github.com/benedekrozemberczki/awesome-gradient-boosting-papers
A curated list of gradient and adaptive boosting papers with implementations from the following conferences:
Similar collections about graph classification, classification/regression tree, fraud detection, Monte Carlo tree search, and community detection papers with implementations.
Computing Abductive Explanations for Boosted Trees (AISTATS 2023)
Boosted Off-Policy Learning (AISTATS 2023)
Variational Boosted Soft Trees (AISTATS 2023)
Krylov-Bellman boosting: Super-linear policy evaluation in general state spaces (AISTATS 2023)
FairGBM: Gradient Boosting with Fairness Constraints (ICLR 2023)
Gradient Boosting Performs Gaussian Process Inference (ICLR 2023)
TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion (AAAI 2022)
A Resilient Distributed Boosting Algorithm (ICML 2022)
Fast Provably Robust Decision Trees and Boosting (ICML 2022)
Building Robust Ensembles via Margin Boosting (ICML 2022)
Retrieval-Based Gradient Boosting Decision Trees for Disease Risk Assessment (KDD 2022)
Federated Functional Gradient Boosting (AISTATS 2022)
ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics (AISTATS 2022)
Precision-based Boosting (AAAI 2021)
BNN: Boosting Neural Network Framework Utilizing Limited Amount of Data (CIKM 2021)
Unsupervised Domain Adaptation for Static Malware Detection based on Gradient Boosting Trees (CIKM 2021)
Individually Fair Gradient Boosting (ICLR 2021)
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees (ICLR 2021)
AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models (ICLR 2021)
Uncertainty in Gradient Boosting via Ensembles (ICLR 2021)
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks (ICLR 2021)
GBHT: Gradient Boosting Histogram Transform for Density Estimation (ICML 2021)
Boosting for Online Convex Optimization (ICML 2021)
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting (ICML 2021)
SGLB: Stochastic Gradient Langevin Boosting (ICML 2021)
Self-boosting for Feature Distillation (IJCAI 2021)
Boosting Variational Inference With Locally Adaptive Step-Sizes (IJCAI 2021)
Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression (KDD 2021)
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction (KDD 2021)
Better Short than Greedy: Interpretable Models through Optimal Rule Boosting (SDM 2021)
A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains (AAAI 2020)
Practical Federated Gradient Boosting Decision Trees (AAAI 2020)
Privacy-Preserving Gradient Boosting Decision Trees (AAAI 2020)
Accelerating Gradient Boosting Machines (AISTATS 2020)
Scalable Feature Selection for Multitask Gradient Boosted Trees (AISTATS 2020)
Functional Gradient Boosting for Learning Residual-like Networks with Statistical Guarantees (AISTATS 2020)
Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost (IJCAI 2020)
MixBoost: Synthetic Oversampling using Boosted Mixup for Handling Extreme Imbalance (ICDM 2020)
Boosting for Control of Dynamical Systems (ICML 2020)
Quantum Boosting (ICML 2020)
Boosted Histogram Transform for Regression (ICML 2020)
Boosting Frank-Wolfe by Chasing Gradients (ICML 2020)
NGBoost: Natural Gradient Boosting for Probabilistic Prediction (ICML 2020)
Online Agnostic Boosting via Regret Minimization (NeurIPS 2020)
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst Case Rates (NeurIPS 2020)
Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks (NeurIPS 2020)
Gradient Boosted Normalizing Flows (NeurIPS 2020)
HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems (WSDM 2020)
Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME (AAAI 2019)
Verifying Robustness of Gradient Boosted Models (AAAI 2019)
Online Multiclass Boosting with Bandit Feedback (AISTATS 2019)
AdaFair: Cumulative Fairness Adaptive Boosting (CIKM 2019)
Interpretable MTL from Heterogeneous Domains using Boosted Tree (CIKM 2019)
Adversarial Training of Gradient-Boosted Decision Trees (CIKM 2019)
Fair Adversarial Gradient Tree Boosting (ICDM 2019)
Boosted Density Estimation Remastered (ICML 2019)
Lossless or Quantized Boosting with Integer Arithmetic (ICML 2019)
Optimal Minimal Margin Maximization with Boosting (ICML 2019)
Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number (ICML 2019)
Boosting for Comparison-Based Learning (IJCAI 2019)
AugBoost: Gradient Boosting Enhanced with Step-Wise Feature Augmentation (IJCAI 2019)
Gradient Boosting with Piece-Wise Linear Regression Trees (IJCAI 2019)
SpiderBoost and Momentum: Faster Variance Reduction Algorithms (NeurIPS 2019)
Faster Boosting with Smaller Memory (NeurIPS 2019)
Regularized Gradient Boosting (NeurIPS 2019)
Margin-Based Generalization Lower Bounds for Boosted Classifiers (NeurIPS 2019)
Minimal Variance Sampling in Stochastic Gradient Boosting (NeurIPS 2019)
Universal Boosting Variational Inference (NeurIPS 2019)
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks (NeurIPS 2019)
Block-distributed Gradient Boosted Trees (SIGIR 2019)
Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning (SIGIR 2019)
Boosted Generative Models (AAAI 2018)
Boosting Variational Inference: an Optimization Perspective (AISTATS 2018)
Online Boosting Algorithms for Multi-label Ranking (AISTATS 2018)
DualBoost: Handling Missing Values with Feature Weights and Weak Classifiers that Abstain (CIKM 2018)
Functional Gradient Boosting based on Residual Network Perception (ICML 2018)
Finding Influential Training Samples for Gradient Boosted Decision Trees (ICML 2018)
Learning Deep ResNet Blocks Sequentially using Boosting Theory (ICML 2018)
UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits (IJCAI 2018)
Adaboost with Auto-Evaluation for Conversational Models (IJCAI 2018)
Ensemble Neural Relation Extraction with Adaptive Boosting (IJCAI 2018)
CatBoost: Unbiased Boosting with Categorical Features (NIPS 2018)
Multitask Boosting for Survival Analysis with Competing Risks (NIPS 2018)
Multi-Layered Gradient Boosting Decision Trees (NIPS 2018)
Boosted Sparse and Low-Rank Tensor Regression (NIPS 2018)
Selective Gradient Boosting for Effective Learning to Rank (SIGIR 2018)
Boosting for Real-Time Multivariate Time Series Classification (AAAI 2017)
Cross-Domain Sentiment Classification via Topic-Related TrAdaBoost (AAAI 2017)
Extreme Gradient Boosting and Behavioral Biometrics (AAAI 2017)
FeaBoost: Joint Feature and Label Refinement for Semantic Segmentation (AAAI 2017)
Boosting Complementary Hash Tables for Fast Nearest Neighbor Search (AAAI 2017)
Gradient Boosting on Stochastic Data Streams (AISTATS 2017)
BoostVHT: Boosting Distributed Streaming Decision Trees (CIKM 2017)
Fast Boosting Based Detection Using Scale Invariant Multimodal Multiresolution Filtered Features (CVPR 2017)
BIER - Boosting Independent Embeddings Robustly (ICCV 2017)
An Analysis of Boosted Linear Classifiers on Noisy Data with Applications to Multiple-Instance Learning (ICDM 2017)
Variational Boosting: Iteratively Refining Posterior Approximations (ICML 2017)
Boosted Fitted Q-Iteration (ICML 2017)
A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency (ICML 2017)
Gradient Boosted Decision Trees for High Dimensional Sparse Output (ICML 2017)
Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization (IJCAI 2017)
Boosted Zero-Shot Learning with Semantic Correlation Regularization (IJCAI 2017)
BDT: Gradient Boosted Decision Tables for High Accuracy and Scoring Efficiency (KDD 2017)
CatBoost: Gradient Boosting with Categorical Features Support (NIPS 2017)
Cost Efficient Gradient Boosting (NIPS 2017)
AdaGAN: Boosting Generative Models (NIPS 2017)
LightGBM: A Highly Efficient Gradient Boosting Decision Tree (NIPS 2017)
Early Stopping for Kernel Boosting Algorithms: A General Analysis with Localized Complexities (NIPS 2017)
Online Multiclass Boosting (NIPS 2017)
Stacking Bagged and Boosted Forests for Effective Automated Classification (SIGIR 2017)
GB-CENT: Gradient Boosted Categorical Embedding and Numerical Trees (WWW 2017)
Group Cost-Sensitive Boosting for Multi-Resolution Pedestrian Detection (AAAI 2016)
Communication Efficient Distributed Agnostic Boosting (AISTATS 2016)
Logistic Boosting Regression for Label Distribution Learning (CVPR 2016)
Structured Regression Gradient Boosting (CVPR 2016)
L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization (ICDM 2016)
Meta-Gradient Boosted Decision Tree Model for Weight and Target Learning (ICML 2016)
Generalized Dictionary for Multitask Learning with Boosting (IJCAI 2016)
Self-Paced Boost Learning for Classification (IJCAI 2016)
Interactive Martingale Boosting (IJCAI 2016)
Optimal and Adaptive Algorithms for Online Boosting (IJCAI 2016)
Rating-Boosted Latent Topics: Understanding Users and Items with Ratings and Reviews (IJCAI 2016)
XGBoost: A Scalable Tree Boosting System (KDD 2016)
Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments (KDD 2016)
Boosting with Abstention (NIPS 2016)
SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques (NIPS 2016)
Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition (NIPS 2016)
Generalized BROOF-L2R: A General Framework for Learning to Rank Based on Boosting and Random Forests (SIGIR 2016)
Online Boosting Algorithms for Anytime Transfer and Multitask Learning (AAAI 2015)
A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling (AAAI 2015)
Efficient Second-Order Gradient Boosting for Conditional Random Fields (AISTATS 2015)
Tumblr Blog Recommendation with Boosted Inductive Matrix Completion (CIKM 2015)
Basis mapping based boosting for object detection (CVPR 2015)
Tracking-by-Segmentation with Online Gradient Boosting Decision Tree (ICCV 2015)
Learning to Boost Filamentary Structure Segmentation (ICCV 2015)
Optimal and Adaptive Algorithms for Online Boosting (ICML 2015)
Rademacher Observations, Private Data, and Boosting (ICML 2015)
Boosted Categorical Restricted Boltzmann Machine for Computational Prediction of Splice Junctions (ICML 2015)
A Direct Boosting Approach for Semi-supervised Classification (IJCAI 2015)
A Boosting Algorithm for Item Recommendation with Implicit Feedback (IJCAI 2015)
Training-Time Optimization of a Budgeted Booster (IJCAI 2015)
Optimal Action Extraction for Random Forests and Boosted Trees (KDD 2015)
Online Gradient Boosting (NIPS 2015)
BROOF: Exploiting Out-of-Bag Errors Boosting and Random Forests for Effective Automated Classification (SIGIR 2015)
Boosting Search with Deep Understanding of Contents and Users (WSDM 2015)
On Boosting Sparse Parities (AAAI 2014)
Joint Coupled-Feature Representation and Coupled Boosting for AD Diagnosis (CVPR 2014)
From Categories to Individuals in Real Time - A Unified Boosting Approach (CVPR 2014)
Efficient Boosted Exemplar-Based Face Detection (CVPR 2014)
Facial Expression Recognition via a Boosted Deep Belief Network (CVPR 2014)
Confidence-Rated Multiple Instance Boosting for Object Detection (CVPR 2014)
The Return of AdaBoost.MH: Multi-Class Hamming Trees (ICLR 2014)
Deep Boosting (ICML 2014)
A Convergence Rate Analysis for LogitBoost, MART and Their Variant (ICML 2014)
Boosting with Online Binary Learners for the Multiclass Bandit Problem (ICML 2014)
Boosting Multi-Step Autoregressive Forecasts (ICML 2014)
Dynamic Programming Boosting for Discriminative Macro-Action Discovery (ICML 2014)
Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting (ICML 2014)
A Multi-Class Boosting Method with Direct Optimization (KDD 2014)
Gradient Boosted Feature Selection (KDD 2014)
Multi-Class Deep Boosting (NIPS 2014)
Deconvolution of High Dimensional Mixtures via Boosting with Application to Diffusion-Weighted MRI of Human Brain (NIPS 2014)
A Drifting-Games Analysis for Online Learning and Applications to Boosting (NIPS 2014)
A Boosting Framework on Grounds of Online Learning (NIPS 2014)
Gradient Boosting Factorization Machines (RECSYS 2014)
Boosting Binary Keypoint Descriptors (CVPR 2013)
PerturBoost: Practical Confidential Classifier Learning in the Cloud (ICDM 2013)
Multiclass Semi-Supervised Boosting Using Similarity Learning (ICDM 2013)
Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner (ICML 2013)
General Functional Matrix Factorization Using Gradient Boosting (ICML 2013)
Margins, Shrinkage, and Boosting (ICML 2013)
Quickly Boosting Decision Trees - Pruning Underachieving Features Early (ICML 2013)
Human Boosting (ICML 2013)
Collaborative Boosting for Activity Classification in Microblogs (KDD 2013)
Direct 0-1 Loss Minimization and Margin Maximization with Boosting (NIPS 2013)
Reservoir Boosting : Between Online and Offline Ensemble Learning (NIPS 2013)
Non-Linear Domain Adaptation with Boosting (NIPS 2013)
Boosting in the Presence of Label Noise (UAI 2013)
Contextual Boost for Pedestrian Detection (CVPR 2012)
Shrink Boost for Selecting Multi-LBP Histogram Features in Object Detection (CVPR 2012)
Boosting Bottom-Up and Top-Down Visual Features for Saliency Estimation (CVPR 2012)
Boosting Algorithms for Simultaneous Feature Extraction and Selection (CVPR 2012)
Sharing Features in Multi-class Boosting via Group Sparsity (CVPR 2012)
Feature Weighting and Selection Using Hypothesis Margin of Boosting (ICDM 2012)
An AdaBoost Algorithm for Multiclass Semi-supervised Learning (ICDM 2012)
AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problem (ICML 2012)
An Online Boosting Algorithm with Theoretical Justifications (ICML 2012)
Learning Image Descriptors with the Boosting-Trick (NIPS 2012)
Accelerated Training for Matrix-norm Regularization: A Boosting Approach (NIPS 2012)
Learning from Heterogeneous Sources via Gradient Boosting Consensus (SDM 2012)
Selective Transfer Between Learning Tasks Using Task-Based Boosting (AAAI 2011)
Incorporating Boosted Regression Trees into Ecological Latent Variable Models (AAAI 2011)
FlowBoost - Appearance Learning from Sparsely Annotated Video (CVPR 2011)
AdaBoost on Low-Rank PSD Matrices for Metric Learning (CVPR 2011)
Boosted Local Structured HOG-LBP for Object Localization (CVPR 2011)
A Direct Formulation for Totally-Corrective Multi-Class Boosting (CVPR 2011)
Gated Classifiers: Boosting Under High Intra-class Variation (CVPR 2011)
TaylorBoost: First and Second-order Boosting Algorithms with Explicit Margin Control (CVPR 2011)
Robust and Efficient Regularized Boosting Using Total Bregman Divergence (CVPR 2011)
Treat Samples differently: Object Tracking with Semi-Supervised Online CovBoost (ICCV 2011)
LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction (ICDM 2011)
Learning Markov Logic Networks via Functional Gradient Boosting (ICDM 2011)
Boosting on a Budget: Sampling for Feature-Efficient Prediction (ICML 2011)
Multiclass Boosting with Hinge Loss based on Output Coding (ICML 2011)
Generalized Boosting Algorithms for Convex Optimization (ICML 2011)
Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach (IJCAI 2011)
Boosting with Maximum Adaptive Sampling (NIPS 2011)
The Fast Convergence of Boosting (NIPS 2011)
ShareBoost: Efficient Multiclass Learning with Feature Sharing (NIPS 2011)
Multiclass Boosting: Theory and Algorithms (NIPS 2011)
Variance Penalizing AdaBoost (NIPS 2011)
MKBoost: A Framework of Multiple Kernel Boosting (SDM 2011)
A Boosting Approach to Improving Pseudo-Relevance Feedback (SIGIR 2011)
Bagging Gradient-Boosted Trees for High Precision, Low Variance Ranking Models (SIGIR 2011)
Boosting as a Product of Experts (UAI 2011)
Parallel Boosted Regression Trees for Web Search Ranking (WWW 2011)
The Boosting Effect of Exploratory Behaviors (AAAI 2010)
Boosting-Based System Combination for Machine Translation (ACL 2010)
BagBoo: A Scalable Hybrid Bagging-the-Boosting Model (CIKM 2010)
Automatic Detection of Craters in Planetary Images: an Embedded Framework Using Feature Selection and Boosting (CIKM 2010)
Facial Point Detection Using Boosted Regression and Graph Models (CVPR 2010)
Boosting for Transfer Learning with Multiple Sources (CVPR 2010)
Efficient Rotation Invariant Object Detection Using Boosted Random Ferns (CVPR 2010)
Implicit Hierarchical Boosting for Multi-view Object Detection (CVPR 2010)
On-Line Semi-Supervised Multiple-Instance Boosting (CVPR 2010)
Online Multi-Class LPBoost (CVPR 2010)
Homotopy Regularization for Boosting (ICDM 2010)
Exploiting Local Data Uncertainty to Boost Global Outlier Detection (ICDM 2010)
Boosting Classifiers with Tightened L0-Relaxation Penalties (ICML 2010)
Boosting for Regression Transfer (ICML 2010)
Boosted Backpropagation Learning for Training Deep Modular Networks (ICML 2010)
Fast Boosting Using Adversarial Bandits (ICML 2010)
Boosting with Structure Information in the Functional Space: an Application to Graph Classification (KDD 2010)
Multi-task Learning for Boosting with Application to Web Search Ranking (KDD 2010)
A Theory of Multiclass Boosting (NIPS 2010)
Boosting Classifier Cascades (NIPS 2010)
Joint Cascade Optimization Using A Product Of Boosted Classifiers (NIPS 2010)
Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost (UAI 2010)
Feature Selection for Ranking Using Boosted Trees (CIKM 2009)
Boosting KNN Text Classification Accuracy by Using Supervised Term Weighting Schemes (CIKM 2009)
Stochastic Gradient Boosted Distributed Decision Trees (CIKM 2009)
A General Magnitude-Preserving Boosting Algorithm for Search Ranking (CIKM 2009)
Reducing Joint Boost-Based Multiclass Classification to Proximity Search (CVPR 2009)
Imbalanced RankBoost for Efficiently Ranking Large-Scale Image-Video Collections (CVPR 2009)
Regularized Multi-Class Semi-Supervised Boosting (CVPR 2009)
Learning to Associate: HybridBoosted Multi-Target Tracker for Crowded Scene (CVPR 2009)
Boosted Multi-task Learning for Face Verification with Applications to Web Image and Video Search (CVPR 2009)
LidarBoost: Depth Superresolution for ToF 3D Shape Scanning (CVPR 2009)
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking (EMNLP 2009)
Finding Shareable Informative Patterns and Optimal Coding Matrix for Multiclass Boosting (ICCV 2009)
RankBoost with L1 Regularization for Facial Expression Recognition and Intensity Estimation (ICCV 2009)
A Robust Boosting Tracker with Minimum Error Bound in a Co-Training Framework (ICCV 2009)
Tutorial Summary: Survey of Boosting from an Optimization Perspective (ICML 2009)
Boosting Products of Base Classifiers (ICML 2009)
ABC-boost: Adaptive Base Class Boost for Multi-Class Classification (ICML 2009)
Boosting with Structural Sparsity (ICML 2009)
Boosting Constrained Mutual Subspace Method for Robust Image-Set Based Object Recognition (IJCAI 2009)
Information Theoretic Regularization for Semi-supervised Boosting (KDD 2009)
Potential-Based Agnostic Boosting (NIPS 2009)
Positive Semidefinite Metric Learning with Boosting (NIPS 2009)
Boosting with Spatial Regularization (NIPS 2009)
Effective Boosting of Na%C3%AFve Bayesian Classifiers by Local Accuracy Estimation (PAKDD 2009)
Multi-resolution Boosting for Classification and Regression Problems (PAKDD 2009)
Efficient Active Learning with Boosting (SDM 2009)
Group-Based Learning: A Boosting Approach (CIKM 2008)
Semi-Supervised Boosting Using Visual Similarity Learning (CVPR 2008)
Mining Compositional Features for Boosting (CVPR 2008)
Boosted Deformable Model for Human Body Alignment (CVPR 2008)
Discriminative Modeling by Boosting on Multilevel Aggregates (CVPR 2008)
Face Alignment via Boosted Ranking Model (CVPR 2008)
Boosting Adaptive Linear Weak Classifiers for Online Learning and Tracking (CVPR 2008)
Detection with Multi-Exit Asymmetric Boosting (CVPR 2008)
Boosting Ordinal Features for Accurate and Fast Iris Recognition (CVPR 2008)
Adaptive and Compact Shape Descriptor by Progressive Feature Combination and Selection with Boosting (CVPR 2008)
Boosting Relational Sequence Alignments (ICDM 2008)
Boosting with Incomplete Information (ICML 2008)
ManifoldBoost: Stagewise Function Approximation for Fully-, Semi- and Un-supervised Learning (ICML 2008)
Random Classification Noise Defeats All Convex Potential Boosters (ICML 2008)
Multi-class Cost-Sensitive Boosting with P-norm Loss Functions (KDD 2008)
MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features (NIPS 2008)
PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning (NIPS 2008)
On the Design of Loss Functions for Classification: Theory, Robustness to Outliers, and SavageBoost (NIPS 2008)
Adaptive Martingale Boosting (NIPS 2008)
A Boosting Algorithm for Learning Bipartite Ranking Functions with Partially Labeled Data (SIGIR 2008)
Using Error-Correcting Output Codes with Model-Refinement to Boost Centroid Text Classifier (ACL 2007)
Fast Human Pose Estimation using Appearance and Motion via Multi-Dimensional Boosting Regression (CVPR 2007)
Generic Face Alignment using Boosted Appearance Model (CVPR 2007)
Eigenboosting: Combining Discriminative and Generative Information (CVPR 2007)
Online Learning Asymmetric Boosted Classifiers for Object Detection (CVPR 2007)
Improving Part based Object Detection by Unsupervised Online Boosting (CVPR 2007)
A Specialized Processor Suitable for AdaBoost-Based Detection with Haar-like Features (CVPR 2007)
Simultaneous Object Detection and Segmentation by Boosting Local Shape Feature based Classifier (CVPR 2007)
Compositional Boosting for Computing Hierarchical Image Structures (CVPR 2007)
Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition (CVPR 2007)
Object Classification in Visual Surveillance Using Adaboost (CVPR 2007)
A Boosting Regression Approach to Medical Anatomy Detection (CVPR 2007)
Joint Real-time Object Detection and Pose Estimation Using Probabilistic Boosting Network (CVPR 2007)
Kernel Sharing With Joint Boosting For Multi-Class Concept Detection (CVPR 2007)
Scale-Space Based Weak Regressors for Boosting (ECML 2007)
Avoiding Boosting Overfitting by Removing Confusing Samples (ECML 2007)
DynamicBoost: Boosting Time Series Generated by Dynamical Systems (ICCV 2007)
Incremental Learning of Boosted Face Detector (ICCV 2007)
Gradient Feature Selection for Online Boosting (ICCV 2007)
Fast Training and Selection of Haar Features Using Statistics in Boosting-based Face Detection (ICCV 2007)
Cluster Boosted Tree Classifier for Multi-View - Multi-Pose Object Detection (ICCV 2007)
Asymmetric Boosting (ICML 2007)
Boosting for Transfer Learning (ICML 2007)
Gradient Boosting for Kernelized Output Spaces (ICML 2007)
Boosting a Complete Technique to Find MSS and MUS Thanks to a Local Search Oracle (IJCAI 2007)
Training Conditional Random Fields Using Virtual Evidence Boosting (IJCAI 2007)
Simple Training of Dependency Parsers via Structured Boosting (IJCAI 2007)
Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree (IJCAI 2007)
Managing Domain Knowledge and Multiple Models with Boosting (IJCAI 2007)
Model-Shared Subspace Boosting for Multi-label Classification (KDD 2007)
Regularized Boost for Semi-Supervised Learning (NIPS 2007)
Boosting Algorithms for Maximizing the Soft Margin (NIPS 2007)
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting (NIPS 2007)
One-Pass Boosting (NIPS 2007)
Boosting the Area under the ROC Curve (NIPS 2007)
FilterBoost: Regression and Classification on Large Datasets (NIPS 2007)
A General Boosting Method and its Application to Learning Ranking Functions for Web Search (NIPS 2007)
Efficient Multiclass Boosting Classification with Active Learning (SDM 2007)
AdaRank: a Boosting Algorithm for Information Retrieval (SIGIR 2007)
Gradient Boosting for Sequence Alignment (AAAI 2006)
Boosting Kernel Models for Regression (ICDM 2006)
Boosting for Learning Multiple Classes with Imbalanced Class Distribution (ICDM 2006)
Boosting the Feature Space: Text Classification for Unstructured Data on the Web (ICDM 2006)
Totally Corrective Boosting Algorithms that Maximize the Margin (ICML 2006)
How Boosting the Margin Can Also Boost Classifier Complexity (ICML 2006)
Multiclass Boosting with Repartitioning (ICML 2006)
AdaBoost is Consistent (NIPS 2006)
Boosting Structured Prediction for Imitation Learning (NIPS 2006)
Chained Boosting (NIPS 2006)
When Efficient Model Averaging Out-Performs Boosting and Bagging (PKDD 2006)
Semantic Place Classification of Indoor Environments with Mobile Robots Using Boosting (AAAI 2005)
Boosting-based Parse Reranking with Subtree Features (ACL 2005)
Using RankBoost to Compare Retrieval Systems (CIKM 2005)
Classifier Fusion Using Shared Sampling Distribution for Boosting (ICDM 2005)
Semi-Supervised Mixture of Kernels via LPBoost Methods (ICDM 2005)
Efficient Discriminative Learning of Bayesian Network Classifier via Boosted Augmented Naive Bayes (ICML 2005)
Unifying the Error-Correcting and Output-Code AdaBoost within the Margin Framework (ICML 2005)
A Smoothed Boosting Algorithm Using Probabilistic Output Codes (ICML 2005)
Robust Boosting and its Relation to Bagging (KDD 2005)
Efficient Computations via Scalable Sparse Kernel Partial Least Squares and Boosted Latent Features (KDD 2005)
Multiple Instance Boosting for Object Detection (NIPS 2005)
Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations (NIPS 2005)
Boosted decision trees for word recognition in handwritten document retrieval (SIGIR 2005)
Obtaining Calibrated Probabilities from Boosting (UAI 2005)
Online Parallel Boosting (AAAI 2004)
A Boosting Approach to Multiple Instance Learning (ECML 2004)
A Boosting Algorithm for Classification of Semi-Structured Text (EMNLP 2004)
Text Classification by Boosting Weak Learners based on Terms and Concepts (ICDM 2004)
Boosting Grammatical Inference with Confidence Oracles (ICML 2004)
Surrogate Maximization/Minimization Algorithms for AdaBoost and the Logistic Regression Model (ICML 2004)
Training Conditional Random Fields via Gradient Tree Boosting (ICML 2004)
Boosting Margin Based Distance Functions for Clustering (ICML 2004)
Column-Generation Boosting Methods for Mixture of Kernels (KDD 2004)
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging (NIPS 2004)
Boosting on Manifolds: Adaptive Regularization of Base Classifiers (NIPS 2004)
Contextual Models for Object Detection Using Boosted Random Fields (NIPS 2004)
Generalization Error and Algorithmic Convergence of Median Boosting (NIPS 2004)
An Application of Boosting to Graph Classification (NIPS 2004)
Logistic Regression and Boosting for Labeled Bags of Instances (PAKDD 2004)
Fast and Light Boosting for Adaptive Mining of Data Streams (PAKDD 2004)
On Boosting and the Exponential Loss (AISTATS 2003)
Boosting Support Vector Machines for Text Classification through Parameter-Free Threshold Relaxation (CIKM 2003)
Learning Cross-Document Structural Relationships Using Boosting (CIKM 2003)
On Boosting Improvement: Error Reduction and Convergence Speed-Up (ECML 2003)
Boosting Lazy Decision Trees (ICML 2003)
On the Convergence of Boosting Procedures (ICML 2003)
Linear Programming Boosting for Uneven Datasets (ICML 2003)
Monte Carlo Theory as an Explanation of Bagging and Boosting (IJCAI 2003)
On the Dynamics of Boosting (NIPS 2003)
Mutual Boosting for Contextual Inference (NIPS 2003)
Boosting Versus Covering (NIPS 2003)
Multiple-Instance Learning via Disjunctive Programming Boosting (NIPS 2003)
Averaged Boosting: A Noise-Robust Ensemble Method (PAKDD 2003)
SMOTEBoost: Improving Prediction of the Minority Class in Boosting (PKDD 2003)
Minimum Majority Classification and Boosting (AAAI 2002)
Ranking Algorithms for Named Entity Extraction: Boosting and the Voted Perceptron (ACL 2002)
Boosting to Correct Inductive Bias in Text Classification (CIKM 2002)
How to Make AdaBoost.M1 Work for Weak Base Classifiers by Changing Only One Line of the Code (ECML 2002)
Scaling Boosting by Margin-Based Inclusionof Features and Relations (ECML 2002)
A Robust Boosting Algorithm (ECML 2002)
iBoost: Boosting Using an instance-Based Exponential Weighting Scheme (ECML 2002)
Boosting Density Function Estimators (ECML 2002)
Statistical Behavior and Consistency of Support Vector Machines, Boosting, and Beyond (ICML 2002)
A Boosted Maximum Entropy Model for Learning Text Chunking (ICML 2002)
Towards Large Margin Speech Recognizers by Boosting and Discriminative Training (ICML 2002)
Incorporating Prior Knowledge into Boosting (ICML 2002)
Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation (ICML 2002)
MARK: A Boosting Algorithm for Heterogeneous Kernel Models (KDD 2002)
Predicting rare classes: can boosting make any weak learner strong (KDD 2002)
Kernel Design Using Boosting (NIPS 2002)
FloatBoost Learning for Classification (NIPS 2002)
Discriminative Learning for Label Sequences via Boosting (NIPS 2002)
Boosting Density Estimation (NIPS 2002)
Self Supervised Boosting (NIPS 2002)
Boosted Dyadic Kernel Discriminants (NIPS 2002)
A Method to Boost Support Vector Machines (PAKDD 2002)
A Method to Boost Naive Bayesian Classifiers (PAKDD 2002)
Predicting Rare Classes: Comparing Two-Phase Rule Induction to Cost-Sensitive Boosting (PKDD 2002)
Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance (PKDD 2002)
Staged Mixture Modelling and Boosting (UAI 2002)
Advances in Boosting (UAI 2002)
Is Regularization Unnecessary for Boosting? (AISTATS 2001)
Online Bagging and Boosting (AISTATS 2001)
Text Categorization Using Transductive Boosting (ECML 2001)
Improving Term Extraction by System Combination Using Boosting (ECML 2001)
Analysis of the Performance of AdaBoost.M2 for the Simulated Digit-Recognition-Example (ECML 2001)
On the Practice of Branching Program Boosting (ECML 2001)
Boosting Mixture Models for Semi-supervised Learning (ICANN 2001)
A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods (ICDM 2001)
Using Boosting to Simplify Classification Models (ICDM 2001)
Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements (ICDM 2001)
Boosting Neighborhood-Based Classifiers (ICML 2001)
Boosting Noisy Data (ICML 2001)
Some Theoretical Aspects of Boosting in the Presence of Noisy Data (ICML 2001)
Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection (ICML 2001)
The Distributed Boosting Algorithm (KDD 2001)
Experimental Comparisons of Online and Batch Versions of Bagging and Boosting (KDD 2001)
Semi-supervised MarginBoost (NIPS 2001)
Boosting and Maximum Likelihood for Exponential Models (NIPS 2001)
Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade (NIPS 2001)
Boosting Localized Classifiers in Heterogeneous Databases (SDM 2001)
Boosted Wrapper Induction (AAAI 2000)
An Improved Boosting Algorithm and its Application to Text Categorization (CIKM 2000)
Boosting for Document Routing (CIKM 2000)
On the Boosting Pruning Problem (ECML 2000)
Boosting Applied to Word Sense Disambiguation (ECML 2000)
An Empirical Study of MetaCost Using Boosting Algorithms (ECML 2000)
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness (ICML 2000)
Comparing the Minimum Description Length Principle and Boosting in the Automatic Analysis of Discourse (ICML 2000)
A Boosting Approach to Topic Spotting on Subdialogues (ICML 2000)
A Comparative Study of Cost-Sensitive Boosting Algorithms (ICML 2000)
Boosting a Positive-Data-Only Learner (ICML 2000)
A Column Generation Algorithm For Boosting (ICML 2000)
A Gradient-Based Boosting Algorithm for Regression Problems (NIPS 2000)
Weak Learners and Improved Rates of Convergence in Boosting (NIPS 2000)
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes (PAKDD 2000)
Scaling Up a Boosting-Based Learner via Adaptive Sampling (PAKDD 2000)
Learning First Order Logic Time Series Classifiers: Rules and Boosting (PKDD 2000)
Bagging and Boosting with Dynamic Integration of Classifiers (PKDD 2000)
Text Filtering by Boosting Naive Bayes Classifiers (SIGIR 2000)
Boosting Methodology for Regression Problems (AISTATS 1999)
Boosting Applied to Tagging and PP Attachment (EMNLP 1999)
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees (ICML 1999)
AdaCost: Misclassification Cost-Sensitive Boosting (ICML 1999)
Boosting a Strong Learner: Evidence Against the Minimum Margin (ICML 1999)
Boosting Algorithms as Gradient Descent (NIPS 1999)
Boosting with Multi-Way Branching in Decision Trees (NIPS 1999)
Potential Boosters (NIPS 1999)
An Efficient Boosting Algorithm for Combining Preferences (ICML 1998)
Query Learning Strategies Using Boosting and Bagging (ICML 1998)
Regularizing AdaBoost (NIPS 1998)
Boosting the Margin: A New Explanation for the Effectiveness of Voting Methods (ICML 1997)
Using Output Codes to Boost Multiclass Learning Problems (ICML 1997)
Improving Regressors Using Boosting Techniques (ICML 1997)
Pruning Adaptive Boosting (ICML 1997)
Training Methods for Adaptive Boosting of Neural Networks (NIPS 1997)
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