decision tree

NBDT: Neural-Backed Decision Tree ICLR 2021 Nearly-Tight and Oblivious Algorithms for Explainable Clustering NeurIPS 2021 Near-Optimal Algorithms for Explainable k-Medians and k-Means ICML 2021 Neural Prototype Trees for Interpretable Fine-Grained Image Recognition CVPR 2021 On the price of explainability for some clustering problems ICML 2021 Optimal Decision Trees for Nonlinear Metrics AAAI 2021 Parameterized Complexity of Small Decision Tree Learning AAAI 2021 Prosodic Boundary Prediction Model for Vietnamese Text-To-Speech Interspeech 2021 Provably efficient, succinct, and precise explanations NeurIPS 2021 Reasoning-Based Learning of Interpretable ML Models IJCAI 2021 Robust Model Compression Using Deep Hypotheses AAAI 2021 Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments CVPR 2021 Scalable Rule-Based Representation Learning for Interpretable Classification NeurIPS 2021 Self-Born Wiring for Neural Trees ICCV 2021 Sharp Analysis of a Simple Model for Random Forests AISTATS 2021 The Tractability of SHAP-Score-Based Explanations for Classification over Deterministic and Decomposable Boolean Circuits AAAI 2021 Tree in Tree: from Decision Trees to Decision Graphs NeurIPS 2021 TripleTree: A Versatile Interpretable Representation of Black Box Agents and their Environments AAAI 2021 Acoustic-Based Articulatory Phenotypes of Amyotrophic Lateral Sclerosis and Parkinson’s Disease: Towards an Interpretable, Hypothesis-Driven Framework of Motor Control Interspeech 2020 Arabic Dialects Identification for All Arabic countries COLING 2020 A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees NeurIPS 2020 Born-Again Tree Ensembles ICML 2020 Decision trees as partitioning machines to characterize their generalization properties NeurIPS 2020 Decision Trees for Decision-Making under the Predict-then-Optimize Framework ICML 2020 Deep Dynamic Boosted Forest ACML 2020