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"

50 / 59 papers shown

Title
Efficient Membership Inference Attacks by Bayesian Neural Network Zhenlong Liu Wenyu Jiang Feng Zhou Hongxin Wei MIALM 97 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 40 1 0 16 Oct 2024
Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs Ruijia Niu D. Wu Rose Yu Yi-An Ma 70 2 0 09 Oct 2024
Gradient Boosting Reinforcement Learning Benjamin Fuhrer Chen Tessler Gal Dalal OffRL AI4CE 141 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 108 2 0 06 Jun 2024
Diffusion Boosted Trees Xizewen Han Mingyuan Zhou AI4CE 97 0 0 03 Jun 2024
SEMF: Supervised Expectation-Maximization Framework for Predicting Intervals Ilia Azizi M. Boldi V. Chavez-Demoulin 124 0 0 28 May 2024
ProbSAINT: Probabilistic Tabular Regression for Used Car Pricing Kiran Madhusudhanan Gunnar Behrens Maximilian Stubbemann Lars Schmidt-Thieme 59 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 66 1 0 04 Mar 2024
Uncertainty quantification in fine-tuned LLMs using LoRA ensembles Oleksandr Balabanov Hampus Linander UQCV 94 19 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 Evgeny Burnaev 57 7 0 06 Jan 2024
SE(3)-Invariant Multiparameter Persistent Homology for Chiral-Sensitive Molecular Property Prediction Andac Demir Francis Prael B. Kiziltan 80 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 65 61 0 15 Nov 2023
Model Uncertainty based Active Learning on Tabular Data using Boosted Trees Sharath M Shankaranarayana 72 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 55 0 0 19 Sep 2023
Correcting sampling biases via importance reweighting for spatial modeling Boris Prokhorov Diana Koldasbayeva Alexey Zaytsev 54 0 0 09 Sep 2023
Machine-Learning Solutions for the Analysis of Single-Particle Diffusion Trajectories Henrik Seckler J. Szwabiński Ralf Metzler 37 27 0 18 Aug 2023
Identifying contributors to supply chain outcomes in a multi-echelon setting: a decentralised approach Stefan Schoepf Jack Foster Alexandra Brintrup 49 1 0 22 Jul 2023
Prescriptive Process Monitoring Under Resource Constraints: A Reinforcement Learning Approach Mahmoud Shoush Marlon Dumas 62 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 52 0 0 14 Apr 2023
Variational Boosted Soft Trees Tristan Cinquin Tammo Rukat Philipp Schmidt Martin Wistuba Artur Bekasov BDL UQCV 53 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 62 13 0 27 Jan 2023
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty Yugo Fujimotol Kei Nakagawa Kentaro Imajo Kentaro Minami AIFin 63 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 70 0 0 18 Oct 2022
Towards Clear Expectations for Uncertainty Estimation Victor Bouvier Simona Maggio A. Abraham L. Dreyfus-Schmidt UQCV 60 2 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 52 20 0 18 Jul 2022
Uncertainty-Aware Mixed-Variable Machine Learning for Materials Design Hengrui Zhang WeiWayneChen Akshay Iyer D. Apley Wei Chen AI4CE 73 12 0 11 Jul 2022
When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraints Mahmoud Shoush Marlon Dumas 47 13 0 15 Jun 2022
Confident Sinkhorn Allocation for Pseudo-Labeling Vu-Linh Nguyen Hisham Husain S. Farfade Anton Van Den Hengel 65 5 0 13 Jun 2022
Gradient Boosting Performs Gaussian Process Inference Aleksei Ustimenko Artem Beliakov Liudmila Prokhorenkova BDL 68 5 0 11 Jun 2022
TreeFlow: Going beyond Tree-based Gaussian Probabilistic Regression Patryk Wielopolski Maciej Ziȩba UQCV 74 1 0 08 Jun 2022
Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees Jonathan Brophy Daniel Lowd 59 10 0 23 May 2022
On the Calibration of Probabilistic Classifier Sets Thomas Mortier Viktor Bengs Eyke Hüllermeier Stijn Luca Willem Waegeman UQCV 64 7 0 20 May 2022
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees Jonathan Brophy Zayd Hammoudeh Daniel Lowd TDI 97 22 0 30 Apr 2022
Probabilistic Models for Manufacturing Lead Times Recep Yusuf Bekci Yacine Mahdid Jinling Xing Nikita Letov Ying Zhang Zahid Pasha 53 0 0 28 Apr 2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization Jungtaek Kim Seungjin Choi 53 5 0 22 Feb 2022
Sketching stochastic valuation functions M. C. Yiliu Wang 65 0 0 01 Feb 2022
More layers! End-to-end regression and uncertainty on tabular data with deep learning Ivan Bondarenko OOD LMTD UQCV 51 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 55 4 0 08 Nov 2021
Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning Preethi Lahoti Krishna P. Gummadi Gerhard Weikum 54 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 48 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 77 36 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 80 131 0 15 Jul 2021
Uncertainty-Aware Boosted Ensembling in Multi-Modal Settings U. Sarawgi Rishab Khincha W. Zulfikar Satrajit S. Ghosh Pattie Maes UQCV 50 7 0 21 Apr 2021
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 84 319 0 15 Feb 2020
SGLB: Stochastic Gradient Langevin Boosting Aleksei Ustimenko Liudmila Prokhorenkova 57 19 0 20 Jan 2020
NGBoost: Natural Gradient Boosting for Probabilistic Prediction Tony Duan Anand Avati D. Ding Khanh K. Thai S. Basu A. Ng Alejandro Schuler BDL 34 302 0 08 Oct 2019
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning Andreas Kirsch Joost R. van Amersfoort Y. Gal FedML 87 627 0 19 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 167 1,695 0 06 Jun 2019
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness A. Malinin Mark Gales UQCV AAML 67 177 0 31 May 2019