Image de couverture de livre

UTBoost: Gradient Boosted Decision Trees for Uplift Modeling

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Gao, Junjie, Zheng, Xiangyu, Wang, DongDong, Huang, Zhixiang, Zheng, Bangqi, Yang, Kai
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

SecureBoost+: Large Scale and High-Performance Vertical Federated Gradient Boosting Decision Tree
par: Fan, Tao, et autres
Publié: (2021)

Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization
par: Sun, Zexu, et autres
Publié: (2023)

Entire Chain Uplift Modeling with Context-Enhanced Learning for Intelligent Marketing
par: Huang, Yinqiu, et autres
Publié: (2024)

Uplift Modeling Under Limited Supervision
par: Panagopoulos, George, et autres
Publié: (2024)

Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers
par: Yan, Kai, et autres
Publié: (2024)

GreenTEA: Gradient Descent with Topic-modeling and Evolutionary Auto-prompting
par: Dong, Zheng, et autres
Publié: (2025)

Online Gradient Boosting Decision Tree: In-Place Updates for Efficient Adding/Deleting Data
par: Lin, Huawei, et autres
Publié: (2025)

Supervised Score-Based Modeling by Gradient Boosting
par: Zhao, Changyuan, et autres
Publié: (2024)

Pocket Foundation Models: Distilling TFMs into CPU-Ready Gradient-Boosted Trees
par: Tanna, Aditya, et autres
Publié: (2026)

Vanilla Gradient Descent for Oblique Decision Trees
par: Panda, Subrat Prasad, et autres
Publié: (2024)

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
par: Dong, Xiangyu, et autres
Publié: (2023)

FracAug: Fractional Augmentation boost Graph-level Anomaly Detection under Limited Supervision
par: Dong, Xiangyu, et autres
Publié: (2025)

A Rectification-Based Approach for Distilling Boosted Trees into Decision Trees
par: Audemard, Gilles, et autres
Publié: (2025)

CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making
par: Dong, Zibin, et autres
Publié: (2024)

Gradient Boosting Reinforcement Learning
par: Fuhrer, Benjamin, et autres
Publié: (2024)

Fairness Evaluation for Uplift Modeling in the Absence of Ground Truth
par: Kadioglu, Serdar, et autres
Publié: (2024)

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent
par: Marton, Sascha, et autres
Publié: (2023)

Policy Gradient for Robust Markov Decision Processes
par: Wang, Qiuhao, et autres
Publié: (2024)

Enhancing DP-SGD through Non-monotonous Adaptive Scaling Gradient Weight
par: Huang, Tao, et autres
Publié: (2024)

AXIL: Exact Instance Attribution for Gradient Boosting
par: Geertsema, Paul, et autres
Publié: (2023)

Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
par: Huang, Zhehao, et autres
Publié: (2024)

MODULI: Unlocking Preference Generalization via Diffusion Models for Offline Multi-Objective Reinforcement Learning
par: Yuan, Yifu, et autres
Publié: (2024)

Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing
par: Sun, Zexu, et autres
Publié: (2025)

Multi-Treatment Multi-Task Uplift Modeling for Enhancing User Growth
par: Wei, Yuxiang, et autres
Publié: (2024)

Beyond Autoregressive RTG: Conditioning via Injection Outside Sequential Modeling in Decision Transformer
par: Wang, Yongyi, et autres
Publié: (2026)

Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation
par: Dai, Juntao, et autres
Publié: (2024)

XGrad: Boosting Gradient-Based Optimizers With Weight Prediction
par: Guan, Lei, et autres
Publié: (2023)

Gradient Boosting within a Single Attention Layer
par: Sargolzaei, Saleh
Publié: (2026)

FPBoost: Fully Parametric Gradient Boosting for Survival Analysis
par: Archetti, Alberto, et autres
Publié: (2024)

Muon$^2$: Boosting Muon via Adaptive Second-Moment Preconditioning
par: Liu, Ziyue, et autres
Publié: (2026)

Boosting LLM Reasoning via Human-Inspired Reward Shaping
par: Lin, Wenze, et autres
Publié: (2026)

Boosting Maximum Entropy Reinforcement Learning via One-Step Flow Matching
par: Li, Zeqiao, et autres
Publié: (2026)

Generative Models in Decision Making: A Survey
par: Shao, Xinyu, et autres
Publié: (2025)

Enhancing Uplift Modeling in Multi-Treatment Marketing Campaigns: Leveraging Score Ranking and Calibration Techniques
par: Park, Yoon Tae, et autres
Publié: (2024)

Adjusting the Output of Decision Transformer with Action Gradient
par: Lin, Rui, et autres
Publié: (2025)

Gradient Boosting Trees and Large Language Models for Tabular Data Few-Shot Learning
par: Huertas, Carlos
Publié: (2024)

Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes
par: Morimura, Tetsuro, et autres
Publié: (2022)

Boosting Large Language Models with Mask Fine-Tuning
par: Zhang, Mingyuan, et autres
Publié: (2025)

Decision Potential Surface: A Theoretical and Practical Approximation of Large Language Model Decision Boundary
par: Liang, Zi, et autres
Publié: (2025)

Should We Ever Prefer Decision Transformer for Offline Reinforcement Learning?
par: Omori, Yumi, et autres
Publié: (2025)