Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation | Paper Citation Record

Observation ba8abb92-f131-4f09-bafe-6242efccd850 · outbound

This paper cites Deep neural networks for youtube recommendations,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Deep neural networks for youtube recommendations,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:04.322305Z

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Observation 683b2d29-92e1-4da5-81cb-267807310cd4 · outbound

This paper cites Amazon. com recommendations: Item-to-item collaborative filtering,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Amazon. com recommendations: Item-to-item collaborative filtering,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:04.126388Z

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Observation 538d8ef4-0873-4a01-9b5a-c4d0170fdb78 · outbound

This paper cites A survey on federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A survey on federated learning,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:49.063463Z

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Observation a39ba7ea-f071-43d7-a3a9-c76ccddbc878 · outbound

This paper cites A Survey on Federated Recommendation Systems.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A Survey on Federated Recommendation Systems

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:33:54.714441Z

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Observation 0d8f566f-f955-4d47-890b-e44a4b81ef20 · outbound

This paper cites Federated recommendation systems,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Federated recommendation systems,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:03.987242Z

Source-reported events for the cited work

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Observation 85e8b25d-f199-495d-97ac-a32f675cfb0e · outbound

This paper cites Federated recommenders: methods, challenges and future,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Federated recommenders: methods, challenges and future,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:03.813067Z

Source-reported events for the cited work

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Observation f92c2dc5-6060-482e-8d0c-d7ce2a0d0716 · outbound

This paper cites A comprehensive survey on privacy-preserving techniques in federated recommendation systems,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A comprehensive survey on privacy-preserving techniques in federated recommendation systems,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:03.597625Z

Source-reported events for the cited work

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Observation 319f6f78-4a5b-417d-a9d3-068f7b356cbe · outbound

This paper cites Recent advances and future challenges in federated recommender systems,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Recent advances and future challenges in federated recommender systems,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:03.425100Z

Source-reported events for the cited work

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Observation b0fffcb6-a24f-4034-976a-12195c9d73c8 · outbound

This paper cites A survey on cross-user federated recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A survey on cross-user federated recommendation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:03.248647Z

Source-reported events for the cited work

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Observation 4d9cec4e-88e3-4887-831a-c84ec5698eee · outbound

This paper cites Privacy-preserved and responsible recommenders: From conventional defense to federated learning and blockchain,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Privacy-preserved and responsible recommenders: From conventional defense to federated learning and blockchain,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:49.667731Z

Source-reported events for the cited work

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Observation 7f036d7a-2ca2-4a5c-b899-8befd9ec25c5 · outbound

This paper cites On-Device Recommender Systems: A Comprehensive Survey.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation On-Device Recommender Systems: A Comprehensive Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:49.759684Z

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Observation 33d51799-a4d0-4b20-87cb-d2b6cab60637 · outbound

This paper cites Client selection in federated learning: Principles, challenges, and opportunities,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Client selection in federated learning: Principles, challenges, and opportunities,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:03.061145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c442bf01-210a-4616-aa25-f83c989d33ed · outbound

This paper cites A review of client selection methods in federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A review of client selection methods in federated learning,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:02.878049Z

Source-reported events for the cited work

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Observation cc8cd8f9-5022-4249-9be3-ed6f894a5410 · outbound

This paper cites A comprehensive survey on client selection strategies in federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A comprehensive survey on client selection strategies in federated learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:02.715306Z

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Observation 84c58d6c-63f0-4583-9bad-27de14c263e6 · outbound

This paper cites Auction: Automated and quality-aware client selection framework for efficient federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Auction: Automated and quality-aware client selection framework for efficient federated learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:02.541713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f2634f65-3ac6-405d-8d95-ef3f1de85802 · outbound

This paper cites Client selection in federated learning based on gradients importance,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Client selection in federated learning based on gradients importance,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:02.334050Z

Source-reported events for the cited work

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Observation 01c15c46-d2ef-4aea-8e05-2de555786989 · outbound

This paper cites Gtg-shapley: Efficient and accurate participant contribution evaluation in federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Gtg-shapley: Efficient and accurate participant contribution evaluation in federated learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:02.031555Z

Source-reported events for the cited work

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Observation 7472da60-6965-4b1f-8751-9f0396755fd5 · outbound

This paper cites Towards efficient data valuation based on the shapley value,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Towards efficient data valuation based on the shapley value,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:01.867097Z

Source-reported events for the cited work

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Observation 2bfadb16-1ff7-433a-9d27-4c1b3b594151 · outbound

This paper cites Towards understanding biased client selection in federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Towards understanding biased client selection in federated learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:01.589696Z

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Observation 18c1ea0a-cc6a-499d-86d7-e1eb78f9d510 · outbound

This paper cites Fedfast: Going beyond average for faster training of federated recommender systems,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Fedfast: Going beyond average for faster training of federated recommender systems,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:01.350578Z

Source-reported events for the cited work

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Observation eb6d155e-28ac-457a-b7a3-15f96faee3c2 · outbound

This paper cites Refrs: Resource-efficient federated recommender system for dynamic and diversified user preferences,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Refrs: Resource-efficient federated recommender system for dynamic and diversified user preferences,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:01.144683Z

Source-reported events for the cited work

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Observation 9d283101-6dcc-405a-9c1c-5f2d8022e46e · outbound

This paper cites Personalized federated recommendation via joint representation learning, user clustering, and model adaptation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Personalized federated recommendation via joint representation learning, user clustering, and model adaptation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:00.910764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 89c41766-031e-4824-a454-d80621c7f5bf · outbound

This paper cites Bandit-based communication-efficient client selection strategies for federated learn- ing,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Bandit-based communication-efficient client selection strategies for federated learn- ing,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:00.732411Z

Source-reported events for the cited work

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Observation ba8df257-6f9a-4b1c-acc5-52fba5575859 · outbound

This paper cites Joint client selection and bandwidth allocation algorithm for federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Joint client selection and bandwidth allocation algorithm for federated learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:00.528768Z

Source-reported events for the cited work

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Observation acf72a22-ac7c-4bc2-9879-f4a71347ca1d · outbound

This paper cites Deep-reinforcement-learning-assisted client selection in nonorthogonal- multiple-access-based federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Deep-reinforcement-learning-assisted client selection in nonorthogonal- multiple-access-based federated learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:00.316628Z

Source-reported events for the cited work

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Observation 08ef6c24-2cea-4629-af4c-ad15af5b5f2f · outbound

This paper cites A multi-agent reinforcement learning approach for efficient client selection in federated learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A multi-agent reinforcement learning approach for efficient client selection in federated learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:34:00.080928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 24e1a856-4be6-46c8-8de2-8081b920a622 · outbound

This paper cites Reinforce- ment active client selection for federated heterogeneous graph learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Reinforce- ment active client selection for federated heterogeneous graph learning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:59.876255Z

Source-reported events for the cited work

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Observation 8c78fbf7-6ab9-4254-8fa0-e0b3193866eb · outbound

This paper cites The movielens datasets: History and context,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation The movielens datasets: History and context,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:59.660606Z

Source-reported events for the cited work

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Observation 4e8d9b14-923c-4fc0-ae4d-4ffc79cf47aa · outbound

This paper cites Federated neural collaborative filter- ing,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Federated neural collaborative filter- ing,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:59.468297Z

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Observation 4654d2bd-80ab-4c7e-a0f5-55f2c839a1d6 · outbound

This paper cites Fedrl: a reinforcement learning federated recommender system for efficient com- munication using reinforcement selector and hypernet generator,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Fedrl: a reinforcement learning federated recommender system for efficient com- munication using reinforcement selector and hypernet generator,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:59.224802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2a2327cc-4b42-4fac-a868-373cc98f24e4 · outbound

This paper cites Neural col- laborative filtering,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Neural col- laborative filtering,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:59.007559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 30c89776-9afe-4eb2-98ef-48c516fd9ebb · outbound

This paper cites Personalized item repre- sentations in federated multimodal recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Personalized item repre- sentations in federated multimodal recommendation,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:51.731546Z

Source-reported events for the cited work

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Observation ea801a05-bdd9-4ea1-9ac3-083e6d2f18c8 · outbound

This paper cites Gpfedrec: Graph-guided personalization for federated recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Gpfedrec: Graph-guided personalization for federated recommendation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:58.756575Z

Source-reported events for the cited work

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Observation 3dc49fd7-171c-4c44-997a-ab88baa55afb · outbound

This paper cites When federated recommendation meets cold-start problem: Separating item attributes and user interactions,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation When federated recommendation meets cold-start problem: Separating item attributes and user interactions,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:58.580792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 828d34cd-f77f-42a3-8dd2-a3d1cd96a104 · outbound

This paper cites Deckg: Decentralized collaborative learning with knowledge graph enhancement for poi recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Deckg: Decentralized collaborative learning with knowledge graph enhancement for poi recommendation,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:58.365726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 98307448-8efe-45bf-9026-0b746ac40864 · outbound

This paper cites Robust federated contrastive recommender system against targeted model poisoning attack,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Robust federated contrastive recommender system against targeted model poisoning attack,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:58.144854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 164e6226-5c9d-4cf4-9e77-cf64c9c951be · outbound

This paper cites Ptf- fsr: A parameter transmission-free federated sequential recommender system,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Ptf- fsr: A parameter transmission-free federated sequential recommender system,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:57.844669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 19a6b10d-1fc2-45c4-97ed-3fcf5007dc50 · outbound

This paper cites Pdc-frs: Privacy-preserving data contribution for federated recommender system,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Pdc-frs: Privacy-preserving data contribution for federated recommender system,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:57.662397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cc552b8f-fc4d-4dd0-9bc7-035d018dc3bd · outbound

This paper cites Robust Federated Contrastive Recommender System against Model Poisoning Attack.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Robust Federated Contrastive Recommender System against Model Poisoning Attack

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:33:54.429404Z

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Observation 2379b5e9-7740-4771-b153-78f5cee3dba1 · outbound

This paper cites Towards personalized privacy: User-governed data contribution for federated recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Towards personalized privacy: User-governed data contribution for federated recommendation,

Reference 40

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Source-reported events for the cited work

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Observation 107d171d-2c3a-4f4e-95d1-7e4ff6f58330 · outbound

This paper cites Semi-decentralized federated ego graph learning for recom- mendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Semi-decentralized federated ego graph learning for recom- mendation,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:57.428069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 043bbab2-5408-4f9d-8527-922c551724cd · outbound

This paper cites Hide your model: A parameter transmission-free federated recommender system,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Hide your model: A parameter transmission-free federated recommender system,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:57.155349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 51d647c4-232d-44ac-b7dc-4c5fd960edaa · outbound

This paper cites Hetefedrec: Federated recommender systems with model heterogeneity,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Hetefedrec: Federated recommender systems with model heterogeneity,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:56.827224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4e089846-e119-4589-82dc-9a179b7a3635 · outbound

This paper cites Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:52.671861Z

Source-reported events for the cited work

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Observation 73861e62-9d5e-46ab-b59c-10b2953953c9 · outbound

This paper cites FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation FedGNN: Federated Graph Neural Network for Privacy-Preserving Recommendation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:52.759304Z

Source-reported events for the cited work

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Observation c21d05f4-ca45-4756-a5ba-8099189bc235 · outbound

This paper cites Feddsr: Daily schedule recommendation in a federated deep reinforcement learning framework,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Feddsr: Daily schedule recommendation in a federated deep reinforcement learning framework,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:56.564447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 04b6c574-8eca-4294-9ea8-18d035e13c8a · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Communication-efficient learning of deep networks from decentralized data,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:52.921608Z

Source-reported events for the cited work

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Observation 34906c70-0650-4092-bf7e-3c6bf5b99c0b · outbound

This paper cites Fedgst: An efficient federated graph neural network for spatio-temporal poi recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Fedgst: An efficient federated graph neural network for spatio-temporal poi recommendation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:56.357408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c92ac2b4-fbff-4dc6-afba-6c3aab3f98b2 · outbound

This paper cites Fedacs: An adaptive client selection framework for communication-efficient federated graph learning,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Fedacs: An adaptive client selection framework for communication-efficient federated graph learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:56.114753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ced727fa-358a-4cee-9c02-2156195eea55 · outbound

This paper cites Ldp-fed: Federated learning with local differential privacy,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Ldp-fed: Federated learning with local differential privacy,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:55.872827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b6c865c8-adb3-4a58-943b-dbe3fa93e541 · outbound

This paper cites BPR: Bayesian Personalized Ranking from Implicit Feedback.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation BPR: Bayesian Personalized Ranking from Implicit Feedback

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:53.223706Z

Source-reported events for the cited work

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Observation 16e2c85b-e8de-4a4c-b11c-e056b4c92302 · outbound

This paper cites Addressing function approxi- mation error in actor-critic methods,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Addressing function approxi- mation error in actor-critic methods,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:53.271536Z

Source-reported events for the cited work

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Observation 11e3ee39-941c-4715-bf1c-ea353fe2cb9c · outbound

This paper cites Justifying recommendations using distantly-labeled reviews and fine-grained aspects,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Justifying recommendations using distantly-labeled reviews and fine-grained aspects,

Reference 53

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Observation 7a9fd9f2-4a81-433c-b439-c156449ca81c · outbound

This paper cites Secure federated matrix factorization,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Secure federated matrix factorization,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:55.680783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 91acd44c-7662-495d-8493-9ff58fd1a7c8 · outbound

This paper cites Dual personalization on federated recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Dual personalization on federated recommendation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:55.467521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dce34f20-bf49-41f4-88ca-ff81acc6ac1d · outbound

This paper cites A federated graph neural network framework for privacy-preserving personalization,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation A federated graph neural network framework for privacy-preserving personalization,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:55.279340Z

Source-reported events for the cited work

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Observation ba9ed778-ee73-46c5-8cbc-d3c0b3b1ac99 · outbound

This paper cites Bars: Towards open benchmarking for recommender systems,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Bars: Towards open benchmarking for recommender systems,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:55.074474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ba4c4998-ca13-4d16-bb05-195fd326eccc · outbound

This paper cites Understanding the difficulty of training deep feedforward neural networks,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Understanding the difficulty of training deep feedforward neural networks,

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T20:33:53.714904Z

Source-reported events for the cited work

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Observation 04d574a6-ae38-4505-9b47-52aedbec4493 · outbound

This paper cites Efficient multimodal streaming recommendation via expandable side mixture-of- experts,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Efficient multimodal streaming recommendation via expandable side mixture-of- experts,

Reference 59

Resolution: verified exact; raw_fallback, observed 2026-08-05T20:33:54.207203Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 38742861-61dd-47f3-a058-b319f0dc8d9e · outbound

This paper cites Scalable dynamic embedding size search for streaming recommendation,.

Proxy Model-Guided Reinforcement Learning for Client Selection in Federated Recommendation Scalable dynamic embedding size search for streaming recommendation,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:33:54.892515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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