A curated list of classification and regression tree research papers with implementations from the following conferences:
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Using MaxSAT for Efficient Explanations of Tree Ensembles (AAAI 2022)
- Alexey Ignatiev, Yacine Izza, Peter J. Stuckey, João Marques-Silva
- [Paper]
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FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles (AAAI 2022)
- Ana Lucic, Harrie Oosterhuis, Hinda Haned, Maarten de Rijke
- [Paper]
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Explainable and Local Correction of Classification Models Using Decision Trees (AAAI 2022)
- Hirofumi Suzuki, Hiroaki Iwashita, Takuya Takagi, Keisuke Goto, Yuta Fujishige, Satoshi Hara
- [Paper]
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Robust Optimal Classification Trees against Adversarial Examples (AAAI 2022)
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Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values (AAAI 2022)
- Haewon Jeong, Hao Wang, Flávio P. Calmon
- [Paper]
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Fast Sparse Decision Tree Optimization via Reference Ensembles (AAAI 2022)
- Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo I. Seltzer
- [Paper]
- [Code]
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TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion (AAAI 2022)
- Yiheng Sun, Tian Lu, Cong Wang, Yuan Li, Huaiyu Fu, Jingran Dong, Yunjie Xu
- [Paper]
- [Code]
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Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees (AISTATS 2022)
- Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike
- [Paper]
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Accurate Shapley Values for explaining tree-based models (AISTATS 2022)
- Salim I. Amoukou, Tangi Salaün, Nicolas J.-B. Brunel
- [Paper]
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A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds (AISTATS 2022)
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Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees (WWW 2022)
- Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon
- [Paper]
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MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration (WWW 2022)
- Siguang Huang, Yunli Wang, Lili Mou, Huayue Zhang, Han Zhu, Chuan Yu, Bo Zheng
- [Paper]
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Rethinking Conversational Recommendations: Is Decision Tree All You Need (CIKM 2022)
- A S. M. Ahsan-Ul-Haque, Hongning Wang
- [Paper]
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A Neural Tangent Kernel Perspective of Infinite Tree Ensembles (ICLR 2022)
- Ryuichi Kanoh, Mahito Sugiyama
- [Paper]
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POETREE: Interpretable Policy Learning with Adaptive Decision Trees (ICLR 2022)
- Alizée Pace, Alex Chan, Mihaela van der Schaar
- [Paper]
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Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models (ICML 2022)
- Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu
- [Paper]
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Popular decision tree algorithms are provably noise tolerant (ICML 2022)
- Guy Blanc, Jane Lange, Ali Malik, Li-Yang Tan
- [Paper]
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Robust Counterfactual Explanations for Tree-Based Ensembles (ICML 2022)
- Sanghamitra Dutta, Jason Long, Saumitra Mishra, Cecilia Tilli, Daniele Magazzeni
- [Paper]
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Fast Provably Robust Decision Trees and Boosting (ICML 2022)
- Jun-Qi Guo, Ming-Zhuo Teng, Wei Gao, Zhi-Hua Zhou
- [Paper]
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BAMDT: Bayesian Additive Semi-Multivariate Decision Trees for Nonparametric Regression (ICML 2022)
- Zhao Tang Luo, Huiyan Sang, Bani K. Mallick
- [Paper]
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Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features (ICML 2022)
- Rahul Mazumder, Xiang Meng, Haoyue Wang
- [Paper]
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A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources (ICML 2022)
- Xiaoqing Tan, Chung-Chou H. Chang, Ling Zhou, Lu Tang
- [Paper]
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On Preferred Abductive Explanations for Decision Trees and Random Forests (IJCAI 2022)
- Gilles Audemard, Steve Bellart, Louenas Bounia, Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis
- [Paper]
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Extending Decision Tree to Handle Multiple Fairness Criteria (IJCAI 2022)
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Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles (KDD 2022)
- Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder
- [Paper]
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Integrity Authentication in Tree Models (KDD 2022)
- Weijie Zhao, Yingjie Lao, Ping Li
- [Paper]
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Retrieval-Based Gradient Boosting Decision Trees for Disease Risk Assessment (KDD 2022)
- Handong Ma, Jiahang Cao, Yuchen Fang, Weinan Zhang, Wenbo Sheng, Shaodian Zhang, Yong Yu
- [Paper]
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Improved feature importance computation for tree models based on the Banzhaf value (UAI 2022)
- Adam Karczmarz, Tomasz Michalak, Anish Mukherjee, Piotr Sankowski, Piotr Wygocki
- [Paper]
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Learning linear non-Gaussian polytree models (UAI 2022)
- Daniele Tramontano, Anthea Monod, Mathias Drton
- [Paper]
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Online Probabilistic Label Trees (AISTATS 2021)
- Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari, Krzysztof Dembczyński
- [Paper]
- [Code]
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Optimal Decision Trees for Nonlinear Metrics (AAAI 2021)
- Emir Demirovic, Peter J. Stuckey
- [Paper]
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SAT-based Decision Tree Learning for Large Data Sets (AAAI 2021)
- André Schidler, Stefan Szeider
- [Paper]
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Parameterized Complexity of Small Decision Tree Learning (AAAI 2021)
- Sebastian Ordyniak, Stefan Szeider
- [Paper]
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Counterfactual Explanations for Oblique Decision Trees: Exact - Efficient Algorithms (AAAI 2021)
- Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
- [Paper]
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Geometric Heuristics for Transfer Learning in Decision Trees (CIKM 2021)
- Siddhesh Chaubal, Mateusz Rzepecki, Patrick K. Nicholson, Guangyuan Piao, Alessandra Sala
- [Paper]
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Fairness-Aware Training of Decision Trees by Abstract Interpretation (CIKM 2021)
- Francesco Ranzato, Caterina Urban, Marco Zanella
- [Paper]
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Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification (CIKM 2021)
- Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon
- [Paper]
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Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees (ICLR 2021)
- Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
- [Paper]
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NBDT: Neural-Backed Decision Tree (ICLR 2021)
- Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez
- [Paper]
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Versatile Verification of Tree Ensembles (ICML 2021)
- Laurens Devos, Wannes Meert, Jesse Davis
- [Paper]
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Connecting Interpretability and Robustness in Decision Trees through Separation (ICML 2021)
- Michal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri
- [Paper]
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Optimal Counterfactual Explanations in Tree Ensembles (ICML 2021)
- Axel Parmentier, Thibaut Vidal
- [Paper]
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Efficient Training of Robust Decision Trees Against Adversarial Examples (ICML 2021)
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Learning Binary Decision Trees by Argmin Differentiation (ICML 2021)
- Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
- [Paper]
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BLOCKSET (Block-Aligned Serialized Trees): Reducing Inference Latency for Tree ensemble Deployment (KDD 2021)
- Meghana Madhyastha, Kunal Lillaney, James Browne, Joshua T. Vogelstein, Randal Burns
- [Paper]
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ControlBurn: Feature Selection by Sparse Forests (KDD 2021)
- Brian Liu, Miaolan Xie, Madeleine Udell
- [Paper]
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Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression (KDD 2021)
- Olivier Sprangers, Sebastian Schelter, Maarten de Rijke
- [Paper]
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Verifying Tree Ensembles by Reasoning about Potential Instances (SDM 2021)
- Laurens Devos, Wannes Meert, Jesse Davis
- [Paper]
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DTCA: Decision Tree-based Co-Attention Networks for Explainable Claim Verification (ACL 2020)
- Lianwei Wu, Yuan Rao, Yongqiang Zhao, Hao Liang, Ambreen Nazir
- [Paper]
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Privacy-Preserving Gradient Boosting Decision Trees (AAAI 2020)
- Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He
- [Paper]
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Practical Federated Gradient Boosting Decision Trees (AAAI 2020)
- Qinbin Li, Zeyi Wen, Bingsheng He
- [Paper]
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Efficient Inference of Optimal Decision Trees (AAAI 2020)
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Learning Optimal Decision Trees Using Caching Branch-and-Bound Search (AAAI 2020)
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Abstract Interpretation of Decision Tree Ensemble Classifiers (AAAI 2020)
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Scalable Feature Selection for (Multitask) Gradient Boosted Trees (AISTATS 2020)
- Cuize Han, Nikhil Rao, Daria Sorokina, Karthik Subbian
- [Paper]
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Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning (AISTATS 2020)
- Andrew Silva, Matthew C. Gombolay, Taylor W. Killian, Ivan Dario Jimenez Jimenez, Sung-Hyun Son
- [Paper]
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Exploiting Categorical Structure Using Tree-Based Methods (AISTATS 2020)
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LdSM: Logarithm-depth Streaming Multi-label Decision Trees (AISTATS 2020)
- Maryam Majzoubi, Anna Choromanska
- [Paper]
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Oblique Decision Trees from Derivatives of ReLU Networks (ICLR 2020)
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Provable Guarantees for Decision Tree Induction: the Agnostic Setting (ICML 2020)
- Guy Blanc, Jane Lange, Li-Yang Tan
- [Paper]
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Decision Trees for Decision-Making under the Predict-then-Optimize Framework (ICML 2020)
- Adam N. Elmachtoub, Jason Cheuk Nam Liang, Ryan McNellis
- [Paper]
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The Tree Ensemble Layer: Differentiability meets Conditional Computation (ICML 2020)
- Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
- [Paper]
- [Code]
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Generalized and Scalable Optimal Sparse Decision Trees (ICML 2020)
- Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo I. Seltzer
- [Paper]
- [Code]
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Born-Again Tree Ensembles (ICML 2020)
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On Lp-norm Robustness of Ensemble Decision Stumps and Trees (ICML 2020)
- Yihan Wang, Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh
- [Paper]
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Smaller, More Accurate Regression Forests Using Tree Alternating Optimization (ICML 2020)
- Arman Zharmagambetov, Miguel Á. Carreira-Perpinan
- [Paper]
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Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost (IJCAI 2020)
- Hao Hu, Mohamed Siala, Emmanuel Hebrard, Marie-José Huguet
- [Paper]
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Speeding up Very Fast Decision Tree with Low Computational Cost (IJCAI 2020)
- Jian Sun, Hongyu Jia, Bo Hu, Xiao Huang, Hao Zhang, Hai Wan, Xibin Zhao
- [Paper]
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PyDL8.5: a Library for Learning Optimal Decision Trees (IJCAI 2020)
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Geodesic Forests (KDD 2020)
- Meghana Madhyastha, Gongkai Li, Veronika Strnadova-Neeley, James Browne, Joshua T. Vogelstein, Randal Burns
- [Paper]
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A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees (NeurIPS 2020)
- Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam
- [Paper]
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Estimating Decision Tree Learnability with Polylogarithmic Sample Complexity (NeurIPS 2020)
- Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan
- [Paper]
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Universal Guarantees for Decision Tree Induction via a Higher-Order Splitting Criterion (NeurIPS 2020)
- Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan
- [Paper]
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Smooth And Consistent Probabilistic Regression Trees (NeurIPS 2020)
- Sami Alkhoury, Emilie Devijver, Marianne Clausel, Myriam Tami, Éric Gaussier, Georges Oppenheim
- [Paper]
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An Efficient Adversarial Attack for Tree Ensembles (NeurIPS 2020)
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Decision Trees as Partitioning Machines to Characterize their Generalization Properties (NeurIPS 2020)
- Jean-Samuel Leboeuf, Frédéric Leblanc, Mario Marchand
- [Paper]
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Evidence Weighted Tree Ensembles for Text Classification (SIGIR 2020)
- Md. Zahidul Islam, Jixue Liu, Jiuyong Li, Lin Liu, Wei Kang
- [Paper]
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Multi Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System (AAAI 2019)
- Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang
- [Paper]
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Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME (AAAI 2019)
- Farhad Shakerin, Gopal Gupta
- [Paper]
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Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making (AAAI 2019)
- Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos
- [Paper]
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Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals (AAAI 2019)
- Kacper Sokol, Peter A. Flach
- [Paper]
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Weighted Oblique Decision Trees (AAAI 2019)
- Bin-Bin Yang, Song-Qing Shen, Wei Gao
- [Paper]
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Learning Optimal Classification Trees Using a Binary Linear Program Formulation (AAAI 2019)
- Sicco Verwer, Yingqian Zhang
- [Paper]
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Optimization of Hierarchical Regression Model with Application to Optimizing Multi-Response Regression K-ary Trees (AAAI 2019)
- Pooya Tavallali, Peyman Tavallali, Mukesh Singhal
- [Paper]
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XBART: Accelerated Bayesian Additive Regression Trees (AISTATS 2019)
- Jingyu He, Saar Yalov, P. Richard Hahn
- [Paper]
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Interaction Detection with Bayesian Decision Tree Ensembles (AISTATS 2019)
- Junliang Du, Antonio R. Linero
- [Paper]
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Adversarial Training of Gradient-Boosted Decision Trees (CIKM 2019)
- Stefano Calzavara, Claudio Lucchese, Gabriele Tolomei
- [Paper]
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Interpretable MTL from Heterogeneous Domains using Boosted Tree (CIKM 2019)
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Interpreting CNNs via Decision Trees (CVPR 2019)
- Quanshi Zhang, Yu Yang, Haotian Ma, Ying Nian Wu
- [Paper]
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EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees (ICDM 2019)
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Fair Adversarial Gradient Tree Boosting (ICDM 2019)
- Vincent Grari, Boris Ruf, Sylvain Lamprier, Marcin Detyniecki
- [Paper]
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Functional Transparency for Structured Data: a Game-Theoretic Approach (ICML 2019)
- Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola
- [Paper]
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Incorporating Grouping Information into Bayesian Decision Tree Ensembles (ICML 2019)
- Junliang Du, Antonio R. Linero
- [Paper]
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Adaptive Neural Trees (ICML 2019)
- Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori
- [Paper]
- [Code]
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Robust Decision Trees Against Adversarial Examples (ICML 2019)
- Hongge Chen, Huan Zhang, Duane S. Boning, Cho-Jui Hsieh
- [Paper]
- [Code]
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Learn Smart with Less: Building Better Online Decision Trees with Fewer Training Examples (IJCAI 2019)
- Ariyam Das, Jin Wang, Sahil M. Gandhi, Jae Lee, Wei Wang, Carlo Zaniolo
- [Paper]
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FAHT: An Adaptive Fairness-aware Decision Tree Classifier (IJCAI 2019)
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Inter-node Hellinger Distance based Decision Tree (IJCAI 2019)
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Gradient Boosting with Piece-Wise Linear Regression Trees (IJCAI 2019)
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A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees (IJCAI 2019)
- Klaus Broelemann, Gjergji Kasneci
- [Paper]
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Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search (KDD 2019)
- Pan Li, Zhen Qin, Xuanhui Wang, Donald Metzler
- [Paper]
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Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers (NeurIPS 2019)
- Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola
- [Paper]
- [Code]
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Partitioning Structure Learning for Segmented Linear Regression Trees (NeurIPS 2019)
- Xiangyu Zheng, Song Xi Chen
- [Paper]
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Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks (NeurIPS 2019)
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Optimal Decision Tree with Noisy Outcomes (NeurIPS 2019)
- Su Jia, Viswanath Nagarajan, Fatemeh Navidi, R. Ravi
- [Paper]
- [Code]
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Regularized Gradient Boosting (NeurIPS 2019)
- Corinna Cortes, Mehryar Mohri, Dmitry Storcheus
- [Paper]
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Optimal Sparse Decision Trees (NeurIPS 2019)
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MonoForest framework for tree ensemble analysis (NeurIPS 2019)
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Calibrating Probability Estimation Trees using Venn-Abers Predictors (SDM 2019)
- Ulf Johansson, Tuwe Löfström, Henrik Boström
- [Paper]
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Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization (SDM 2019)
- Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander
- [Paper]
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Forest Packing: Fast Parallel, Decision Forests (SDM 2019)
- James Browne, Disa Mhembere, Tyler M. Tomita, Joshua T. Vogelstein, Randal Burns
- [Paper]
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Block-distributed Gradient Boosted Trees (SIGIR 2019)
- Theodore Vasiloudis, Hyunsu Cho, Henrik Boström
- [Paper]
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Entity Personalized Talent Search Models with Tree Interaction Features (WWW 2019)
- Cagri Ozcaglar, Sahin Cem Geyik, Brian Schmitz, Prakhar Sharma, Alex Shelkovnykov, Yiming Ma, Erik Buchanan
- [Paper]
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Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees (AAAI 2018)
- Dennis J. N. J. Soemers, Tim Brys, Kurt Driessens, Mark H. M. Winands, Ann Nowé
- [Paper]
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MERCS: Multi-Directional Ensembles of Regression and Classification Trees (AAAI 2018)
- Elia Van Wolputte, Evgeniya Korneva, Hendrik Blockeel
- [Paper]
- [Code]
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Differential Performance Debugging With Discriminant Regression Trees (AAAI 2018)
- Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Ashutosh Trivedi
- [Paper]
- [Code]
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Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction (AAAI 2018)
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MDP-Based Cost Sensitive Classification Using Decision Trees (AAAI 2018)
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Generative Adversarial Image Synthesis With Decision Tree Latent Controller (CVPR 2018)
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Enhancing Very Fast Decision Trees with Local Split-Time Predictions (ICDM 2018)
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Realization of Random Forest for Real-Time Evaluation through Tree Framing (ICDM 2018)
- Sebastian Buschjäger, Kuan-Hsun Chen, Jian-Jia Chen, Katharina Morik
- [Paper]
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Finding Influential Training Samples for Gradient Boosted Decision Trees (ICML 2018)
- Boris Sharchilev, Yury Ustinovskiy, Pavel Serdyukov, Maarten de Rijke
- [Paper]
- [Code]
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Learning Optimal Decision Trees with SAT (IJCAI 2018)
- Nina Narodytska, Alexey Ignatiev, Filipe Pereira, João Marques-Silva
- [Paper]
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Extremely Fast Decision Tree (KDD 2018)
- Chaitanya Manapragada, Geoffrey I. Webb, Mahsa Salehi
- [Paper]
- [Code]
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RapidScorer: Fast Tree Ensemble Evaluation by Maximizing Compactness in Data Level Parallelization (KDD 2018)
- Ting Ye, Hucheng Zhou, Will Y. Zou, Bin Gao, Ruofei Zhang
- [Paper]
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CatBoost: Unbiased Boosting with Categorical Features (NIPS 2018)
- Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin
- [Paper]
- [Code]
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Active Learning for Non-Parametric Regression Using Purely Random Trees (NIPS 2018)
- Jack Goetz, Ambuj Tewari, Paul Zimmerman
- [Paper]
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Alternating Optimization of Decision Trees with Application to Learning Sparse Oblique Trees (NIPS 2018)
- Miguel Á. Carreira-Perpiñán, Pooya Tavallali
- [Paper]
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Multi-Layered Gradient Boosting Decision Trees (NIPS 2018)
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Transparent Tree Ensembles (SIGIR 2018)
- Alexander Moore, Vanessa Murdock, Yaxiong Cai, Kristine Jones
- [Paper]
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Privacy-aware Ranking with Tree Ensembles on the Cloud (SIGIR 2018)
- Shiyu Ji, Jinjin Shao, Daniel Agun, Tao Yang
- [Paper]
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Strategic Sequences of Arguments for Persuasion Using Decision Trees (AAAI 2017)
- Emmanuel Hadoux, Anthony Hunter
- [Paper]
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BoostVHT: Boosting Distributed Streaming Decision Trees (CIKM 2017)
- Theodore Vasiloudis, Foteini Beligianni, Gianmarco De Francisci Morales
- [Paper]
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Latency Reduction via Decision Tree Based Query Construction (CIKM 2017)
- Aman Grover, Dhruv Arya, Ganesh Venkataraman
- [Paper]
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Enumerating Distinct Decision Trees (ICML 2017)
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Gradient Boosted Decision Trees for High Dimensional Sparse Output (ICML 2017)
- Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh
- [Paper]
- [Code]
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Consistent Feature Attribution for Tree Ensembles (ICML 2017)
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Extremely Fast Decision Tree Mining for Evolving Data Streams (KDD 2017)
- Albert Bifet, Jiajin Zhang, Wei Fan, Cheng He, Jianfeng Zhang, Jianfeng Qian, Geoff Holmes, Bernhard Pfahringer
- [Paper]
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CatBoost: Gradient Boosting with Categorical Features Support (NIPS 2017)
- Anna Veronika Dorogush, Vasily Ershov, Andrey Gulin
- [Paper]
- [Code]
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LightGBM: A Highly Efficient Gradient Boosting Decision Tree (NIPS 2017)
- Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu
- [Paper]
- [Code]
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Variable Importance Using Decision Trees (NIPS 2017)
- Jalil Kazemitabar, Arash Amini, Adam Bloniarz, Ameet S. Talwalkar
- [Paper]
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A Unified Approach to Interpreting Model Predictions (NIPS 2017)
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Pruning Decision Trees via Max-Heap Projection (SDM 2017)
- Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan, Wei Fan, Jieping Ye
- [Paper]
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A Practical Method for Solving Contextual Bandit Problems Using Decision Trees (UAI 2017)
- Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik
- [Paper]
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Complexity of Solving Decision Trees with Skew-Symmetric Bilinear Utility (UAI 2017)
- Hugo Gilbert, Olivier Spanjaard
- [Paper]
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GB-CENT: Gradient Boosted Categorical Embedding and Numerical Trees (WWW 2017)
- Qian Zhao, Yue Shi, Liangjie Hong
- [Paper]
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Sparse Perceptron Decision Tree for Millions of Dimensions (AAAI 2016)
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Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees (CVPR 2016)
- Jianhui Chen, Hoang Minh Le, Peter Carr, Yisong Yue, James J. Little
- [Paper]
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Online Learning with Bayesian Classification Trees (CVPR 2016)
- Samuel Rota Bulò, Peter Kontschieder
- [Paper]
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Accurate Robust and Efficient Error Estimation for Decision Trees (ICML 2016)
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Meta-Gradient Boosted Decision Tree Model for Weight and Target Learning (ICML 2016)
- Yury Ustinovskiy, Valentina Fedorova, Gleb Gusev, Pavel Serdyukov
- [Paper]
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Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments (KDD 2016)
- Alexey Poyarkov, Alexey Drutsa, Andrey Khalyavin, Gleb Gusev, Pavel Serdyukov
- [Paper]
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XGBoost: A Scalable Tree Boosting System (KDD 2016)
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Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale (NIPS 2016)
- Firas Abuzaid, Joseph K. Bradley, Feynman T. Liang, Andrew Feng, Lee Yang, Matei Zaharia, Ameet S. Talwalkar
- [Paper]
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A Communication-Efficient Parallel Algorithm for Decision Tree (NIPS 2016)
- Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu
- [Paper]
- [Code]
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Exploiting CPU SIMD Extensions to Speed-up Document Scoring with Tree Ensembles (SIGIR 2016)
- Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini
- [Paper]
- [Code]
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Post-Learning Optimization of Tree Ensembles for Efficient Ranking (SIGIR 2016)
- Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Fabrizio Silvestri, Salvatore Trani
- [Paper]
- [Code]
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Particle Gibbs for Bayesian Additive Regression Trees (AISTATS 2015)
- Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh
- [Paper]
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DART: Dropouts Meet Multiple Additive Regression Trees (AISTATS 2015)
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Single Target Tracking Using Adaptive Clustered Decision Trees and Dynamic Multi-level Appearance Models (CVPR 2015)
- Jingjing Xiao, Rustam Stolkin, Ales Leonardis
- [Paper]
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Face Alignment Using Cascade Gaussian Process Regression Trees (CVPR 2015)
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Tracking-by-Segmentation with Online Gradient Boosting Decision Tree (ICCV 2015)
- Jeany Son, Ilchae Jung, Kayoung Park, Bohyung Han
- [Paper]
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Entropy Evaluation Based on Confidence Intervals of Frequency Estimates : Application to the Learning of Decision Trees (ICML 2015)
- Mathieu Serrurier, Henri Prade
- [Paper]
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Large-scale Distributed Dependent Nonparametric Trees (ICML 2015)
- Zhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing
- [Paper]
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Optimal Action Extraction for Random Forests and Boosted Trees (KDD 2015)
- Zhicheng Cui, Wenlin Chen, Yujie He, Yixin Chen
- [Paper]
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A Decision Tree Framework for Spatiotemporal Sequence Prediction (KDD 2015)
- Taehwan Kim, Yisong Yue, Sarah L. Taylor, Iain A. Matthews
- [Paper]
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Efficient Non-greedy Optimization of Decision Trees (NIPS 2015)
- Mohammad Norouzi, Maxwell D. Collins, Matthew Johnson, David J. Fleet, Pushmeet Kohli
- [Paper]
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QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees (SIGIR 2015)
- Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini
- [Paper]
- [Code]
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Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria (ICCV 2013)
- Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht
- [Paper]
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Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees (ICCV 2013)
- Oisin Mac Aodha, Gabriel J. Brostow
- [Paper]
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Conformal Prediction Using Decision Trees (ICDM 2013)
- Ulf Johansson, Henrik Boström, Tuve Löfström
- [Paper]
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Focal-Test-Based Spatial Decision Tree Learning: A Summary of Results (ICDM 2013)
- Zhe Jiang, Shashi Shekhar, Xun Zhou, Joseph K. Knight, Jennifer Corcoran
- [Paper]
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Top-down Particle Filtering for Bayesian Decision Trees (ICML 2013)
- Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh
- [Paper]
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Quickly Boosting Decision Trees - Pruning Underachieving Features Early (ICML 2013)
- Ron Appel, Thomas J. Fuchs, Piotr Dollár, Pietro Perona
- [Paper]
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Knowledge Compilation for Model Counting: Affine Decision Trees (IJCAI 2013)
- Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis, Samuel Thomas
- [Paper]
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Understanding Variable Importances in Forests of Randomized Trees (NIPS 2013)
- Gilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts
- [Paper]
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Regression-tree Tuning in a Streaming Setting (NIPS 2013)
- Samory Kpotufe, Francesco Orabona
- [Paper]
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Learning Max-Margin Tree Predictors (UAI 2013)
- Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson
- [Paper]
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Incorporating Boosted Regression Trees into Ecological Latent Variable Models (AAAI 2011)
- Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Dietterich
- [Paper]
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Syntactic Decision Tree LMs: Random Selection or Intelligent Design (EMNLP 2011)
- Denis Filimonov, Mary P. Harper
- [Paper]
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Decision Tree Fields (ICCV 2011)
- Sebastian Nowozin, Carsten Rother, Shai Bagon, Toby Sharp, Bangpeng Yao, Pushmeet Kohli
- [Paper]
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Confidence in Predictions from Random Tree Ensembles (ICDM 2011)
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Speeding-Up Hoeffding-Based Regression Trees With Options (ICML 2011)
- Elena Ikonomovska, João Gama, Bernard Zenko, Saso Dzeroski
- [Paper]
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Density Estimation Trees (KDD 2011)
- Parikshit Ram, Alexander G. Gray
- [Paper]
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Bagging Gradient-Boosted Trees for High Precision, Low Variance Ranking Models (SIGIR 2011)
- Yasser Ganjisaffar, Rich Caruana, Cristina Videira Lopes
- [Paper]
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On the Complexity of Decision Making in Possibilistic Decision Trees (UAI 2011)
- Hélène Fargier, Nahla Ben Amor, Wided Guezguez
- [Paper]
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Adaptive Bootstrapping of Recommender Systems Using Decision Trees (WSDM 2011)
- Nadav Golbandi, Yehuda Koren, Ronny Lempel
- [Paper]
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Parallel Boosted Regression Trees for Web Search Ranking (WWW 2011)
- Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal, Jennifer Paykin
- [Paper]
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Tree-based Classifiers for Bilayer Video Segmentation (CVPR 2007)
- Pei Yin, Antonio Criminisi, John M. Winn, Irfan A. Essa
- [Paper]
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Additive Groves of Regression Trees (ECML 2007)
- Daria Sorokina, Rich Caruana, Mirek Riedewald
- [Paper]
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Decision Tree Instability and Active Learning (ECML 2007)
- Kenneth Dwyer, Robert Holte
- [Paper]
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Ensembles of Multi-Objective Decision Trees (ECML 2007)
- Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski
- [Paper]
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Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble (ECML 2007)
- Anneleen Van Assche, Hendrik Blockeel
- [Paper]
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Sample Compression Bounds for Decision Trees (ICML 2007)
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A Tighter Error Bound for Decision Tree Learning Using PAC Learnability (IJCAI 2007)
- Chaithanya Pichuka, Raju S. Bapi, Chakravarthy Bhagvati, Arun K. Pujari, Bulusu Lakshmana Deekshatulu
- [Paper]
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Keep the Decision Tree and Estimate the Class Probabilities Using its Decision Boundary (IJCAI 2007)
- Isabelle Alvarez, Stephan Bernard, Guillaume Deffuant
- [Paper]
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Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree (IJCAI 2007)
- Claudia Henry, Richard Nock, Frank Nielsen
- [Paper]
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Scalable Look-ahead Linear Regression Trees (KDD 2007)
- David S. Vogel, Ognian Asparouhov, Tobias Scheffer
- [Paper]
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Mining Optimal Decision Trees from Itemset Lattices (KDD 2007)
- Siegfried Nijssen, Élisa Fromont
- [Paper]
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A Hybrid Multi-group Privacy-Preserving Approach for Building Decision Trees (PAKDD 2007)
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Decision Tree Methods for Finding Reusable MDP Homomorphisms (AAAI 2006)
- Alicia P. Wolfe, Andrew G. Barto
- [Paper]
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A Fast Decision Tree Learning Algorithm (AAAI 2006)
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Anytime Induction of Decision Trees: An Iterative Improvement Approach (AAAI 2006)
- Saher Esmeir, Shaul Markovitch
- [Paper]
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When a Decision Tree Learner Has Plenty of Time (AAAI 2006)
- Saher Esmeir, Shaul Markovitch
- [Paper]
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Decision Trees for Functional Variables (ICDM 2006)
- Suhrid Balakrishnan, David Madigan
- [Paper]
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Cost-Sensitive Decision Tree Learning for Forensic Classification (ECML 2006)
- Jason V. Davis, Jungwoo Ha, Christopher J. Rossbach, Hany E. Ramadan, Emmett Witchel
- [Paper]
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Improving the Ranking Performance of Decision Trees (ECML 2006)
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A General Framework for Accurate and Fast Regression by Data Summarization in Random Decision Trees (KDD 2006)
- Wei Fan, Joe McCloskey, Philip S. Yu
- [Paper]
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Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction (PAKDD 2006)
- Phu Chien Nguyen, Kouzou Ohara, Akira Mogi, Hiroshi Motoda, Takashi Washio
- [Paper]
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Variable Randomness in Decision Tree Ensembles (PAKDD 2006)
- Fei Tony Liu, Kai Ming Ting
- [Paper]
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Generalized Conditional Entropy and a Metric Splitting Criterion for Decision Trees (PAKDD 2006)
- Dan A. Simovici, Szymon Jaroszewicz
- [Paper]
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Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics (PKDD 2006)
- Hendrik Blockeel, Leander Schietgat, Jan Struyf, Saso Dzeroski, Amanda Clare
- [Paper]
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k-Anonymous Decision Tree Induction (PKDD 2006)
- Arik Friedman, Assaf Schuster, Ran Wolff
- [Paper]
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Representing Conditional Independence Using Decision Trees (AAAI 2005)
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Use of Expert Knowledge for Decision Tree Pruning (AAAI 2005)
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Model Selection in Omnivariate Decision Trees (ECML 2005)
- Olcay Taner Yildiz, Ethem Alpaydin
- [Paper]
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Combining Bias and Variance Reduction Techniques for Regression Trees (ECML 2005)
- Yuk Lai Suen, Prem Melville, Raymond J. Mooney
- [Paper]
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Simple Test Strategies for Cost-Sensitive Decision Trees (ECML 2005)
- Shengli Sheng, Charles X. Ling, Qiang Yang
- [Paper]
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Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches (ICDM 2005)
- Wei Fan, Ed Greengrass, Joe McCloskey, Philip S. Yu, Kevin Drummey
- [Paper]
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Exploiting Informative Priors for Bayesian Classification and Regression Trees (IJCAI 2005)
- Nicos Angelopoulos, James Cussens
- [Paper]
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Ranking Cases with Decision Trees: a Geometric Method that Preserves Intelligibility (IJCAI 2005)
- Isabelle Alvarez, Stephan Bernard
- [Paper]
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Maximizing Tree Diversity by Building Complete-Random Decision Trees (PAKDD 2005)
- Fei Tony Liu, Kai Ming Ting, Wei Fan
- [Paper]
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Hybrid Cost-Sensitive Decision Tree (PKDD 2005)
- Shengli Sheng, Charles X. Ling
- [Paper]
-
Tree2 - Decision Trees for Tree Structured Data (PKDD 2005)
- Björn Bringmann, Albrecht Zimmermann
- [Paper]
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Building Decision Trees on Records Linked through Key References (SDM 2005)
- Ke Wang, Yabo Xu, Philip S. Yu, Rong She
- [Paper]
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Decision Tree Induction in High Dimensional, Hierarchically Distributed Databases (SDM 2005)
- Amir Bar-Or, Ran Wolff, Assaf Schuster, Daniel Keren
- [Paper]
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Boosted Decision Trees for Word Recognition in Handwritten Document Retrieval (SIGIR 2005)
- Nicholas R. Howe, Toni M. Rath, R. Manmatha
- [Paper]
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On the Optimality of Probability Estimation by Random Decision Trees (AAAI 2004)
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Occam’s Razor and a Non-Syntactic Measure of Decision Tree Complexity (AAAI 2004)
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Using Emerging Patterns and Decision Trees in Rare-Class Classification (ICDM 2004)
- Hamad Alhammady, Kotagiri Ramamohanarao
- [Paper]
-
Orthogonal Decision Trees (ICDM 2004)
- Hillol Kargupta, Haimonti Dutta
- [Paper]
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Improving the Reliability of Decision Tree and Naive Bayes Learners (ICDM 2004)
- David George Lindsay, Siân Cox
- [Paper]
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Communication Efficient Construction of Decision Trees Over Heterogeneously Distributed Data (ICDM 2004)
- Chris Giannella, Kun Liu, Todd Olsen, Hillol Kargupta
- [Paper]
-
Decision Tree Evolution Using Limited Number of Labeled Data Items from Drifting Data Streams (ICDM 2004)
- Wei Fan, Yi-an Huang, Philip S. Yu
- [Paper]
-
Lookahead-based Algorithms for Anytime Induction of Decision Trees (ICML 2004)
- Saher Esmeir, Shaul Markovitch
- [Paper]
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Decision Trees with Minimal Costs (ICML 2004)
- Charles X. Ling, Qiang Yang, Jianning Wang, Shichao Zhang
- [Paper]
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Training Conditional Random Fields via Gradient Tree Boosting (ICML 2004)
- Thomas G. Dietterich, Adam Ashenfelter, Yaroslav Bulatov
- [Paper]
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Detecting Structural Metadata with Decision Trees and Transformation-Based Learning (NAACL 2004)
- Joungbum Kim, Sarah E. Schwarm, Mari Ostendorf
- [Paper]
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On the Adaptive Properties of Decision Trees (NIPS 2004)
- Clayton D. Scott, Robert D. Nowak
- [Paper]
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A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index (PAKDD 2004)
- Dan A. Simovici, Szymon Jaroszewicz
- [Paper]
-
Rademacher Penalization over Decision Tree Prunings (ECML 2003)
- Matti Kääriäinen, Tapio Elomaa
- [Paper]
-
Ensembles of Cascading Trees (ICDM 2003)
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Postprocessing Decision Trees to Extract Actionable Knowledge (ICDM 2003)
- Qiang Yang, Jie Yin, Charles X. Ling, Tielin Chen
- [Paper]
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K-D Decision Tree: An Accelerated and Memory Efficient Nearest Neighbor Classifier (ICDM 2003)
- Tomoyuki Shibata, Takekazu Kato, Toshikazu Wada
- [Paper]
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Identifying Markov Blankets with Decision Tree Induction (ICDM 2003)
- Lewis J. Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
- [Paper]
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Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy (ICDM 2003)
- Jin Huang, Jingjing Lu, Charles X. Ling
- [Paper]
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Boosting Lazy Decision Trees (ICML 2003)
- Xiaoli Zhang Fern, Carla E. Brodley
- [Paper]
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Decision Tree with Better Ranking (ICML 2003)
- Charles X. Ling, Robert J. Yan
- [Paper]
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Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction (IJCAI 2003)
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Efficient Decision Tree Construction on Streaming Data (KDD 2003)
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PaintingClass: Interactive Construction Visualization and Exploration of Decision Trees (KDD 2003)
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Accurate Decision Trees for Mining High-Speed Data Streams (KDD 2003)
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