Deep Reinforcement Learning for Search, Recommendation, and Online Advertising - a Survey
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Abstract 뉴스 추천을 위한 딥러닝 기반의 강화 학습 프레임워크를 제안한다. news feature 들과 user 의 preferences 의 변동성 (dynamic) 을 설명하는 것은 상당히 어렵다.
Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning Discussion Q-learning based offline 학습 방식이고, 모델도 무겁고.
Empirical Evaluation: Live Experiments YouTube 에 SARSA-TS 알고리즘을 실험 candidate -> ranker 를 거치게 되는데, ranker 의 scoring 함수에서 사용하는 myopic(근시안적) engagement 측정값을 LTV estimate 로 변경함...
Abstract 해결하려는 문제: 강화학습에서의 효율적인 exploration Randomized value functions offer a promising approach to efficient exploration with generalization, but existing algorithms are not...
Exploration by Random Network Distillation RL methods work by maximizing the expected return of a policy.
paper Link: arxiv.org/pdf/1205.2606.pdf Exploring Compact Reinforcement-learning Representations with Linear Regression KWIK Linear Regression KWIK (Knows What It Knows) is a...
A Survey on Deep Learning Based POI Recommendations A POI recommendation technique essentially exploits users’ historical check-ins and other multimodal information to...
Online Learning to Rank for Information Retrieval Related References slide: staff.fnwi.uva.nl/m.derijke/wp-content/uploads/sigir2016-tutorial.pdf .
Paper page - Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs RLVR의 역설 배경: LLM의 추론 능력을 향상시키기 위해 RLVR(검증 가능한 보상을 이용한 강화학습)...
Joint User-Entity Representation Learning for Event Recommendation in Social Network Paper link Abstract 사용자와 이벤트를 동일한 latent space 에 project 하기 위해 a joint representation...