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政采云技术
政采云技术
Sep 19, 2023 · Big Data

Techniques for Processing Massive Data: Sorting, Querying, Top‑K, and Deduplication

This article explains core concepts and practical solutions for handling massive datasets that cannot fit into memory, covering batch processing, distributed sorting, bitmap indexing, hash‑based lookups, top‑K extraction, and deduplication techniques with code examples and multi‑machine strategies.

Big DataDeduplicationbitmap indexing
0 likes · 18 min read
Techniques for Processing Massive Data: Sorting, Querying, Top‑K, and Deduplication
Baidu Geek Talk
Baidu Geek Talk
Aug 21, 2023 · Artificial Intelligence

Decoding Strategies for Generative Models: Top‑k, Top‑p, Contrastive Search, Beam Search, and Sampling

The article explains how generative models use deterministic methods like greedy and beam search and stochastic techniques such as top‑k, top‑p, contrastive search and sampling, describing their mechanisms, temperature control, repetition penalties, and practical trade‑offs for balancing fluency, diversity and coherence.

aibeam searchcontrastive search
0 likes · 9 min read
Decoding Strategies for Generative Models: Top‑k, Top‑p, Contrastive Search, Beam Search, and Sampling
DataFunTalk
DataFunTalk
Sep 30, 2019 · Artificial Intelligence

Reinforcement Learning for Recommender Systems: Challenges, Solutions, and Key Papers

This article reviews recent advances in applying reinforcement learning to recommendation systems, explains the fundamental RL concepts, discusses the specific challenges such as large action spaces, bias, and long‑term reward modeling, and summarizes two influential YouTube papers along with practical insights and future directions.

long-term rewardoff-policyrecommender systems
0 likes · 13 min read
Reinforcement Learning for Recommender Systems: Challenges, Solutions, and Key Papers