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Hierarchical Multi-label Classification

Multi-label classification is a standard machine learning problem in which an object can be associated with multiple labels. A hierarchical multi-label classification (HMC) problem is defined as a multi-label classification problem in which classes are hierarchically organized as a tree or as a directed acyclic graph (DAG), and in which every prediction must be coherent, i.e., respect the hierarchy constraint. The hierarchy constraint states that a datapoint belonging to a given class must also belong to all its ancestors in the hierarchy.

Papers

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Showing 1–25 of 48 papers

TitleStatusHype
Hierarchy-aware Biased Bound Margin Loss Function for Hierarchical Text ClassificationCode1
BCAmirs at SemEval-2024 Task 4: Beyond Words: A Multimodal and Multilingual Exploration of Persuasion in MemesCode1
HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text ClassificationCode1
HiTIN: Hierarchy-aware Tree Isomorphism Network for Hierarchical Text ClassificationCode1
Hierarchical Multi-Label Classification of Scientific DocumentsCode1
Semantic Probabilistic Layers for Neuro-Symbolic LearningCode1
Modeling Label Space Interactions in Multi-label Classification using Box EmbeddingsCode1
Multi-Label Classification Neural Networks with Hard Logical ConstraintsCode1
Joint Learning of Hyperbolic Label Embeddings for Hierarchical Multi-label ClassificationCode1
Coherent Hierarchical Multi-Label Classification NetworksCode1
Clinically-Inspired Hierarchical Multi-Label Classification of Chest X-rays with a Penalty-Based Loss FunctionCode0
Can Large Language Models Serve as Effective Classifiers for Hierarchical Multi-Label Classification of Scientific Documents at Industrial Scale?—0
Acoustic identification of individual animals with hierarchical contrastive learning—0
Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat ImageryCode0
Error Detection and Constraint Recovery in Hierarchical Multi-Label Classification without Prior KnowledgeCode0
Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation—0
IITK at SemEval-2024 Task 4: Hierarchical Embeddings for Detection of Persuasion Techniques in MemesCode0
Hierarchical Multi-label Classification for Fine-level Event Extraction from Aviation Accident Reports—0
Hierarchical Multi-Label Classification of Online Vaccine Concerns—0
Hierarchical Classification of Financial Transactions Through Context-Fusion of Transformer-based Embeddings and Taxonomy-aware Attention Layer—0
TLMCM Network for Medical Image Hierarchical Multi-Label Classification—0
Interdisciplinary Fairness in Imbalanced Research Proposal Topic Inference: A Hierarchical Transformer-based Method with Selective Interpolation—0
Geometric Relational Embeddings: A Survey—0
Enhancing Classification with Hierarchical Scalable Query on Fusion Transformer—0
Solution for the EPO CodeFest on Green Plastics: Hierarchical multi-label classification of patents relating to green plastics using deep learningCode0
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