ResearchTrend.AI
PASTO: Strategic Parameter Optimization in Recommendation Systems -- Probabilistic is Better than Deterministic

PASTO: Strategic Parameter Optimization in Recommendation Systems -- Probabilistic is Better than Deterministic

Weicong Ding
Hanlin Tang
Jingshuo Feng
Lei Yuan
Sen Yang
Guangxu Yang
Jie Zheng
Jing Wang
Qiang Su
Dong Zheng
Xue-Bo Qiu
Yongqiang Liu
Yuxuan Chen
Yang Liu
Chao Song
Dongying Kong
Kai Ren
Peng Jiang
Qiao Lian
Ji Liu
ArXivPDFHTML

Papers citing "PASTO: Strategic Parameter Optimization in Recommendation Systems -- Probabilistic is Better than Deterministic"

2 / 2 papers shown
Title
Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
Syrine Belakaria
Aryan Deshwal
J. Doppa
47
131
0
01 Sep 2020
Multi-Gradient Descent for Multi-Objective Recommender Systems
Multi-Gradient Descent for Multi-Objective Recommender Systems
Nikola Milojković
Diego Antognini
Giancarlo Bergamin
Boi Faltings
C. Musat
37
46
0
09 Dec 2019

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.