Uncertainty in Gradient Boosting via Ensembles

18 June 2020

Aleksei Ustimenko

Liudmila Prokhorenkova

A. Malinin

UQCV

ArXiv PDF HTML

Papers citing "Uncertainty in Gradient Boosting via Ensembles"

48 / 48 papers shown

Title
Efficient Membership Inference Attacks by Bayesian Neural Network Zhenlong Liu Wenyu Jiang Feng Zhou Hongxin Wei MIALM 66 1 0 10 Mar 2025
Position Specific Scoring Is All You Need? Revisiting Protein Sequence Classification Tasks Sarwan Ali Taslim Murad Prakash Chourasia Haris Mansoor I. Khan Pin-Yu Chen Murray Patterson 26 1 0 16 Oct 2024
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs Ruijia Niu D. Wu Rose Yu Yi-An Ma 28 1 0 09 Oct 2024
Advancing Molecular Machine (Learned) Representations with Stereoelectronics-Infused Molecular Graphs Daniil A. Boiko Thiago Reschutzegger Benjamín Sánchez-Lengeling Samuel M. Blau Gabe Gomes GNN AI4CE 23 1 0 08 Aug 2024
Gradient Boosting Reinforcement Learning Benjamin Fuhrer Chen Tessler Gal Dalal OffRL AI4CE 44 3 0 11 Jul 2024
Regularized KL-Divergence for Well-Defined Function-Space Variational Inference in Bayesian neural networks Tristan Cinquin Robert Bamler UQCV BDL 38 2 0 06 Jun 2024
Diffusion Boosted Trees Xizewen Han Mingyuan Zhou AI4CE 36 0 0 03 Jun 2024
SEMF: Supervised Expectation-Maximization Framework for Predicting Intervals Ilia Azizi M. Boldi V. Chavez-Demoulin 95 0 0 28 May 2024
ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing Kiran Madhusudhanan Gunnar Behrens Maximilian Stubbemann Lars Schmidt-Thieme 20 0 0 06 Mar 2024
Embracing Uncertainty Flexibility: Harnessing a Supervised Tree Kernel to Empower Ensemble Modelling for 2D Echocardiography-Based Prediction of Right Ventricular Volume T. A. Bohoran P. Kampaktsis Laura McLaughlin Jay Leb Gerry P. McCann A. Giannakidis 25 1 0 04 Mar 2024
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles Oleksandr Balabanov H. Linander UQCV 28 13 0 19 Feb 2024
SeqNAS: Neural Architecture Search for Event Sequence Classification Igor Udovichenko Egor Shvetsov Denis Divitsky Dmitry Osin I. Trofimov Anatoliy Glushenko I. Sukharev Dmitry Berestnev E. Burnaev 23 6 0 06 Jan 2024
SE(3)-Invariant Multiparameter Persistent Homology for Chiral-Sensitive Molecular Property Prediction Andac Demir Francis Prael B. Kiziltan 19 2 0 12 Dec 2023
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling Bairu Hou Yujian Liu Kaizhi Qian Jacob Andreas Shiyu Chang Yang Zhang UD UQCV PER 21 48 0 15 Nov 2023
Model Uncertainty based Active Learning on Tabular Data using Boosted Trees Sharath M Shankaranarayana 27 0 0 30 Oct 2023
Improving Opioid Use Disorder Risk Modelling through Behavioral and Genetic Feature Integration Sybille Légitime Kaustubh Prabhu Devin J. McConnell Bing Wang D. Dey Derek Aguiar 12 0 0 19 Sep 2023
Correcting sampling biases via importance reweighting for spatial modeling Boris Prokhorov Diana Koldasbayeva Alexey Zaytsev 11 0 0 09 Sep 2023
Machine-Learning Solutions for the Analysis of Single-Particle Diffusion Trajectories Henrik Seckler J. Szwabiński Ralf Metzler 19 25 0 18 Aug 2023
Identifying contributors to supply chain outcomes in a multi-echelon setting: a decentralised approach Stefan Schoepf Jack Foster Alexandra Brintrup 19 1 0 22 Jul 2023
Prescriptive Process Monitoring Under Resource Constraints: A Reinforcement Learning Approach Mahmoud Shoush Marlon Dumas 29 1 0 13 Jul 2023
Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit O. Fitzgerald O. Perez-Concha B. Gallego-Luxan Alejandro Metke-Jimenez Lachlan Rudd Louisa R Jorm BDL OOD AI4TS 22 0 0 14 Apr 2023
Variational Boosted Soft Trees Tristan Cinquin Tammo Rukat Philipp Schmidt Martin Wistuba Artur Bekasov BDL UQCV 16 0 0 21 Feb 2023
Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean Anton Thielmann René-Marcel Kruse Thomas Kneib Benjamin Säfken 24 12 0 27 Jan 2023
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty Yugo Fujimotol Kei Nakagawa Kentaro Imajo Kentaro Minami AIFin 30 3 0 31 Oct 2022
Uncertainty in Extreme Multi-label Classification Jyun-Yu Jiang Wei-Cheng Chang Jiong Zhong Cho-Jui Hsieh Hsiang-Fu Yu UQCV 14 0 0 18 Oct 2022
Towards Clear Expectations for Uncertainty Estimation Victor Bouvier Simona Maggio A. Abraham L. Dreyfus-Schmidt UQCV 25 1 0 27 Jul 2022
Benchmarking Machine Learning Robustness in Covid-19 Genome Sequence Classification Sarwan Ali Bikram Sahoo Alexander Zelikovskiy Pin-Yu Chen Murray Patterson OOD AAML 22 19 0 18 Jul 2022
Uncertainty-Aware Mixed-Variable Machine Learning for Materials Design Hengrui Zhang WeiWayneChen Akshay Iyer D. Apley Wei-Neng Chen AI4CE 31 11 0 11 Jul 2022
When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraints Mahmoud Shoush Marlon Dumas 30 12 0 15 Jun 2022
Confident Sinkhorn Allocation for Pseudo-Labeling Vu-Linh Nguyen Hisham Husain S. Farfade A. Hengel 25 5 0 13 Jun 2022
Gradient Boosting Performs Gaussian Process Inference Aleksei Ustimenko Artem Beliakov Liudmila Prokhorenkova BDL 20 5 0 11 Jun 2022
TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression Patryk Wielopolski Maciej Ziȩba UQCV 17 1 0 08 Jun 2022
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees Jonathan Brophy Daniel Lowd 26 10 0 23 May 2022
On the Calibration of Probabilistic Classifier Sets Thomas Mortier Viktor Bengs Eyke Hüllermeier Stijn Luca Willem Waegeman UQCV 19 7 0 20 May 2022
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees Jonathan Brophy Zayd Hammoudeh Daniel Lowd TDI 19 22 0 30 Apr 2022
Probabilistic Models for Manufacturing Lead Times Recep Yusuf Bekci Yacine Mahdid Jinling Xing Nikita Letov Ying Zhang Zahid Pasha 14 0 0 28 Apr 2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization Jungtaek Kim Seungjin Choi 22 5 0 22 Feb 2022
Sketching stochastic valuation functions M. C. Yiliu Wang 17 0 0 01 Feb 2022
More layers! End-to-end regression and uncertainty on tabular data with deep learning Ivan Bondarenko OOD LMTD UQCV 17 4 0 07 Dec 2021
Evaluating Predictive Uncertainty and Robustness to Distributional Shift Using Real World Data Kumud Lakara Akshat Bhandari Pratinav Seth Ujjwal Verma OOD 19 3 0 08 Nov 2021
Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning Preethi Lahoti Krishna P. Gummadi G. Weikum 26 3 0 09 Sep 2021
Look Before You Leap! Designing a Human-Centered AI System for Change Risk Assessment Binay Gupta Anirban Chatterjee Harika Matha Kunal Banerjee Lalitdutt Parsai Vijay Srinivas Agneeswaran 19 2 0 18 Aug 2021
Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning Naichen Shi Fan Lai Raed Al Kontar Mosharaf Chowdhury FedML 23 35 0 21 Jul 2021
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks A. Malinin Neil Band Ganshin Alexander German Chesnokov ... Roginskiy Denis Mariya Shmatova Panos Tigas Boris Yangel UQCV OOD 25 126 0 15 Jul 2021
Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings U. Sarawgi Rishab Khincha W. Zulfikar Satrajit S. Ghosh Pattie Maes UQCV 25 7 0 21 Apr 2021
SGLB: Stochastic Gradient Langevin Boosting Aleksei Ustimenko Liudmila Prokhorenkova 11 19 0 20 Jan 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 282 9,136 0 06 Jun 2015