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EM algorithm

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Model Perspective
Model Perspective
Mar 1, 2023 · Artificial Intelligence

Mastering the EM Algorithm: Theory, Math, and Python Implementation

This article explains the Expectation‑Maximization (EM) algorithm, detailing its iterative E‑step and M‑step processes, mathematical formulation, and practical Python implementation for estimating parameters of mixed linear regression models, while highlighting convergence considerations and common pitfalls.

EM algorithmexpectation maximizationmachine learning
0 likes · 12 min read
Mastering the EM Algorithm: Theory, Math, and Python Implementation
Model Perspective
Model Perspective
Jan 8, 2023 · Artificial Intelligence

Unlock Hidden Patterns: A Deep Dive into Unsupervised Learning Techniques

This article introduces unsupervised learning, covering its motivation, Jensen's inequality, key clustering methods such as EM, k‑means, hierarchical clustering, evaluation metrics, and dimensionality‑reduction techniques like PCA and ICA, providing clear explanations and illustrative diagrams.

EM algorithmICAPCA
0 likes · 8 min read
Unlock Hidden Patterns: A Deep Dive into Unsupervised Learning Techniques
DataFunTalk
DataFunTalk
Nov 10, 2021 · Artificial Intelligence

Learnable Index Structures for Large‑Scale Retrieval: Deep Retrieval Model and Training Methods

This article introduces ByteDance's Deep Retrieval (DR) framework, describing its learnable index structure that aligns embedding training with retrieval objectives, detailing the core model, structure‑loss training via EM and online EM algorithms, beam‑search serving, multi‑task learning, and practical insights from Q&A.

EM algorithmRecommendation systemsbeam search
0 likes · 11 min read
Learnable Index Structures for Large‑Scale Retrieval: Deep Retrieval Model and Training Methods