Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Predicting good probabilities with supervised learning
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers
Probabilistic machine learning and artificial intelligence
A probabilistic methodology for multilabel classification
Deep learning of support vector machines with class probability output networks
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
An empirical study of the naive Bayes classifier
Unsupervised Learning by Probabilistic Latent Semantic Analysis
A note on Platt’s probabilistic outputs for support vector machines
Predictive learning via rule ensembles
Inducing probabilistic relational rules from probabilistic examples
Posterior probability support vector Machines for unbalanced data
Lifted First-Order Probabilistic Inference
Rule-Based Neural Networks for Classification and Probability Estimation
How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets
Cross-Validation and the Estimation of Conditional Probability Densities
Probabilistic Reasoning via Deep Learning: Neural Association Models
A Tutorial on Learning With Bayesian Networks
Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory
Unsupervised Learning with Stein's Unbiased Risk Estimator
Predicting distributions with Linearizing Belief Networks
An Empirical Investigation of Antecedents of Internet Abuse in the Workplace
De-constructing depersonalization: Further evidence for symptom clusters
Ultra-wide stopband in a compact low pass filter using stepped impedance resonators and novel techniques
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
Adaptive and context-aware service composition for IoT-based smart cities