and Two Industry‑First Techniques