Represent k-means as an MLP

Quick Overview

This question evaluates understanding of how the nearest-centroid step of k-means can be expressed as a fully connected neural network layer with activation, focusing on linear algebra, model equivalence, and numerical behavior of softmax under low temperature.

Represent k-means as an MLP

Company: Sealth

Role: Machine Learning Engineer

Category: Machine Learning

Difficulty: easy

Interview Round: Onsite

Quick Answer: This question evaluates understanding of how the nearest-centroid step of k-means can be expressed as a fully connected neural network layer with activation, focusing on linear algebra, model equivalence, and numerical behavior of softmax under low temperature.

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Sealth
Apr 12, 2026, 12:00 AM
easyMachine Learning EngineerOnsiteMachine Learning
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