Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Obtaining Calibrated Probabilities from Boosting
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Predicting good probabilities with supervised learning
Automatic Gradient Boosting
Multiclass Boosting: Theory and Algorithms
On the importance of accurate weak classifier learning for boosted weak classifiers
Self Supervised Boosting
Weighted Sampling for Large-Scale Boosting
Visual Diagnosis of Tree Boosting Methods
Query Learning Strategies Using Boosting and Bagging
QBoost: Predicting quantiles with boosting for regression and binary classification
Improving naive Bayes classifier using conditional probabilities
Functional Frank-Wolfe Boosting for General Loss Functions
XGBoost : Reliable Large-scale Tree Boosting System
Gradient Boosting With Piece-Wise Linear Regression Trees
An Efficient Boosting Algorithm for Combining Preferences
Probabilistic graphical models for boosting cardinal and ordinal peer grading in MOOCs
Evaluating boosting algorithms to classify rare classes: comparison and improvements
Real AdaBoost : boosting for credit scorecards and similarity to WOE logistic regression
Experiments with a New Boosting Algorithm
Online bagging and boosting
Projection Pursuit Regression
The activation of attentional networks
Video Quality Assessment Based on Structural Distortion Measurement
Colorectal Cancer
Using Background Knowledge in Multilayer Perceptron Learning