Results 11 to 20 of about 26,557 (311)
CONTRASTIVE GRAMMAR AS A LEARNING STRATEGY [PDF]
1st Annual International Conference on Language, Literature & Linguistics (L3 2012), 2012 Contrastive grammar is an excellent strategy that can accelerate the learning of new concepts by using previous knowledge. It is a very effective tool for both teaching as well as learning a foreign language. The following article aims to demonstrate how contrastive grammar has been and continues to be pertinent, and is being increasingly used as an ...
Monika Ciesielkiewicz +1 more
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Boosting Graph Contrastive Learning via Adaptive Sampling [PDF]
, 2023 Contrastive learning (CL) is a prominent technique for self-supervised representation learning, which aims to contrast semantically similar (i.e., positive) and dissimilar (i.e., negative) pairs of examples under different augmented views.
Chen Gong +13 more
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Aglinskas/Contrastive-Machine-Learning-reveals-the-structure-of-individual-variation-in-ASD: Code Release for reproducibility [PDF]
, 2022 Code and materials for the analyses presented in the manuscript "Contrastive machine learning reveals the structure of neuroanatomical variation within ...
Aidas Aglinskas
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Equivariant Contrastive Learning
CoRR, 2021 In state-of-the-art self-supervised learning (SSL) pre-training produces semantically good representations by encouraging them to be invariant under meaningful transformations prescribed from human knowledge. In fact, the property of invariance is a trivial instance of a broader class called equivariance, which can be intuitively understood as the ...
Rumen Dangovski +7 more
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Dual Space Graph Contrastive Learning [PDF]
, 2022 Unsupervised graph representation learning has emerged as a powerful tool to address real-world problems and achieves huge success in the graph learning domain.
Li, L +5 more
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An Asymmetric Contrastive Loss for Handling Imbalanced Datasets
Entropy, 2022 Contrastive learning is a representation learning method performed by contrasting a sample to other similar samples so that they are brought closely together, forming clusters in the feature space.
Valentino Vito, Lim Yohanes Stefanus
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What Should Not Be Contrastive in Contrastive Learning
CoRR, 2020 Published as a conference paper at ICLR ...
Tete Xiao +3 more
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Contrastive and attentive graph learning for multi-view clustering [PDF]
, 2022 Graph-based multi-view clustering aims to take advantage of multiple view graph information to provide clustering solutions. The consistency constraint of multiple views is the key of multi-view graph clustering.
Li, Lin +4 more
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SigRep: Toward Robust Wearable Emotion Recognition With Contrastive Representation Learning [PDF]
, 2022 Extracting emotions from physiological signals has become popular over the past decade. Recent advancements in wearable smart devices have enabled capturing physiological signals continuously and unobtrusively.
Rana, Rajib +6 more
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SelfCCL: Curriculum Contrastive Learning by Transferring Self-Taught Knowledge for Fine-Tuning BERT
Applied Sciences, 2023 BERT, the most popular deep learning language model, has yielded breakthrough results in various NLP tasks. However, the semantic representation space learned by BERT has the property of anisotropy.
Somaiyeh Dehghan, Mehmet Fatih Amasyali
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