README.md

Gradient Boosting Papers

• Boosting Methodology for Regression Problems
• Extreme Gradient Boosting and Behavioral Biometrics
• A comparison of stacking with meta decision trees to other combining methods
• Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade
• Using RankBoost to Compare Retrieval Systems
• Gradient Boosting for Kernelized Output Spaces
• Surrogate Maximization/Minimization Algorithms for AdaBoost and the Logistic Regression Model
• Interactive Martingale Boosting
• Real Boosting a la Carte with an Application to Boosting Oblique Decision Trees
• Managing Domain Knowledge and Multiple Models with Boosting
• Information Theoretic Regularization for Semi-Supervised Boosting
• A Boosting Algorithm for Item Recommendation with Implicit Feedback
• Simple Training of Dependency Parsers via Structured Boosting
• Generalized Dictionary for Multitask Learning with Boosting
• UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits
• Boosting on a Budget: Sampling for Feature-Efficient Prediction
• Training Conditional Random Fields using Virtual Evidence Boosting
• ABC-Boost: Adaptive Base Class Boost for Multi-class Classification
• Boosted Backpropagation Learning for Training Deep Modular Networks
• AugBoost: Gradient Boosting Enhanced with Step-Wise Feature Augmentation
• Training-Time Optimization of a Budgeted Booster
• A Direct Boosting Approach for Semi-Supervised Classification
• Adaboost with Auto-Evaluation for Conversational Models
• Optimal and Adaptive Algorithms for Online Boosting
• Ensemble Neural Relation Extraction with Adaptive Boosting
• Generalized Boosting Algorithms for Convex Optimization
• The return of ADABOOST.MH: multi-class Hamming trees
• Boosted Local Structured HOG-LBP for Object Localization
• Boosted Generative Models
• The Boosting Effect of Exploratory Behaviors
• Verifying Robustness of Gradient Boosted Models
• Incorporating Boosted Regression Trees into Ecological Latent Variable Models
• A Boosted Multi-Task Model for Pedestrian Detection with Occlusion Handling
• Group Cost-Sensitive Boosting for Multi-Resolution Pedestrian Detection
• Boosting for Real-Time Multivariate Time Series Classification
• BagBoo: A Scalable Hybrid Bagging-the-Boosting Model
• Online Parallel Boosting
• Gradient Boosting for Sequence Alignment
• Learning to Boost Filamentary Structure Segmentation
• Boosting-based parse reranking with subtree features
• Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments
• FeatureWeighting and Selection Using Hypothesis Margin of Boosting
• Quickly Boosting Decision Trees - Pruning Underachieving Features Early
• BROOF: Exploiting Out-of-Bag Errors, Boosting and Random Forests for Effective Automated Classification - Online Appendix
• Asymmetric Boosting
• Efficient Active Learning with Boosting
• Robust Boosting and its Relation to Bagging
• Bagging Gradient-Boosted Trees for High Precision, Low Variance Ranking Models
• AdaBoost is Consistent
• Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting
• Convergence and Consistency of Regularized Boosting Algorithms with Stationary Beta-Mixing Observations
• Optimal and Adaptive Algorithms for Online Boosting
• One-Pass Boosting
• How Boosting the Margin Can Also Boost Classifier Complexity
• Boosting with Incomplete Information
• Boosting Noisy Data
• Experiments with a New Boosting Algorithm
• Boosting the margin: A new explanation for the effectiveness of voting methods
• A boosting regression approach to medical anatomy detection
• Incorporating Prior Knowledge into Boosting
• BoostVHT: Boosting Distributed Streaming Decision Trees
• Contextual models for object detection using boosted random fields
• Fast boosting using adversarial bandits
• Online Boosting Algorithms for Anytime Transfer and Multitask Learning
• Totally Corrective Boosting Algorithms that Maximize the Margin
• Boosting KNN Text Classification Accuracy by using Supervised Term Weighting Schemes
• An Improved Boosting Algorithm and its Application to Text Categorization
• Automatic Detection of Craters in Planetary Images: An Embedded Framework Using Feature Selection and Boosting
• Adversarial Training of Gradient-Boosted Decision Trees
• Boosting for Document Routing
• Group-based Learning — A Boosting Approach
• A General Magnitude-Preserving Boosting Algorithm for Search Ranking
• Deep Boosting
• Fast Boosting based Detection using Scale Invariant Multimodal Multiresolution Filtered Features
• Joint Real-time Object Detection and Pose Estimation Using Probabilistic Boosting Network
• LidarBoost: Depth Superresolution for ToF 3D Shape Scanning
• Efficient Boosted Exemplar-based Face Detection
• Facial Point Detection using Boosted Regression and Graph Models
• Boosting Bottom-up and Top-down Visual Features for Saliency Estimation
• Structured Regression Gradient Boosting
• Boosting Margin Based Distance Functions for Clustering
• Boosting with Structural Sparsity
• Selective Transfer Between Learning Tasks Using Task-Based Boosting
• SMOTEBoost: Improving Prediction of the Minority Class in Boosting
• Semi-Supervised MarginBoost
• FilterBoost: Regression and Classification on Large Datasets
• Parallel Boosted Regression Trees for Web Search Ranking
• An Efficient Boosting Algorithm for Combining Preferences
• A Robust Boosting Tracker with Minimum Error Bound in a Co-Training Framework
• Eigenboosting: Combining Discriminative and Generative Information
• Human Boosting
• Boosting the Feature Space: Text Classification for Unstructured Data on the Web
• Boosting Kernel Models for Regression
• Boosting Relational Sequence Alignments
• LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction
• General Functional Matrix Factorization Using Gradient Boosting
• Modeling Auction Price Uncertainty Using Boostingbased Conditional Density Estimation
• Boosting Lazy Decision Trees
• Boosting grammatical inference with confidence oracles
• A Smoothed Boosting Algorithm Using Probabilistic Output Codes
• Boosting for Regression Transfer
• Boosting with Online Binary Learners for the Multiclass Bandit Problem
• Query Learning Strategies Using Boosting and Bagging.
• Boosting a Complete Technique to Find MSS and MUS thanks to a Local Search Oracle
• Model-Shared Subspace Boosting for Multi-label Classification
• Boosting for Learning Multiple Classes with Imbalanced Class Distribution
• Kernel Sharing With Joint Boosting For Multi-Class Concept Detection
• Experimental Comparisons of Online and Batch Versions of Bagging and Boosting
• MARK: A Boosting Algorithm for Heterogeneous Kernel Models
• Boosting products of base classifiers
• A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains
• Gradient Feature Selection for Online Boosting
• Boosted Deformable Model for Human Body Alignment
• BDT: Gradient Boosted Decision Tables for High Accuracy and Scoring Efficiency
• Adaptive Martingale Boosting
• Random Classification Noise Defeats All Convex Potential Boosters
• Survey of Boosting from an Optimization Perspective
• Minimum Majority Classification and Boosting
• MKBoost: A framework of multiple kernel boosting
• Training Conditional Random Fields via Gradient Tree Boosting
• Boosting Support Vector Machines
• A Theory of Multiclass Boosting
• Semi-Supervised Boosting for Multi-Class Classification
• Multiclass Boosting with Hinge Loss based on Output Coding
• Multiclass Boosting with Hinge Loss based on Output Coding
• Fast and Light Boosting for Adaptive Mining of Data Streams
• CatBoost: unbiased boosting with categorical features
• Multi-Layered Gradient Boosting Decision Trees
• Obtaining Calibrated Probabilities from Boosting
• Discriminative Learning for Label Sequences via Boosting
• From Isolation to Cooperation: An Alternative View of a System of Experts
• Training Methods for Adaptive Boosting of Neural Networks
• Boosting Algorithms as Gradient Descent
• Boosting with Multi-Way Branching in Decision Trees
• Weak Learners and Improved Rates of Convergence in Boosting
• Boosting and Maximum Likelihood for Exponential Models
• Boosting Density Estimation
• Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
• Boosting Structured Prediction for Imitation Learning
• Boosting Algorithms for Maximizing the Soft Margin
• Boosting the Area Under the ROC Curve
• McRank: Learning to Rank Using Multiple Classification and Gradient Boosting
• Regularized Boost for Semi-Supervised Learning
• Boosting Classifier Cascades
• Multiclass Boosting: Theory and Algorithms
• Variance Penalizing AdaBoost
• Learning Image Descriptors with the Boosting-Trick
• A Boosting Framework on Grounds of Online Learning
• SEBOOST – Boosting Stochastic Learning Using Subspace Optimization Techniques
• SEBOOST – Boosting Stochastic Learning Using Subspace Optimization Techniques
• Optimal Action Extraction for Random Forests and Boosted Trees
• BIER - Boosting Independent Embeddings Robustly
• Online Bagging and Boosting
• Collaborative Boosting for Activity Classification in Microblogs
• Multiclass Boosting with Repartitioning
• GB-CENT: Gradient Boosted Categorical Embedding and Numerical Trees
• A Boosting Approach to Improving Pseudo-Relevance Feedback
• Gradient Boosting Factorization Machines
• XGBoost: A Scalable Tree Boosting System
• Learning First Order Logic Time Series Classifiers: Rules and Boosting
• Semantic Place Classification of Indoor Environments with Mobile Robots using Boosting
• Using output codes to boost multiclass learning problems
• Selective Gradient Boosting for Effective Learning to Rank
• A Boosting Algorithm for Learning Bipartite Ranking Functions with Partially Labeled Data
• Sharing Features in Multi-class Boosting via Group Sparsity
• Joint Coupled-Feature Representation and Coupled Boosting for AD Diagnosis
• Learning from Heterogeneous Sources via Gradient Boosting Consensus
• AdaRank: A Boosting Algorithm for Information Retrieval
• Tracking-by-Segmentation with Online Gradient Boosting Decision Tree
• Boosting Algorithms for Simultaneous Feature Extraction and Selection
• Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner
• A Convergence Rate Analysis for LogitBoost, MART and Their Variant
• Boosting multi-step autoregressive forecasts
• Linear Programming Boosting for Uneven Datasets
• Stochastic Gradient Boosted Distributed Decision Trees
• A Boosting Approach to Topic Spotting on Subdialogues
• Boosted Dyadic Kernel Discriminants
• Boosting Adaptive Linear Weak Classifiers for Online Learning and Tracking
• Boosting for Transfer Learning
• Advances in Boosting
• DynamicBoost: Boosting Time Series Generated by Dynamical Systems
• Boosted Multi-Task Learning for Face Verification With Applications to Web Image and Video Search
• Logistic Regression and Boosting for Labeled Bags of Instances