ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1411.6591
  4. Cited By
A Latent Source Model for Online Collaborative Filtering

A Latent Source Model for Online Collaborative Filtering

31 October 2014
Guy Bresler
George H. Chen
Devavrat Shah
    FedML
ArXiv (abs)PDFHTML

Papers citing "A Latent Source Model for Online Collaborative Filtering"

19 / 19 papers shown
Title
Explaining the Success of Nearest Neighbor Methods in Prediction
George H. Chen
Devavrat Shah
OOD
600
148
0
21 Feb 2025
Adversarial Online Collaborative Filtering
Adversarial Online Collaborative Filtering
Stephen Pasteris
Fabio Vitale
Mark Herbster
Claudio Gentile
Andre' Panisson
80
0
0
11 Feb 2023
Optimal Algorithms for Latent Bandits with Cluster Structure
Optimal Algorithms for Latent Bandits with Cluster Structure
S. Pal
A. Suggala
Karthikeyan Shanmugam
Prateek Jain
74
9
0
17 Jan 2023
Online Low Rank Matrix Completion
Online Low Rank Matrix Completion
Prateek Jain
S. Pal
66
9
0
08 Sep 2022
Learning User Preferences in Non-Stationary Environments
Learning User Preferences in Non-Stationary Environments
Wasim Huleihel
S. Pal
O. Shayevitz
119
13
0
29 Jan 2021
Regret in Online Recommendation Systems
Regret in Online Recommendation Systems
Kaito Ariu
Narae Ryu
Seyoung Yun
Alexandre Proutiere
60
6
0
23 Oct 2020
Machine Learning in/for Blockchain: Future and Challenges
Machine Learning in/for Blockchain: Future and Challenges
Fang Chen
Hong Wan
Hua Cai
Guangquan Cheng
90
39
0
12 Sep 2019
Introduction to Multi-Armed Bandits
Introduction to Multi-Armed Bandits
Aleksandrs Slivkins
677
1,024
0
15 Apr 2019
Active Learning in Recommendation Systems with Multi-level User
  Preferences
Active Learning in Recommendation Systems with Multi-level User Preferences
Yuheng Bu
Kevin Small
78
5
0
30 Nov 2018
Regret vs. Bandwidth Trade-off for Recommendation Systems
Regret vs. Bandwidth Trade-off for Recommendation Systems
Linqi Song
Christina Fragouli
Devavrat Shah
20
1
0
15 Oct 2018
Scalable Recommender Systems through Recursive Evidence Chains
Scalable Recommender Systems through Recursive Evidence Chains
Elias Tragas
Calvin Luo
Maxime Gazeau
Kevin Luk
David Duvenaud
LRM
25
1
0
05 Jul 2018
Regret Bounds and Regimes of Optimality for User-User and Item-Item
  Collaborative Filtering
Regret Bounds and Regimes of Optimality for User-User and Item-Item Collaborative Filtering
Guy Bresler
Mina Karzand
167
14
0
06 Nov 2017
The Sample Complexity of Online One-Class Collaborative Filtering
The Sample Complexity of Online One-Class Collaborative Filtering
Reinhard Heckel
Kannan Ramchandran
55
17
0
31 May 2017
Nearest Neighbors for Matrix Estimation Interpreted as Blind Regression
  for Latent Variable Model
Nearest Neighbors for Matrix Estimation Interpreted as Blind Regression for Latent Variable Model
Yihua Li
Devavrat Shah
Dogyoon Song
Chao Yu
400
23
0
13 May 2017
Boolean kernels for collaborative filtering in top-N item recommendation
Boolean kernels for collaborative filtering in top-N item recommendation
Mirko Polato
F. Aiolli
41
21
0
21 Dec 2016
Low-rank Bandits with Latent Mixtures
Low-rank Bandits with Latent Mixtures
Aditya Gopalan
Odalric-Ambrym Maillard
Mohammadi Zaki
121
28
0
06 Sep 2016
Context-Aware Bandits
Shuai Li
Purushottam Kar
72
13
0
12 Oct 2015
Regret Guarantees for Item-Item Collaborative Filtering
Regret Guarantees for Item-Item Collaborative Filtering
Guy Bresler
Devavrat Shah
L. Voloch
257
29
0
20 Jul 2015
Bayesian regression and Bitcoin
Bayesian regression and Bitcoin
Devavrat Shah
Kang Zhang
47
160
0
06 Oct 2014
1