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Supervised Learning

988 directly classified papers

Papers per year

Papers

Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data JMLR 2020
High-dimensional Linear Discriminant Analysis Classifier for Spiked Covariance Model JMLR 2020
Robust high dimensional learning for Lipschitz and convex losses JMLR 2020
Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection JMLR 2020
Learning from Noisy Labels via Discrepant Collaborative Training WACV 2020
SocCogCom at SemEval-2020 Task 11: Characterizing and Detecting Propaganda Using Sentence-Level Emotional Salience Features COLING 2020
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust ICML 2020
Generalized and Scalable Optimal Sparse Decision Trees ICML 2020
Optimal Margin Distribution Machine for Multi-Instance Learning IJCAI 2020
Contextualized Point-of-Interest Recommendation IJCAI 2020
Human Consensus-Oriented Image Captioning IJCAI 2020
Structured Probabilistic End-to-End Learning from Crowds IJCAI 2020
Can Cross Entropy Loss Be Robust to Label Noise? IJCAI 2020
Learning Interpretable Models in the Property Specification Language IJCAI 2020
Label Distribution for Learning with Noisy Labels IJCAI 2020
Turning 30: New Ideas in Inductive Logic Programming IJCAI 2020
FEARLESS STEPS Challenge (FS-2): Supervised Learning with Massive Naturalistic Apollo Data INTERSPEECH 2020
On Synthesis for Supervised Monaural Speech Separation in Time Domain INTERSPEECH 2020
Active Learning in the Geometric Block Model AAAI 2020
Transparent Classification with Multilayer Logical Perceptrons and Random Binarization AAAI 2020
Predicting the Topical Stance and Political Leaning of Media using Tweets ACL 2020
Neural Temporal Opinion Modelling for Opinion Prediction on Twitter ACL 2020
SetConv: A New Approach for Learning from Imbalanced Data EMNLP 2020
TNT: Text Normalization based Pre-training of Transformers for Content Moderation EMNLP 2020
IGT2P: From Interlinear Glossed Texts to Paradigms EMNLP 2020