{"total":63,"rows":[{"id":"2103.11251","title":"Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges","created":"2021-03-20","cited_by_count":367,"area":null},{"id":"2211.00541","title":"Logic-Based Explainability in Machine Learning","created":"2022-10-24","cited_by_count":48,"area":null},{"id":"2205.09971","title":"On Tackling Explanation Redundancy in Decision Trees","created":"2022-05-20","cited_by_count":44,"area":null},{"id":"2206.11844","title":"Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features","created":"2022-06-23","cited_by_count":20,"area":null},{"id":"2405.14956","title":"Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning","created":"2024-05-23","cited_by_count":18,"area":"deeprl"},{"id":"2211.14980","title":"Optimal Sparse Regression Trees","created":"2022-11-28","cited_by_count":13,"area":null},{"id":"2305.03515","title":"GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent","created":"2023-05-05","cited_by_count":11,"area":null},{"id":"2401.03451","title":"Optimization Over Trained Neural Networks: Taking a Relaxing Walk","created":"2024-01-07","cited_by_count":10,"area":null},{"id":"2409.12788","title":"Optimal or Greedy Decision Trees? Revisiting their Objectives, Tuning, and Performance","created":"2024-09-19","cited_by_count":9,"area":null},{"id":"2502.15988","title":"Near Optimal Decision Trees in a SPLIT Second","created":"2025-02-21","cited_by_count":8,"area":null},{"id":"2111.08674","title":"Multiclass Optimal Classification Trees with SVM-splits","created":"2021-11-16","cited_by_count":6,"area":null},{"id":"2511.03344","title":"SORTeD Rashomon Sets of Sparse Decision Trees: Anytime Enumeration","created":"2025-11-05","cited_by_count":6,"area":null},{"id":"2309.15312","title":"MAPTree: Beating \"Optimal\" Decision Trees with Bayesian Decision Trees","created":"2023-09-26","cited_by_count":5,"area":null},{"id":"2104.10751","title":"Rule Generation for Classification: Scalability, Interpretability, and Fairness","created":"2021-04-21","cited_by_count":4,"area":null},{"id":"2206.04857","title":"Mixed integer linear optimization formulations for learning optimal binary classification trees","created":"2022-06-10","cited_by_count":4,"area":null},{"id":"2303.01141","title":"DeepSaDe: Learning Neural Networks that Guarantee Domain Constraint Satisfaction","created":"2023-03-02","cited_by_count":4,"area":null},{"id":"2506.14143","title":"Leveraging Predictive Equivalence in Decision Trees","created":"2025-06-17","cited_by_count":4,"area":"lr"},{"id":"2112.00552","title":"SaDe: Learning Models that Provably Satisfy Domain Constraints","created":"2021-12-01","cited_by_count":3,"area":null},{"id":"2306.04423","title":"On Computing Optimal Tree Ensembles","created":"2023-06-07","cited_by_count":3,"area":null},{"id":"2405.15911","title":"Learning accurate and interpretable tree-based models","created":"2024-05-24","cited_by_count":3,"area":null},{"id":"2508.06064","title":"A Generic Complete Anytime Beam Search for Optimal Decision Tree","created":"2025-08-08","cited_by_count":3,"area":null},{"id":"2211.10502","title":"A Mathematical Programming Approach to Optimal Classification Forests","created":"2022-11-18","cited_by_count":2,"area":null},{"id":"2307.15691","title":"ODTlearn: A Package for Learning Optimal Decision Trees for Prediction and Prescription","created":"2023-07-28","cited_by_count":2,"area":null},{"id":"2310.01551","title":"Harnessing the Power of Choices in Decision Tree Learning","created":"2023-10-02","cited_by_count":2,"area":null},{"id":"2503.06985","title":"Learning Decision Trees as Amortized Structure Inference","created":"2025-03-10","cited_by_count":2,"area":null},{"id":"2601.14765","title":"Anytime Optimal Decision Tree Learning with Continuous Features","created":"2026-01-21","cited_by_count":2,"area":null},{"id":"2209.07575","title":"A Nested Genetic Algorithm for Explaining Classification Data Sets with Decision Rules","created":"2022-08-23","cited_by_count":1,"area":null},{"id":"2210.06825","title":"Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design","created":"2022-10-13","cited_by_count":1,"area":null},{"id":"2409.03260","title":"In Search of Trees: Decision-Tree Policy Synthesis for Black-Box Systems via Search","created":"2024-09-05","cited_by_count":1,"area":null},{"id":"2410.01588","title":"DynFrs: An Efficient Framework for Machine Unlearning in Random Forest","created":"2024-10-02","cited_by_count":1,"area":"safety"},{"id":"2502.19502","title":"Models That Are Interpretable But Not Transparent","created":"2025-02-26","cited_by_count":1,"area":null},{"id":"2503.01455","title":"Proper decision trees: An axiomatic framework for solving optimal decision tree problems with arbitrary splitting rules","created":"2025-03-03","cited_by_count":1,"area":null},{"id":"2503.03576","title":"Optimal Decision Tree Pruning Revisited: Algorithms and Complexity","created":"2025-03-05","cited_by_count":1,"area":null},{"id":"2507.18242","title":"Boosting Revisited: Benchmarking and Advancing LP-Based Ensemble Methods","created":"2025-07-24","cited_by_count":1,"area":null},{"id":"2508.16345","title":"Uppaal Coshy: Automatic Synthesis of Compact Shields for Hybrid Systems","created":"2025-08-22","cited_by_count":1,"area":null},{"id":"2510.20621","title":"Towards the Formalization of a Trustworthy AI for Mining Interpretable Models explOiting Sophisticated Algorithms","created":"2025-10-23","cited_by_count":1,"area":null},{"id":"2602.02173","title":"Generalized Optimal Classification Trees: A Mixed-Integer Programming Approach","created":"2026-02-02","cited_by_count":1,"area":null},{"id":"2605.07598","title":"Optimal Recourse Summaries via Bi-Objective Decision Tree Learning","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2106.11389","title":"Robust and Heterogenous Odds Ratio: Estimating Price Sensitivity for Unbought Items","created":"2021-06-21","cited_by_count":0,"area":null},{"id":"2112.05239","title":"On multivariate randomized classification trees: $l_0$-based sparsity, VC~dimension and decomposition methods","created":"2021-12-09","cited_by_count":0,"area":null},{"id":"2306.06777","title":"Improving the Validity of Decision Trees as Explanations","created":"2023-06-11","cited_by_count":0,"area":null},{"id":"2405.15314","title":"Output-Constrained Decision Trees","created":"2024-05-24","cited_by_count":0,"area":null},{"id":"2408.01023","title":"Distilling interpretable causal trees from causal forests","created":"2024-08-02","cited_by_count":0,"area":null},{"id":"2408.01297","title":"Optimal Mixed Integer Linear Optimization Trained Multivariate Classification Trees","created":"2024-08-02","cited_by_count":0,"area":null},{"id":"2408.12304","title":"OPTDTALS: Approximate Logic Synthesis via Optimal Decision Trees Approach","created":"2024-08-22","cited_by_count":0,"area":null},{"id":"2507.07576","title":"On Trustworthy Rule-Based Models and Explanations","created":"2025-07-10","cited_by_count":0,"area":null},{"id":"2509.12057","title":"Optimal hypersurface decision trees","created":"2025-09-15","cited_by_count":0,"area":null},{"id":"2509.17774","title":"Efficient & Correct Predictive Equivalence for Decision Trees","created":"2025-09-22","cited_by_count":0,"area":null},{"id":"2510.07832","title":"Surrogate Graph Partitioning for Spatial Prediction","created":"2025-10-09","cited_by_count":0,"area":null},{"id":"2510.19241","title":"SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes","created":"2025-10-22","cited_by_count":0,"area":"deeprl"},{"id":"2510.23901","title":"RS-ORT: A Reduced-Space Branch-and-Bound Algorithm for Optimal Regression Trees","created":"2025-10-27","cited_by_count":0,"area":null},{"id":"2604.21042","title":"Interpretable Quantile Regression by Optimal Decision Trees","created":"2026-04-22","cited_by_count":0,"area":null},{"id":"2607.25925","title":"dtControl2+$\\varepsilon$: Trading Optimality for Explainability in MDPs via Decision Trees","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2607.28170","title":"Search Strategies for Optimal Classification and Regression Trees","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2608.04310","title":"ArborEnum: Decision Tree Rashomon Sets over Continuous Features","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2608.29262","title":"Adaptive Multi-Branching for Shallow Decision Tree Induction","created":"2026-08-29","cited_by_count":0,"area":null},{"id":"2609.01430","title":"Learning Sparse Decision Trees via Transformer Variational Auto-Encoders","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.05826","title":"Scaling Optimal Classification Trees via Adaptive Feature and Sample Reduction","created":"2026-09-05","cited_by_count":0,"area":null},{"id":"2609.16952","title":"Learning Choice Model Trees for Feature-Based Multi-Product Pricing: Exact Optimization and Field Evidence","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.23780","title":"Falling Trees: A Model Class for Interpretable Risk Prioritization","created":"2026-09-20","cited_by_count":0,"area":null},{"id":"2609.24741","title":"An Exact Junction-Tree Extended Formulation for Optimal Classification Trees","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.38194","title":"A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees","created":"2026-09-18","cited_by_count":0,"area":null},{"id":"2610.04385","title":"Largest Rashomon sets of decision trees for robust contextual optimization","created":"2026-10-03","cited_by_count":0,"area":null}],"next_cursor":null}