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Methodology
← Core Methods
Machine Learning
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Core Methods
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Metric Learning
2800 directly classified papers
Papers per year
2001: 1
2002: 1
2003: 7
2004: 7
2005: 6
2006: 14
2007: 11
2008: 10
2009: 25
2010: 21
2011: 28
2012: 35
2013: 80
2014: 54
2015: 101
2016: 85
2017: 135
2018: 154
2019: 303
2020: 257
2021: 306
2022: 290
2023: 317
2024: 242
2025: 216
2026: 94
Papers
Adaptive Feature Discrimination and Denoising for Asymmetric Text Matching
COLING 2022
Learning Representations via a Robust Behavioral Metric for Deep Reinforcement Learning
NIPS 2022
Target Confusion in End-to-end Speaker Extraction: Analysis and Approaches
INTERSPEECH 2022
Deconfounded Representation Similarity for Comparison of Neural Networks
NIPS 2022
On Metric Learning for Audio-Text Cross-Modal Retrieval
INTERSPEECH 2022
Extractive Entity-Centric Summarization as Sentence Selection using Bi-Encoders
IJCNLP 2022
Maximizing Cosine Similarity Between Spatial Features for Unsupervised Domain Adaptation in Semantic Segmentation
WACV 2022
SeeTek: Very Large-Scale Open-Set Logo Recognition With Text-Aware Metric Learning
WACV 2022
Template based Graph Neural Network with Optimal Transport Distances
NIPS 2022
Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization
EMNLP 2022
Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors
ICML 2022
Metaphor Detection via Linguistics Enhanced Siamese Network
COLING 2022
Kernel similarity matching with Hebbian networks
NIPS 2022
GULP: a prediction-based metric between representations
NIPS 2022
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs
ICML 2022
C-MinHash: Improving Minwise Hashing with Circulant Permutation
ICML 2022
Evaluating Graph Generative Models with Contrastively Learned Features
NIPS 2022
Distributionally robust weighted k-nearest neighbors
NIPS 2022
DAVINZ: Data Valuation using Deep Neural Networks at Initialization
ICML 2022
Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action Recognition
WACV 2022
On the consistent estimation of optimal Receiver Operating Characteristic (ROC) curve
NIPS 2022
Quantifying and Learning Linear Symmetry-Based Disentanglement
ICML 2022
Measuring Representational Robustness of Neural Networks Through Shared Invariances
ICML 2022
Multi-Head Deep Metric Learning Using Global and Local Representations
WACV 2022
Generalization and Robustness Implications in Object-Centric Learning
ICML 2022
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