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Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Oct 8, 2024 · Artificial Intelligence

Two NIRC Papers Accepted at NeurIPS 2024: FM-Delta Compression and GLAFF Forecasting

The Beijing University of Posts and Telecommunications' Network Intelligent Research Center (NIRC) had two papers accepted to NeurIPS 2024, presenting FM-Delta, a lossless compression technique that halves storage and cuts cloud costs by over 40%, and GLAFF, a global‑local fusion framework that markedly improves the robustness of time‑series forecasting across multiple domains.

AI researchFM-DeltaGLAFF
0 likes · 8 min read
Two NIRC Papers Accepted at NeurIPS 2024: FM-Delta Compression and GLAFF Forecasting
vivo Internet Technology
vivo Internet Technology
Jun 29, 2022 · Big Data

Lossless Image Compression Overview and Lepton Optimization for Large‑Scale Storage

The article explains JPEG’s lossy fundamentals, introduces Lepton’s lossless layer and its optimizations—such as arithmetic coding and multithreaded Huffman switching—and describes how vivo’s hybrid physical‑server and Kubernetes deployment achieves roughly 22 % storage reduction across petabytes of JPEG images despite high CPU demands.

Huffman codingJPEGLepton
0 likes · 13 min read
Lossless Image Compression Overview and Lepton Optimization for Large‑Scale Storage
21CTO
21CTO
Jul 24, 2021 · Fundamentals

How Jacob Ziv’s Lempel‑Ziv Algorithms Revolutionized Data Compression

Jacob Ziv, the 90‑year‑old Israeli pioneer honored with the 2021 IEEE Medal of Honor, co‑created the groundbreaking Lempel‑Ziv lossless compression algorithms that underpin modern formats like GIF, PNG and ZIP, and his century‑spanning career reshaped data storage, transmission, and information theory.

Jacob ZivLempel-Zivalgorithm history
0 likes · 10 min read
How Jacob Ziv’s Lempel‑Ziv Algorithms Revolutionized Data Compression
ELab Team
ELab Team
Apr 30, 2021 · Fundamentals

Why Use Lossy Compression? Algorithms, RLE, Huffman, and Compression Bombs

This article explains the principles of data compression, contrasting lossy and lossless methods, introduces common algorithms such as Run‑Length Encoding, dictionary coding, and Huffman coding, and discusses extreme cases like compression bombs, illustrating concepts with examples and visual diagrams.

Huffman codingcompression algorithmsdata compression
0 likes · 9 min read
Why Use Lossy Compression? Algorithms, RLE, Huffman, and Compression Bombs