Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: Optimal Binary Classifier Aggregation for General Losses
loss functions for binary class probability estimation and classification : structure and applications .
On the equivalence between Kolmogorov-Smirnov and ROC curve metrics for binary classification
Optimizing the Multiclass F-Measure via Biconcave Programming
Hierarchical loss for classification.
On the relation between accuracy and fairness in binary classification
Data-Dependent Generalization Bounds for Multi-Class Classification
An Overview of Classifier Fusion Methods
Large-scale detection of non-technical losses in imbalanced data sets
Rethinking Feature Distribution for Loss Functions in Image Classification
A loss function for classification based on a robust similarity metric
P-N learning: Bootstrapping binary classifiers by structural constraints
Chapter 2 – Classifiers Based on Bayes Decision Theory
Multi-class least squares classification at binary-classification complexity
Bag-Level Aggregation for Multiple-Instance Active Learning in Instance Classification Problems
The Effect of Class Distribution on Classifier Learning: An Empirical Study
Comparative Evaluation of Binary Features
Reconstruction of training samples from loss functions
Multi-class cost-sensitive boosting with p-norm loss functions
Multiclass From Binary: Expanding One-Versus-All, One-Versus-One and ECOC-Based Approaches
Feature-cost sensitive learning with submodular trees of classifiers
Understanding the consumer: Multi-modal market research on consumer attitudes in Germany towards lightweight furniture and lightweight materials in furniture design
Strictly Proper Scoring Rules, Prediction, and Estimation
Discrete Event Simulation for Performance Modelling in Healthcare : A Review of the Literature
Toward Blockchain-Based Accounting and Assurance.
Spatial-Aware Hierarchical Collaborative Deep Learning for POI Recommendation