Cover Image

Don't Explain Noise: Robust Counterfactuals for Randomized Ensembles

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Forel, Alexandre, Parmentier, Axel, Vidal, Thibaut
Format:	Preprint
Published:	2022
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DistrictNet: Decision-aware learning for geographical districting
by: Ahmed, Cheikh, et al.
Published: (2024)

Free Lunch in the Forest: Functionally-Identical Pruning of Boosted Tree Ensembles
by: Emine, Youssouf, et al.
Published: (2024)

Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet Control
by: Jungel, Kai, et al.
Published: (2023)

A Survey of Contextual Optimization Methods for Decision Making under Uncertainty
by: Sadana, Utsav, et al.
Published: (2023)

CF-OPT: Counterfactual Explanations for Structured Prediction
by: Vivier-Ardisson, Germain, et al.
Published: (2024)

PACE: Prune-And-Compress Ensemble Models
by: Akkerman, Fabian, et al.
Published: (2026)

Don't Be Greedy, Just Relax! Pruning LLMs via Frank-Wolfe
by: Roux, Christophe, et al.
Published: (2025)

The Differentiable Feasibility Pump
by: Cacciola, Matteo, et al.
Published: (2024)

Adaptive Partitioning for Chance-Constrained Problems with Finite Support
by: Roland, Marius, et al.
Published: (2023)

Don't Be So Positive: Negative Step Sizes in Second-Order Methods
by: Shea, Betty, et al.
Published: (2024)

Primal-dual algorithm for contextual stochastic combinatorial optimization
by: Bouvier, Louis, et al.
Published: (2025)

Contextual Stochastic Vehicle Routing with Time Windows
by: Serrano, Breno, et al.
Published: (2024)

Predicting Accurate Lagrangian Multipliers for Mixed Integer Linear Programs
by: Demelas, Francesco, et al.
Published: (2023)

Preference-aware compensation policies for crowdsourced on-demand services
by: Nouli, Georgina, et al.
Published: (2025)

Combinatorial Optimization Augmented Machine Learning
by: Schiffer, Maximilian, et al.
Published: (2026)

Structured Reinforcement Learning for Combinatorial Decision-Making
by: Hoppe, Heiko, et al.
Published: (2025)

The Branch-and-Bound Tree Closure
by: Roland, Marius, et al.
Published: (2025)

Single- vs. Dual-Policy Reinforcement Learning for Dynamic Bike Rebalancing
by: Liang, Jiaqi, et al.
Published: (2024)

Can Learning Be Explained By Local Optimality In Robust Low-rank Matrix Recovery?
by: Ma, Jianhao, et al.
Published: (2023)

SHANG++: Robust Stochastic Acceleration under Multiplicative Noise
by: Yu, Yaxin, et al.
Published: (2026)

Muon with Nesterov Momentum: Heavy-Tailed Noise and (Randomized) Inexact Polar Decomposition
by: Choudhury, Sayantan, et al.
Published: (2026)

Counterfactual Explanations for Linear Optimization
by: Kurtz, Jannis, et al.
Published: (2024)

S-CFE: Simple Counterfactual Explanations
by: Sadiku, Shpresim, et al.
Published: (2024)

Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural Networks
by: Bernardelli, Ambrogio Maria, et al.
Published: (2022)

Outlier-Robust Linear System Identification Under Heavy-tailed Noise
by: Kanakeri, Vinay, et al.
Published: (2024)

Supervised Feature Compression based on Counterfactual Analysis
by: Piccialli, Veronica, et al.
Published: (2022)

Malliavin Calculus with Weak Derivatives for Counterfactual Stochastic Optimization
by: Krishnamurthy, Vikram, et al.
Published: (2025)

Linear Model Extraction via Factual and Counterfactual Queries
by: Otto, Daan, et al.
Published: (2026)

Gap Safe Screening Rules for Fast Training of Robust Support Vector Machines under Feature Noise
by: Nguyen, Tan-Hau, et al.
Published: (2026)

Going from a Representative Agent to Counterfactuals in Combinatorial Choice
by: Ruan, Yanqiu, et al.
Published: (2025)

Boosting-Enabled Robust System Identification of Partially Observed LTI Systems Under Heavy-Tailed Noise
by: Kanakeri, Vinay, et al.
Published: (2025)

Counterfactual optimization for fault prevention in complex wind energy systems
by: Carrizosa, Emilio, et al.
Published: (2025)

Combinatorial Optimization and Machine Learning for Dynamic Inventory Routing
by: Greif, Toni, et al.
Published: (2024)

Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates
by: Paul, Anik Kumar, et al.
Published: (2026)

Subsampled Ensemble Can Improve Generalization Tail Exponentially
by: Qian, Huajie, et al.
Published: (2024)

A Two-Timescale Primal-Dual Framework for Reinforcement Learning via Online Dual Variable Guidance
by: Wolter, Axel Friedrich, et al.
Published: (2025)

Managing delay in tail assignment: from minimum turn time to stochastic routing at Air France
by: Baty, Léo, et al.
Published: (2026)

Can SGD Handle Heavy-Tailed Noise?
by: Fatkhullin, Ilyas, et al.
Published: (2025)

Provable Mixed-Noise Learning with Flow-Matching
by: Hagemann, Paul, et al.
Published: (2025)

LEVDA: Latent Ensemble Variational Data Assimilation via Differentiable Dynamics
by: Si, Phillip, et al.
Published: (2026)