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Extreme Multi-Label Classification

Extreme Multi-Label Classification is a supervised learning problem where an instance may be associated with multiple labels. The two main problems are the unbalanced labels in the dataset and the amount of different labels.

Papers

Showing 5175 of 75 papers

TitleStatusHype
Investigating Active Learning Sampling Strategies for Extreme Multi Label Text Classification0
Label Disentanglement in Partition-based Extreme Multilabel Classification0
DiSMEC - Distributed Sparse Machines for Extreme Multi-label ClassificationCode0
Dense Retrieval as Indirect Supervision for Large-space Decision MakingCode0
Dual-Encoders for Extreme Multi-Label ClassificationCode0
Learning a Compressed Sensing Measurement Matrix via Gradient UnrollingCode0
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood AggregationCode0
Deep Extreme Multi-label LearningCode0
Priberam at MESINESP Multi-label Classification of Medical Texts TaskCode0
A no-regret generalization of hierarchical softmax to extreme multi-label classificationCode0
Taming Pretrained Transformers for Extreme Multi-label Text ClassificationCode0
Bonsai -- Diverse and Shallow Trees for Extreme Multi-label ClassificationCode0
Extreme Multi-label Learning for Semantic Matching in Product SearchCode0
MDACE: MIMIC Documents Annotated with Code EvidenceCode0
Multi-label Learning with Random Circular VectorsCode0
Adaptive Elastic Training for Sparse Deep Learning on Heterogeneous Multi-GPU ServersCode0
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood PredictionCode0
Generalized test utilities for long-tail performance in extreme multi-label classificationCode0
Revisiting the Vector Space Model: Sparse Weighted Nearest-Neighbor Method for Extreme Multi-Label ClassificationCode0
HFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text CategorizationCode0
Top-k eXtreme Contextual Bandits with Arm HierarchyCode0
ICXML: An In-Context Learning Framework for Zero-Shot Extreme Multi-Label ClassificationCode0
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label ClassificationCode0
Adversarial Extreme Multi-label ClassificationCode0
Stratified Sampling for Extreme Multi-Label DataCode0
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