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Methodology
← Learning Types
Machine Learning
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Learning Types
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Classification
1251 directly classified papers
Papers per year
2000: 1
2001: 1
2003: 2
2004: 1
2005: 1
2006: 18
2007: 9
2008: 14
2009: 7
2010: 12
2011: 10
2012: 26
2013: 22
2014: 29
2015: 21
2016: 28
2017: 57
2018: 66
2019: 92
2020: 110
2021: 139
2022: 148
2023: 164
2024: 142
2025: 130
2026: 1
Papers
Error-Bounded Correction of Noisy Labels
ICML 2020
Exploring aspects of similarity between spoken personal narratives by disentangling them into narrative clause types
ACL 2020
Methods for Extracting Information from Messages from Primary Care Providers to Specialists
ACL 2020
Hierarchical Evidence Set Modeling for Automated Fact Extraction and Verification
EMNLP 2020
A State-independent and Time-evolving Network for Early Rumor Detection in Social Media
EMNLP 2020
LGPSolver - Solving Logic Grid Puzzles Automatically
EMNLP 2020
Improving Confidence Estimates for Unfamiliar Examples
CVPR 2020
Distilling Effective Supervision From Severe Label Noise
CVPR 2020
M2m: Imbalanced Classification via Major-to-Minor Translation
CVPR 2020
Making Better Mistakes: Leveraging Class Hierarchies With Deep Networks
CVPR 2020
Equalization Loss for Long-Tailed Object Recognition
CVPR 2020
Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays
ACL 2020
Noise Pollution in Hospital Readmission Prediction: Long Document Classification with Reinforcement Learning
ACL 2020
Comparative Analysis of Text Classification Approaches in Electronic Health Records
ACL 2020
Out of the Echo Chamber: Detecting Countering Debate Speeches
ACL 2020
Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness
ACL 2020
Implicit Discourse Relation Classification: We Need to Talk about Evaluation
ACL 2020
Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event
ACL 2020
Will-They-Won’t-They: A Very Large Dataset for Stance Detection on Twitter
ACL 2020
Semi-supervised learning, causality, and the conditional cluster assumption
UAI 2020
Federated Learning with Only Positive Labels
ICML 2020
Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function Class
NIPS 2020
A Fair Classifier Using Kernel Density Estimation
NIPS 2020
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning
NIPS 2020
Efficient active learning of sparse halfspaces with arbitrary bounded noise
NIPS 2020
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