Tag

Multi-armed bandit

0 views collected around this technical thread.

Model Perspective
Model Perspective
Jan 22, 2024 · Artificial Intelligence

How A/B Testing and the ε‑Greedy Multi‑Armed Bandit Can Boost Decisions

This article explains the principles of A/B testing and the ε‑greedy multi‑armed bandit algorithm, illustrates their practical use in e‑commerce recommendation optimization, and draws broader life lessons about balancing exploration and exploitation for better personal and professional decisions.

A/B testingExploration vs exploitationGreedy
0 likes · 6 min read
How A/B Testing and the ε‑Greedy Multi‑Armed Bandit Can Boost Decisions
58 Tech
58 Tech
Dec 28, 2021 · Artificial Intelligence

Reinforcement Learning for Cold‑Start Job Recommendation in 58.com

This talk explains how 58.com tackles the cold‑start and interest‑divergence problems of its massive blue‑collar job recruitment platform by modeling the recommendation process as a reinforcement‑learning task, detailing the use of multi‑armed bandit, contextual bandit, and linear‑UCB algorithms, offline evaluation pipelines, online deployment, and observed performance gains.

Cold StartMulti-armed banditcontextual bandit
0 likes · 25 min read
Reinforcement Learning for Cold‑Start Job Recommendation in 58.com
DataFunTalk
DataFunTalk
Dec 17, 2021 · Artificial Intelligence

Applying Reinforcement Learning to Solve Cold‑Start Problems in 58.com Job Recruitment

This talk explains how 58.com’s massive blue‑collar recruitment platform uses reinforcement‑learning techniques—including multi‑armed bandits, contextual MAB, and linear UCB—to address cold‑start and interest‑divergence challenges, describes the system architecture, offline evaluation, online deployment, and reports an 8% uplift in new‑user conversion.

Cold StartMulti-armed banditcontextual MAB
0 likes · 26 min read
Applying Reinforcement Learning to Solve Cold‑Start Problems in 58.com Job Recruitment
DataFunTalk
DataFunTalk
Nov 12, 2020 · Artificial Intelligence

Reinforcement Learning for Recommendation System Mixing: Concepts, Practice, and Evaluation

This article explains how reinforcement learning, with its focus on maximizing long‑term reward, can improve recommendation system mixing by covering basic RL concepts, differences from supervised learning, multi‑armed bandit approaches, practical OpenAI Gym experiments, new AUC metrics, online gains, and advanced model optimizations.

Multi-armed banditOpenAI GymQ-learning
0 likes · 10 min read
Reinforcement Learning for Recommendation System Mixing: Concepts, Practice, and Evaluation
DataFunTalk
DataFunTalk
Jan 7, 2020 · Artificial Intelligence

Personalized Poster Production and Distribution System for Video Recommendation

This article describes how iQIYI’s technical product team designed and implemented an AI‑driven personalized poster generation and distribution pipeline that automatically creates, ranks, and serves customized video posters, improving click‑through rates across TV and mobile platforms.

AIMulti-armed banditcontent personalization
0 likes · 11 min read
Personalized Poster Production and Distribution System for Video Recommendation
Qunar Tech Salon
Qunar Tech Salon
May 16, 2016 · Artificial Intelligence

Improving A/B Testing with a 20‑Line Multi‑Armed Bandit Algorithm

This article explains how a simple 20‑line multi‑armed bandit implementation can replace traditional A/B testing by continuously balancing exploration and exploitation to automatically discover the most effective UI variant, reducing manual analysis and improving conversion rates.

A/B testingMulti-armed banditexploitation
0 likes · 8 min read
Improving A/B Testing with a 20‑Line Multi‑Armed Bandit Algorithm