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Field-aware Calibration: A Simple and Empirically Strong Method for
  Reliable Probabilistic Predictions

Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions

26 May 2019
Feiyang Pan
Xiang Ao
Pingzhong Tang
Min Lu
Dapeng Liu
Lei Xiao
Qing He
ArXivPDFHTML

Papers citing "Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions"

4 / 4 papers shown
Title
FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical
  Federated Learning
FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning
Penghui Wei
Hongjian Dou
Shaoguo Liu
Rong Tang
Li Liu
Liangji Wang
Bo Zheng
FedML
24
12
0
15 May 2023
Variable-Based Calibration for Machine Learning Classifiers
Variable-Based Calibration for Machine Learning Classifiers
Mark Kelly
Padhraic Smyth
19
4
0
30 Sep 2022
A Unified Framework for Campaign Performance Forecasting in Online
  Display Advertising
A Unified Framework for Campaign Performance Forecasting in Online Display Advertising
Jun Chen
Cheng Chen
Huayue Zhang
Qing Tan
8
2
0
24 Feb 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
1