most citedA Cross-Conformal Predictor for Multi-label Classification

7 citations · 7 across the 1 of their papers we have counts for

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cs.LG2023

Vesicoureteral Reflux Detection with Reliable Probabilistic Outputs

Harris Papadopoulos, George Anastassopoulos

Vesicoureteral Reflux (VUR) is a pediatric disorder in which urine flows backwards from the bladder to the upper urinary tract. Its detection is of great importance as it increases…

cs.LG2023

Reliable Probabilistic Classification with Neural Networks

Harris Papadopoulos

Venn Prediction (VP) is a new machine learning framework for producing well-calibrated probabilistic predictions. In particular it provides well-calibrated lower and upper bounds f…

cs.LG2023

Reliable Prediction Intervals with Regression Neural Networks

Harris Papadopoulos, Haris Haralambous

This paper proposes an extension to conventional regression Neural Networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required…

cs.LG2023

Well-calibrated Confidence Measures for Multi-label Text Classification with a Large Number of Labels

Lysimachos Maltoudoglou, Andreas Paisios, Ladislav Lenc +3

We extend our previous work on Inductive Conformal Prediction (ICP) for multi-label text classification and present a novel approach for addressing the computational inefficiency o…

cs.LG20227 cited

A Cross-Conformal Predictor for Multi-label Classification

Harris Papadopoulos

Unlike the typical classification setting where each instance is associated with a single class, in multi-label learning each instance is associated with multiple classes simultane…