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Enhancing age-related postural sway classification using partial least squares-discriminant analysis and hybrid feature set
Feature sets in a machine learning algorithm can have an impact on the robustness, interpretability, and characterization of the data. To detect...
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Set-Based Counterfactuals in Partial Classification
Given a class label y assigned by a classifier to a point x in feature space, the counterfactual generation task, in its simplest form, consists of...
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Vectorial bent functions and partial difference sets
The objective of this article is to broaden the understanding of the connections between bent functions and partial difference sets. Recently, the...
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A multi-class partial hinge loss for partial label learning
As an important branch of weakly supervised learning, partial label learning (PLL) tackles the problem where each training instance is associated...
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Generalized characteristic sets and new multivariate difference dimension polynomials
We introduce a new type of characteristic sets of difference polynomials using a generalization of the concept of effective order to the case of...
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Multi-instance partial-label learning: towards exploiting dual inexact supervision
Weakly supervised machine learning algorithms are able to learn from ambiguous samples or labels, e.g., multi-instance learning or partial-label...
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Boundary Difference over Union Loss for Medical Image Segmentation
Medical image segmentation is crucial for clinical diagnosis. However, current losses for medical image segmentation mainly focus on overall...
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Reconciling Partial and Local Invertibility
Invertible programming languages specify transformations to be run in two directions, such as compression/decompression or encryption/decryption. Two...
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Multi-graph embedding for partial label learning
Partial label learning (PLL) is an essential weakly supervised learning method. In PLL, the example’s ground-truth label is unknown and hidden in a...
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Solving many-objective optimisation problems using partial dominance
Most optimisation problems have multiple, often conflicting, objectives. Due to the conflicting objectives, a single solution does not exist, and...
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Characterization of Exact One-Query Quantum Algorithms for Partial Boolean Functions
The query model (or black-box model) has attracted much attention from the communities of both classical and quantum computing. Usually, quantum...
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Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data
Ordinary differential equations (ODEs) are a widely used formalism for the mathematical modeling of dynamical systems, a task omnipresent in...
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Universal Model Adaptation by Style Augmented Open-set Consistency
Learning to recognize unknown target samples is of great importance for unsupervised domain adaptation (UDA). Open-set domain adaptation (OSDA) and...
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PE-MSC: partial entailment-based minimum set cover for text summarization
The notion of Textual Entailment (TE) is an established indicator of text connectedness. It captures semantic relationships between texts. Recently,...
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Partial Differential Equations
A partial differential equation (PDE) relates the quantities of a multivariate function and its various partial derivatives in an equation. An...
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Partial Multi-label Learning via Constraint Clustering
Multi-label learning (MLL) refers to a learning task where each instance is associated with a set of labels. However, in most real-world...
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Few-shot partial multi-label learning with synthetic features network
In partial multi-label learning (PML) problems, each training sample is partially annotated with a candidate label set, among which only a subset of...
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Crank-Nicolson ADI finite difference/compact difference schemes for the 3D tempered integrodifferential equation associated with Brownian motion
This paper proposes and analyzes a tempered fractional integrodifferential equation in three-dimensional (3D) space. The Crank-Nicolson (CN) method...