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README.md

Awesome decision tree research papers

Awesome PRs Welcome

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A curated list of decision, classification and regression tree research papers with implementations from the following conferences:

A similar collection about graph embedding and community detection papers with implementations.

2018

  • 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]

  • MERCS: Multi-Directional Ensembles of Regression and Classification Trees (AAAI 2018)

    • Elia Van Wolputte, Evgeniya Korneva, Hendrik Blockeel
    • [Paper]
    • [Code]

  • Differential Performance Debugging With Discriminant Regression Trees (AAAI 2018)

    • Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Ashutosh Trivedi
    • [Paper]
    • [Code]

  • Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction (AAAI 2018)

  • MDP-Based Cost Sensitive Classification Using Decision Trees (AAAI 2018)

  • Generative Adversarial Image Synthesis With Decision Tree Latent Controller (CVPR 2018)

  • Enhancing Very Fast Decision Trees with Local Split-Time Predictions (ICDM 2018)

  • Finding Influential Training Samples for Gradient Boosted Decision Trees (ICML 2018)

    • Boris Sharchilev, Yury Ustinovskiy, Pavel Serdyukov, Maarten de Rijke
    • [Paper]
    • [Code]

  • Learning Optimal Decision Trees with SAT (IJCAI 2018)

    • Nina Narodytska, Alexey Ignatiev, Filipe Pereira, João Marques-Silva
    • [Paper]

  • Extremely Fast Decision Tree (KDD 2018)

    • Chaitanya Manapragada, Geoffrey I. Webb, Mahsa Salehi
    • [Paper]
    • [Code]

  • Alternating optimization of decision trees with application to learning sparse oblique trees (NIPS 2018)

    • Miguel Á. Carreira-Perpiñán, Pooya Tavallali
    • [Paper]

  • Multi-Layered Gradient Boosting Decision Trees (NIPS 2018)

2017

  • Strategic Sequences of Arguments for Persuasion Using Decision Trees (AAAI 2017)

    • Emmanuel Hadoux, Anthony Hunter
    • [Paper]

  • BoostVHT: Boosting Distributed Streaming Decision Trees (CIKM 2017)

    • Theodore Vasiloudis, Foteini Beligianni, Gianmarco De Francisci Morales
    • [Paper]

  • Latency Reduction via Decision Tree Based Query Construction (CIKM 2017)

    • Aman Grover, Dhruv Arya, Ganesh Venkataraman
    • [Paper]

  • Enumerating Distinct Decision Trees (ICML 2017)

  • 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]

  • 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]

  • 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]

  • Variable Importance Using Decision Trees (NIPS 2017)

    • Jalil Kazemitabar, Arash Amini, Adam Bloniarz, Ameet S. Talwalkar
    • [Paper]

  • A Practical Method for Solving Contextual Bandit Problems Using Decision Trees (UAI 2017)

    • Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik
    • [Paper]

  • Complexity of Solving Decision Trees with Skew-Symmetric Bilinear Utility (UAI 2017)

    • Hugo Gilbert, Olivier Spanjaard
    • [Paper]

2016

  • Sparse Perceptron Decision Tree for Millions of Dimensions (AAAI 2016)

  • 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]

  • Online Learning with Bayesian Classification Trees (CVPR 2016)

    • Samuel Rota Bulò, Peter Kontschieder
    • [Paper]

  • Accurate Robust and Efficient Error Estimation for Decision Trees (ICML 2016)

  • Meta-Gradient Boosted Decision Tree Model for Weight and Target Learning (ICML 2016)

    • Yury Ustinovskiy, Valentina Fedorova, Gleb Gusev, Pavel Serdyukov
    • [Paper]

  • 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]

  • 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]

  • 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]

2015

  • Particle Gibbs for Bayesian Additive Regression Trees (AISTATS 2015)

    • Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh
    • [Paper]

  • DART: Dropouts meet Multiple Additive Regression Trees (AISTATS 2015)

  • Single target tracking using adaptive clustered decision trees and dynamic multi-level appearance models (CVPR 2015)

    • Jingjing Xiao, Rustam Stolkin, Ales Leonardis
    • [Paper]

  • Face alignment using cascade Gaussian process regression trees (CVPR 2015)

  • Tracking-by-Segmentation with Online Gradient Boosting Decision Tree (ICCV 2015)

    • Jeany Son, Ilchae Jung, Kayoung Park, Bohyung Han
    • [[Paper]](Tracking-by-Segmentation with Online Gradient Boosting Decision Tree)

  • Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees (ICML 2015)

    • Mathieu Serrurier, Henri Prade
    • [Paper]

  • A Decision Tree Framework for Spatiotemporal Sequence Prediction (KDD 2015)

    • Taehwan Kim, Yisong Yue, Sarah L. Taylor, Iain A. Matthews
    • [Paper]

  • Efficient Non-greedy Optimization of Decision Trees (NIPS 2015)

    • Mohammad Norouzi, Maxwell D. Collins, Matthew Johnson, David J. Fleet, Pushmeet Kohli
    • [Paper]

2014

  • On Building Decision Trees from Large-scale Data in Applications of On-line Advertising (CIKM 2014)

    • Shivaram Kalyanakrishnan, Deepthi Singh, Ravi Kant
    • [Paper]

  • Fast Supervised Hashing with Decision Trees for High-Dimensional Data (CVPR 2014)

    • Guosheng Lin, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, David Suter
    • [Paper]

  • One Millisecond Face Alignment with an Ensemble of Regression Trees (CVPR 2014)

    • Vahid Kazemi, Josephine Sullivan
    • [Paper]

  • Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost (ICML 2014)

    • Ferdinando Cicalese, Eduardo Sany Laber, Aline Medeiros Saettler
    • [Paper]

2013

  • Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria (ICCV 2013)

    • Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht
    • [Paper]

  • Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees (ICCV 2013)

    • Oisin Mac Aodha, Gabriel J. Brostow
    • [Paper]

  • Conformal Prediction Using Decision Trees (ICDM 2013)

    • Ulf Johansson, Henrik Boström, Tuve Löfström
    • [Paper]

  • 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]

  • Top-down particle filtering for Bayesian decision trees (ICML 2013)

    • Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh
    • [Paper]

  • Quickly Boosting Decision Trees - Pruning Underachieving Features Early (ICML 2013)

    • Ron Appel, Thomas J. Fuchs, Piotr Dollár, Pietro Perona
    • [Paper]

  • Knowledge Compilation for Model Counting: Affine Decision Trees (IJCAI 2013)

    • Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis, Samuel Thomas
    • [Paper]

2012

  • Regression Tree Fields - An efficient, non-parametric approach to image labeling problems (CVPR 2012)

    • Jeremy Jancsary, Sebastian Nowozin, Toby Sharp, Carsten Rother
    • [Paper]

  • ConfDTree: Improving Decision Trees Using Confidence Intervals (ICDM 2012)

    • Gilad Katz, Asaf Shabtai, Lior Rokach, Nir Ofek
    • [Paper]

  • Improved Information Gain Estimates for Decision Tree Induction (ICML 2012)

  • Learning Partially Observable Models Using Temporally Abstract Decision Trees (NIPS 2012)

2011

  • Incorporating Boosted Regression Trees into Ecological Latent Variable Models (AAAI 2011)

    • Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Dietterich
    • [Paper]

  • Syntactic Decision Tree LMs: Random Selection or Intelligent Design (EMNLP 2011)

    • Denis Filimonov, Mary P. Harper
    • [Paper]

  • Speeding-Up Hoeffding-Based Regression Trees With Options (ICML 2011)

    • Elena Ikonomovska, João Gama, Bernard Zenko, Saso Dzeroski
    • [Paper]

  • On the Complexity of Decision Making in Possibilistic Decision Trees (UAI 2011)

    • Hélène Fargier, Nahla Ben Amor, Wided Guezguez
    • [Paper]

  • Parallel boosted regression trees for web search ranking (WWW 2011)

    • Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal, Jennifer Paykin
    • [Paper]

2010

  • Discrimination Aware Decision Tree Learning (ICDM 2010)

    • Faisal Kamiran, Toon Calders, Mykola Pechenizkiy
    • [Paper]

  • Decision Trees for Uplift Modeling (ICDM 2010)

    • Piotr Rzepakowski, Szymon Jaroszewicz
    • [Paper]

  • Learning Markov Network Structure with Decision Trees (ICDM 2010)

  • Multivariate Dyadic Regression Trees for Sparse Learning Problems (NIPS 2010)

2009

  • Stochastic gradient boosted distributed decision trees (CIKM 2009)
    • Jerry Ye, Jyh-Herng Chow, Jiang Chen, Zhaohui Zheng
    • [Paper]

2008

  • Predicting Future Decision Trees from Evolving Data (ICDM 2008)

    • Mirko Böttcher, Martin Spott, Rudolf Kruse
    • [Paper]

  • Bayes optimal classification for decision trees (ICML 2008)

2007

  • Sample compression bounds for decision trees (ICML 2007)

  • 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]

  • Keep the Decision Tree and Estimate the Class Probabilities Using its Decision Boundary (IJCAI 2007)

    • Isabelle Alvarez, Stephan Bernard, Guillaume Deffuant
    • [Paper]

  • Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree (IJCAI 2007)

    • Claudia Henry, Richard Nock, Frank Nielsen
    • [Paper]

  • Scalable look-ahead linear regression trees (KDD 2007)

    • David S. Vogel, Ognian Asparouhov, Tobias Scheffer
    • [Paper]

  • Mining optimal decision trees from itemset lattices (KDD 2007)

    • Siegfried Nijssen, Élisa Fromont
    • [Paper]

2006

  • Decision Tree Methods for Finding Reusable MDP Homomorphisms (AAAI 2006)

    • Alicia P. Wolfe, Andrew G. Barto
    • [Paper]

  • A Fast Decision Tree Learning Algorithm (AAAI 2006)

  • Anytime Induction of Decision Trees: An Iterative Improvement Approach (AAAI 2006)

    • Saher Esmeir, Shaul Markovitch
    • [Paper]

  • When a Decision Tree Learner Has Plenty of Time (AAAI 2006)

    • Saher Esmeir, Shaul Markovitch
    • [Paper]

  • Decision Trees for Functional Variables (ICDM 2006)

    • Suhrid Balakrishnan, David Madigan
    • [Paper]

  • 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]

2005

  • Representing Conditional Independence Using Decision Trees (AAAI 2005)

  • Use of Expert Knowledge for Decision Tree Pruning (AAAI 2005)

  • 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]

  • Exploiting Informative Priors for Bayesian Classification and Regression Trees (IJCAI 2005)

    • Nicos Angelopoulos, James Cussens
    • [Paper]

  • Ranking Cases with Decision Trees: a Geometric Method that Preserves Intelligibility (IJCAI 2005)

    • Isabelle Alvarez, Stephan Bernard
    • [Paper]

2004

  • On the Optimality of Probability Estimation by Random Decision Trees (AAAI 2004)

  • Occam's Razor and a Non-Syntactic Measure of Decision Tree Complexity (AAAI 2004)

  • 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]

  • Improving the Reliability of Decision Tree and Naive Bayes Learners (ICDM 2004)

    • David George Lindsay, Siân Cox
    • [Paper]

  • 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]

  • Detecting Structural Metadata with Decision Trees and Transformation-Based Learning (NAACL 2004)

    • Joungbum Kim, Sarah E. Schwarm, Mari Ostendorf
    • [Paper]

  • On the Adaptive Properties of Decision Trees (NIPS 2004)

    • Clayton D. Scott, Robert D. Nowak
    • [Paper]

2003

  • Postprocessing Decision Trees to Extract Actionable Knowledge (ICDM 2003)

    • Qiang Yang, Jie Yin, Charles X. Ling, Tielin Chen
    • [Paper]

  • K-D Decision Tree: An Accelerated and Memory Efficient Nearest Neighbor Classifier (ICDM 2003)

    • Tomoyuki Shibata, Takekazu Kato, Toshikazu Wada
    • [Paper]

  • Identifying Markov Blankets with Decision Tree Induction (ICDM 2003)

    • Lewis J. Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov
    • [Paper]

  • Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy (ICDM 2003)

    • Jin Huang, Jingjing Lu, Charles X. Ling
    • [Paper]

  • Boosting Lazy Decision Trees (ICML 2003)

    • Xiaoli Zhang Fern, Carla E. Brodley
    • [Paper]

  • Decision Tree with Better Ranking (ICML 2003)

    • Charles X. Ling, Robert J. Yan
    • [Paper]

  • Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction (IJCAI 2003)

  • Efficient decision tree construction on streaming data (KDD 2003)

    • Ruoming Jin, Gagan Agrawal
    • [Paper]

  • PaintingClass: interactive construction%2C visualization and exploration of decision trees (KDD 2003)

    • Soon Tee Teoh, Kwan-Liu Ma
    • [Paper]

  • Accurate decision trees for mining high-speed data streams (KDD 2003)

    • João Gama, Ricardo Rocha, Pedro Medas
    • [Paper]

  • Near-Minimax Optimal Classification with Dyadic Classification Trees (NIPS 2003)

    • Clayton D. Scott, Robert D. Nowak
    • [Paper]

2002

  • Solving the Fragmentation Problem of Decision Trees by Discovering Boundary Emerging Patterns (ICDM 2002)

  • Learning Decision Trees Using the Area Under the ROC Curve (ICML 2002)

    • César Ferri, Peter A. Flach, José Hernández-Orallo
    • [Paper]

  • Finding an Optimal Gain-Ratio Subset-Split Test for a Set-Valued Attribute in Decision Tree Induction (ICML 2002)

    • Fumio Takechi, Einoshin Suzuki
    • [Paper]

  • SECRET: a scalable linear regression tree algorithm (KDD 2002)

    • Alin Dobra, Johannes Gehrke
    • [Paper]

  • Instability of decision tree classification algorithms (KDD 2002)

    • Ruey-Hsia Li, Geneva G. Belford
    • [Paper]

  • Extracting decision trees from trained neural networks (KDD 2002)

  • Dyadic Classification Trees via Structural Risk Minimization (NIPS 2002)

    • Clayton D. Scott, Robert D. Nowak
    • [Paper]

2001

  • Japanese Named Entity Recognition based on a Simple Rule Generator and Decision Tree Learning (ACL 2001)

  • Message Length as an Effective Ockham's Razor in Decision Tree Induction (AISTATS 2001)

    • Scott Needham, David L. Dowe
    • [Paper]

  • SQL Database Primitives for Decision Tree Classifiers (CIKM 2001)

    • Kai-Uwe Sattler, Oliver Dunemann
    • [Paper]

  • Mining Decision Trees from Data Streams in a Mobile Environment (ICDM 2001)

    • Hillol Kargupta, Byung-Hoon Park
    • [Paper]

  • Efficient Determination of Dynamic Split Points in a Decision Tree (ICDM 2001)

    • David Maxwell Chickering, Christopher Meek, Robert Rounthwaite
    • [Paper]

  • A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods (ICDM 2001)

    • Bernard Zenko, Ljupco Todorovski, Saso Dzeroski
    • [Paper]

  • Efficient algorithms for decision tree cross-validation (ICML 2001)

    • Hendrik Blockeel, Jan Struyf
    • [Paper]

  • Bias Correction in Classification Tree Construction (ICML 2001)

    • Alin Dobra, Johannes Gehrke
    • [Paper]

  • Breeding Decision Trees Using Evolutionary Techniques (ICML 2001)

    • Athanassios Papagelis, Dimitrios Kalles
    • [Paper]

  • Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers (ICML 2001)

    • Bianca Zadrozny, Charles Elkan
    • [Paper]

  • Temporal Decision Trees or the lazy ECU vindicated (IJCAI 2001)

    • Luca Console, Claudia Picardi, Daniele Theseider Dupré
    • [Paper]

  • A Decision Tree of Bigrams is an Accurate Predictor of Word Sense (NAACL 2001)

1999

  • Modeling decision tree performance with the power law (AISTATS 1999)

    • Lewis J. Frey, Douglas H. Fisher
    • [Paper]

  • Causal Mechanisms and Classification Trees for Predicting Chemical Carcinogens (AISTATS 1999)

  • POS Tags and Decision Trees for Language Modeling (EMNLP 1999)

  • Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees (ICML 1999)

    • Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
    • [Paper]

  • The Alternating Decision Tree Learning Algorithm (ICML 1999)

  • Boosting with Multi-Way Branching in Decision Trees (NIPS 1999)

    • Yishay Mansour, David A. McAllester
    • [Paper]

1998

  • Learning Sorting and Decision Trees with POMDPs (ICML 1998)

    • Blai Bonet, Hector Geffner
    • [Paper]

  • Using a Permutation Test for Attribute Selection in Decision Trees (ICML 1998)

  • A Fast and Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization (ICML 1998)

    • Michael J. Kearns, Yishay Mansour
    • [Paper]

1997

  • Pessimistic decision tree pruning based Continuous-time (ICML 1997)

  • PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction (ICML 1997)

  • Option Decision Trees with Majority Votes (ICML 1997)

  • Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction (ICML 1997)

    • Ricardo Vilalta, Larry A. Rendell
    • [Paper]

  • Functional Models for Regression Tree Leaves (ICML 1997)

  • The Effects of Training Set Size on Decision Tree Complexity (ICML 1997)

    • Tim Oates, David D. Jensen
    • [Paper]

  • Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis (NIPS 1997)

    • Marcus Held, Joachim M. Buhmann
    • [Paper]

  • Data-Dependent Structural Risk Minimization for Perceptron Decision Trees (NIPS 1997)

    • John Shawe-Taylor, Nello Cristianini
    • [Paper]

  • Generalization in Decision Trees and DNF: Does Size Matter (NIPS 1997)

    • Mostefa Golea, Peter L. Bartlett, Wee Sun Lee, Llew Mason
    • [Paper]

1996

  • Second Tier for Decision Trees (ICML 1996)

  • Non-Linear Decision Trees - NDT (ICML 1996)

    • Andreas Ittner, Michael Schlosser
    • [Paper]

  • Learning Relational Concepts with Decision Trees (ICML 1996)

    • Peter Geibel, Fritz Wysotzki
    • [Paper]

1995

  • A Hill-Climbing Approach for Optimizing Classification Trees (AISTATS 1995)

    • Xiaorong Sun, Steve Y. Chiu, Louis Anthony Cox Jr.
    • [Paper]

  • An Exact Probability Metric for Decision Tree Splitting (AISTATS 1995)

  • On Pruning and Averaging Decision Trees (ICML 1995)

    • Jonathan J. Oliver, David J. Hand
    • [Paper]

  • On Handling Tree-Structured Attributed in Decision Tree Learning (ICML 1995)

    • Hussein Almuallim, Yasuhiro Akiba, Shigeo Kaneda
    • [Paper]

  • Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (ICML 1995)

    • Padhraic Smyth, Alexander G. Gray, Usama M. Fayyad
    • [Paper]

  • Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves (ICML 1995)

  • Efficient Algorithms for Finding Multi-way Splits for Decision Trees (ICML 1995)

    • Truxton Fulton, Simon Kasif, Steven Salzberg
    • [Paper]

  • Theory and Applications of Agnostic PAC-Learning with Small Decision Trees (ICML 1995)

    • Peter Auer, Robert C. Holte, Wolfgang Maass
    • [Paper]

  • Boosting Decision Trees (NIPS 1995)

    • Harris Drucker, Corinna Cortes
    • [Paper]

  • Using Pairs of Data-Points to Define Splits for Decision Trees (NIPS 1995)

    • Geoffrey E. Hinton, Michael Revow
    • [Paper]

  • A New Pruning Method for Solving Decision Trees and Game Trees (UAI 1995)

1994

  • A Statistical Approach to Decision Tree Modeling (ICML 1994)

  • In Defense of C4.5: Notes Learning One-Level Decision Trees (ICML 1994)

  • An Improved Algorithm for Incremental Induction of Decision Trees (ICML 1994)

  • Decision Tree Parsing using a Hidden Derivation Model (NAACL 1994)

    • Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Adwait Ratnaparkhi, Salim Roukos
    • [Paper]

1993

  • Using Decision Trees to Improve Case-Based Learning (ICML 1993)

1991

  • Context Dependent Modeling of Phones in Continuous Speech Using Decision Trees (NAACL 1991)
    • Lalit R. Bahl, Peter V. de Souza, P. S. Gopalakrishnan, David Nahamoo, Michael Picheny
    • [Paper]

1989

  • Performance Comparisons Between Backpropagation Networks and Classification Trees on Three Real-World Applications (NIPS 1989)
    • Les E. Atlas, Ronald A. Cole, Jerome T. Connor, Mohamed A. El-Sharkawi, Robert J. Marks II, Yeshwant K. Muthusamy, Etienne Barnard
    • [Paper]

1988

  • Multiple decision trees (UAI 1988)
    • Suk Wah Kwok, Chris Carter
    • [Paper]

1987

  • Decision Tree Induction Systems: A Bayesian Analysis (UAI 1987)

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