calibration | BestHub

IT Services Circle

Jul 9, 2024 · Artificial Intelligence

Comparative Study of Classification Algorithms and Calibration Using Synthetic Data

This article presents a comprehensive case study that explains classification principles, shows the key formulas for logistic regression and SVM, and provides a full Python implementation that generates synthetic data, trains multiple classifiers, calibrates them, and visualizes calibration curves and probability histograms.

Machine Learningcalibrationclassification

0 likes · 6 min read

Comparative Study of Classification Algorithms and Calibration Using Synthetic Data

Alimama Tech

Jun 21, 2023 · Artificial Intelligence

Joint Optimization of Ranking and Calibration (JRC) for CTR Prediction

The Joint Optimization of Ranking and Calibration (JRC) model introduces a two‑logit generative‑discriminative architecture that jointly minimizes LogLoss for calibration and a listwise ranking loss, delivering superior GAUC and CTR performance across Alibaba’s display‑ad system, especially for sparse long‑tail users, while remaining simple to train and deploy.

CTR predictionHybrid ModelMachine Learning

0 likes · 18 min read

Joint Optimization of Ranking and Calibration (JRC) for CTR Prediction

Alimama Tech

Mar 14, 2023 · Artificial Intelligence

Bayesian Hierarchical Calibration for Online Advertising Scoring

Bayesian hierarchical calibration applies a lightweight, interpretable Bayesian GLM with variational inference to correct pre‑ and post‑click scoring biases, using risk‑aware objectives that reduce calibration error by up to 66%, lift revenue by 5%, and cut conversion costs, while handling cold‑start and dimension‑wise sparsity in online advertising.

Hierarchical Modeladvertisingbayesian

0 likes · 19 min read

Bayesian Hierarchical Calibration for Online Advertising Scoring

DataFunSummit

Mar 6, 2023 · Artificial Intelligence

Calibration-Based Multi-Task Learning for CVR: Model Design, Experiments, and Future Directions

This article reviews the evolution of CVR multi‑task learning, introduces a representation‑calibration architecture that shares embeddings between CTR and CVR, details four calibration network designs, reports offline and online AUC improvements, and outlines future research on embedding clustering and loss‑level triplet modeling.

A/B testingCVRRecommendation systems

0 likes · 14 min read

Calibration-Based Multi-Task Learning for CVR: Model Design, Experiments, and Future Directions

DataFunTalk

Dec 21, 2022 · Artificial Intelligence

A Comprehensive Overview of Computational Advertising: Architecture, Deep‑Learning Evolution, and Future Directions

This article provides a thorough examination of computational advertising, covering the oCPM pricing model as a superset, classic system architecture, the evolution of core modules such as ad ranking, pacing, bidding, federated learning, calibration, and conversion‑delay handling, and concludes with career advice for algorithm engineers.

Federated Learningad rankingbudget optimization

0 likes · 29 min read

A Comprehensive Overview of Computational Advertising: Architecture, Deep‑Learning Evolution, and Future Directions

Alimama Tech

May 25, 2022 · Artificial Intelligence

AdaCalib: Posterior-Guided Feature-Adaptive Calibration Model for Online Advertising

AdaCalib is a posterior‑guided feature‑adaptive calibration model for online advertising that learns per‑feature piecewise‑linear calibration functions via a deep neural network with adaptive bucketing, improving probability estimates and ranking, achieving lower Field‑RCE, higher AUC, and a 5% CVR lift in live tests.

Deep neural networkscalibrationfeature adaptation

0 likes · 19 min read

AdaCalib: Posterior-Guided Feature-Adaptive Calibration Model for Online Advertising

Alimama Tech

Apr 6, 2022 · Artificial Intelligence

Alibaba's Five Papers Accepted at SIGIR 2022

Alibaba’s research team had five papers accepted at the prestigious SIGIR 2022 conference in Madrid, covering innovations such as joint ad‑ranking and creative selection, personalized bundle generation, calibrated neural predictions, disentangled counterfactual regression, and cold‑start user recommendation, showcasing strong expertise in information retrieval and online advertising.

Recommendation systemsSIGIR 2022calibration

0 likes · 8 min read

Alibaba's Five Papers Accepted at SIGIR 2022

Alimama Tech

Feb 9, 2022 · Artificial Intelligence

Alibaba Mama Team Papers Selected for The Web Conference 2023 – Summaries of Five AI Research Works

The Alibaba Mama technical team secured five paper acceptances at The Web Conference 2023, presenting advances in unbiased delayed‑feedback conversion modeling, uncertainty‑regularized knowledge‑distilled CVR debiasing, feature‑aware probability calibration, coordinated two‑stage ad auctions, and scalable decoupled graph neural networks for large‑scale e‑commerce retrieval.

AICVRDelayed Feedback

0 likes · 12 min read

Alibaba Mama Team Papers Selected for The Web Conference 2023 – Summaries of Five AI Research Works

Alimama Tech

Aug 25, 2021 · Artificial Intelligence

Calibration Techniques for User Response Prediction in Online Advertising

Alibaba Mama’s talk explains how calibrated probability models—evolving from simple Platt scaling to Bayesian isotonic regression and real‑time wave‑adjusted variants—improve click‑through and conversion predictions, enabling more accurate bidding, stable auctions, and fairer ad allocation despite data drift and sparsity.

CTR predictionMachine Learningalgorithm

0 likes · 20 min read

Calibration Techniques for User Response Prediction in Online Advertising

DataFunTalk

Aug 9, 2021 · Artificial Intelligence

Calibration Techniques for User Behavior Prediction in Online Advertising: Background, Algorithm Evolution, and Engineering Practice

This article introduces the concept of calibration in trustworthy machine learning, explains why accurate probability estimates are crucial for online advertising, reviews related research and evaluation metrics, and details the evolution of calibration algorithms such as Smoothed Isotonic Regression, Bayes‑SIR, real‑time optimizations, and post‑click conversion models, concluding with engineering deployment and future directions.

Machine Learningalgorithm optimizationcalibration

0 likes · 18 min read

Calibration Techniques for User Behavior Prediction in Online Advertising: Background, Algorithm Evolution, and Engineering Practice

DataFunTalk

May 20, 2021 · Artificial Intelligence

Fundamentals and Nuances of CTR (Click‑Through Rate) Modeling

This article explains the theoretical foundations of CTR modeling, why click‑through rates are intrinsically unpredictable at the micro level, the simplifying assumptions that make binary classification feasible, and how evaluation metrics like AUC, contradictory samples, theoretical AUC bounds, and calibration affect model performance.

AUCMachine Learningadvertising

0 likes · 18 min read

Fundamentals and Nuances of CTR (Click‑Through Rate) Modeling

DataFunTalk

Aug 12, 2019 · Artificial Intelligence

Multi‑Sensor Fusion in Autonomous Driving: Challenges, Prerequisites, and Methods

Pony.ai shares its extensive experience on multi‑sensor perception for autonomous trucks, explaining why sensor fusion is needed, the essential motion‑compensation and calibration steps, and practical camera‑lidar and radar‑lidar fusion techniques that improve detection range and robustness.

CameraLiDARautonomous driving

0 likes · 15 min read

Multi‑Sensor Fusion in Autonomous Driving: Challenges, Prerequisites, and Methods