spencerai / awesome-decision-tree-papers

A collection of research papers on decision, classification and regression trees with implementations.

Awesome decision tree research papers

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

• Machine learning
  • NeurIPS
  • ICML
  • ICLR
• Computer vision
  • CVPR
  • ICCV
  • ECCV
• Natural language processing
  • ACL
  • NAACL
  • EMNLP
• Data
  • KDD
  • ICDM
  • WWW
• Artificial intelligence
  • AAAI
  • IJCAI
  • UAI

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)

  • Jessa Bekker, Jesse Davis
  • [Paper]

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

  • Shlomi Maliah, Guy Shani
  • [Paper]

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

  • Takuhiro Kaneko, Kaoru Hiramatsu, Kunio Kashino
  • [Paper]
  • [Code]

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

  • Viktor Losing, Heiko Wersing, Barbara Hammer
  • [Paper]
  • [Code]

• 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)

  • Ji Feng, Yang Yu, Zhi-Hua Zhou
  • [Paper]
  • [Code]

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)

  • Salvatore Ruggieri
  • [Paper]

• 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)

  • Weiwei Liu, Ivor W. Tsang
  • [Paper]

• 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)

  • Lixin Fan
  • [Paper]

• 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)

  • Korlakai Vinayak Rashmi, Ran Gilad-Bachrach
  • [Paper]
  • [Code]

• 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)

  • Donghoon Lee, Hyunsin Park, Chang Dong Yoo
  • [Paper]
  • [Code]

• 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)

  • Sebastian Nowozin
  • [Paper]

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

  • Erik Talvitie
  • [Paper]

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)

  • Daniel Lowd, Jesse Davis
  • [Paper]

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

  • Han Liu, Xi Chen
  • [Paper]

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)

  • Siegfried Nijssen
  • [Paper]

2007

• Sample compression bounds for decision trees (ICML 2007)

  • Mohak Shah
  • [Paper]

• 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)

  • Jiang Su, Harry Zhang
  • [Paper]

• 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)

  • Jiang Su, Harry Zhang
  • [Paper]

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

  • Jingfeng Cai, John Durkin
  • [Paper]

• 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)

  • Wei Fan
  • [Paper]

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

  • Goutam Paul
  • [Paper]

• 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)

  • David Page, Soumya Ray
  • [Paper]

• 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)

  • Jinyan Li, Limsoon Wong
  • [Paper]

• 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)

  • Olcay Boz
  • [Paper]

• 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)

  • Hideki Isozaki
  • [Paper]

• 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)

  • Ted Pedersen
  • [Paper]

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)

  • Louis Anthony Cox Jr.
  • [Paper]

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

  • Peter A. Heeman
  • [Paper]

• 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)

  • Yoav Freund, Llew Mason
  • [Paper]
  • [Code]

• 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)

  • Eibe Frank, Ian H. Witten
  • [Paper]

• 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)

  • Yishay Mansour
  • [Paper]

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

  • Scott E. Decatur
  • [Paper]

• Option Decision Trees with Majority Votes (ICML 1997)

  • Ron Kohavi, Clayton Kunz
  • [Paper]

• 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)

  • Luís Torgo
  • [Paper]

• 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)

  • Miroslav Kubat
  • [Paper]

• 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)

  • J. Kent Martin
  • [Paper]

• 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)

  • David J. Lubinsky
  • [Paper]

• 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)

  • Prakash P. Shenoy
  • [Paper]

1994

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

  • Michael I. Jordan
  • [Paper]

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

  • Tapio Elomaa
  • [Paper]

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

  • Paul E. Utgoff
  • [Paper]

• 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)
  • Claire Cardie
  • [Paper]

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)
  • Wray L. Buntine
  • [Paper]