negative sampling - Robuta Search

https://deepai.org/publication/rethinking-negative-sampling-for-unlabeled-entity-problem-in-named-entity-recognition Rethinking Negative Sampling for Unlabeled Entity Problem in Named Entity Recognition | DeepAI Aug 26, 2021 - 08/26/21 - In many situations (e.g., distant supervision), unlabeled entity problem seriously degrades the performances of named entity recog... negative sampling rethinking unlabeled https://www.amazon.science/publications/emc2-efficient-mcmc-negative-sampling-for-contrastive-learning-with-global-convergence EMC2: Efficient MCMC negative sampling for contrastive learning with global convergence - Amazon... A key challenge in contrastive learning is to generate negative samples from a large sample set to contrast with positive samples, for learning better encoding... negative sampling https://openreview.net/forum?id=pC5rTmBdB5&referrer=%5Bthe%20profile%20of%20Fang%20Wan%5D(%2Fprofile%3Fid%3D~Fang_Wan1) Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection | OpenReview Multi-view 3D object detection systems often struggle with generating precise predictions due to the challenges in estimating depth from images, increasing... https://arxiv.org/abs/1402.3722?ref=ruder.io [1402.3722] word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method Abstract page for arXiv paper 1402.3722: word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method https://arxiv.org/abs/1809.01812 [1809.01812] Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency... Abstract page for arXiv paper 1809.01812: Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency https://deepai.org/publication/analysis-of-the-impact-of-negative-sampling-on-link-prediction-in-knowledge-graphs Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs | DeepAI Aug 22, 2017 - 08/22/17 - Knowledge graphs are large, useful, but incomplete knowledge repositories. They encode knowledge through entities and relations wh... https://deepai.org/publication/gsasrec-reducing-overconfidence-in-sequential-recommendation-trained-with-negative-sampling gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling |... Aug 14, 2023 - 08/14/23 - A large catalogue size is one of the central challenges in training recommendation models: a large number of items makes them memo... reducing overconfidence sequential recommendation trained https://aclanthology.org/2022.findings-acl.114/ A Transformational Biencoder with In-Domain Negative Sampling for Zero-Shot Entity Linking - ACL... Kai Sun, Richong Zhang, Samuel Mensah, Yongyi Mao, Xudong Liu. Findings of the Association for Computational Linguistics: ACL 2022. 2022.