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Ensemble Methods

233 directly classified papers

Papers per year

Papers

ACCEPT at SemEval-2023 Task 3: An Ensemble-based Approach to Multilingual Framing Detection SEMEVAL 2023
Towards Better Decision Forests: Forest Alternating Optimization CVPR 2023
NLP_CHRISTINE at SemEval-2023 Task 10: Utilizing Transformer Contextual Representations and Ensemble Learning for Sexism Detection on Social Media Texts ACL 2023
Investigating the Effectiveness of Multiple Expert Models Collaboration EMNLP 2023
Norm-constrained Score-level Ensemble for Spoofing Aware Speaker Verification INTERSPEECH 2022
Amrita_CEN at SemEval-2022 Task 6: A Machine Learning Approach for Detecting Intended Sarcasm using Oversampling SEMEVAL 2022
PILE: Pairwise Iterative Logits Ensemble for Multi-Teacher Labeled Distillation EMNLP 2022
Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model ACL 2022
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression JMLR 2022
Tree-Based Models for Correlated Data JMLR 2022
KADO@LT-EDI-ACL2022: BERT-based Ensembles for Detecting Signs of Depression from Social Media Text ACL 2022
SOA_NLP@LT-EDI-ACL2022: An Ensemble Model for Hope Speech Detection from YouTube Comments ACL 2022
Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation NIPS 2022
Crowdsourcing Regression: A Spectral Approach AISTATS 2022
ASRtrans at SemEval-2022 Task 4: Ensemble of Tuned Transformer-based Models for PCL Detection NAACL 2022
Pushing the Envelope of Gradient Boosting Forests via Globally-Optimized Oblique Trees CVPR 2022
Ensemble Multi-Relational Graph Neural Networks IJCAI 2022
Trading Complexity for Sparsity in Random Forest Explanations AAAI 2022
NT5 at WMT 2022 General Translation Task EMNLP 2022
Boosted Dense Retriever NAACL 2022
RTM Super Learner Results at Quality Estimation Task EMNLP 2021
Written Justifications are Key to Aggregate Crowdsourced Forecasts EMNLP 2021
Anytime Inference with Distilled Hierarchical Neural Ensembles AAAI 2021
Versatile Verification of Tree Ensembles ICML 2021
Machine Unlearning for Random Forests ICML 2021