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The natural world is abundant with concepts expressed via visual, acoustic, tactile, and linguistic modalities.
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Audio set: An ontology and human-labeled dataset for audio events
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Cross-domain and cross-modality transfer learning for multi-domain and multi-modality event detection
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Multimodal machine learning: A survey and taxonomy
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Bert: Pre-training of deep bidirectional transformers for language understanding
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A closer look at few-shot classification
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On the measure of intelligence
François Chollet · 2019
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Unsupervised domain adaptation via regularized conditional alignment
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Cross-modal data programming enables rapid medical machine learning
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Provable guarantees for gradient-based meta-learning
Mikhail Khodak, Maria-Florina Balcan, and Ameet Talwalkar · 2019
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Santlr: Speech annotation toolkit for low resource languages
Xinjian Li, Zhong Zhou, Siddharth Dalmia, Alan W Black, and Florian Metze · 2019
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Learning representations from imperfect time series data via tensor rank regularization
Paul Pu Liang, Zhun Liu, Yao-Hung Hubert Tsai, Qibin Zhao, Ruslan Salakhutdinov, and Louis-Philippe Morency · 2019
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Meta-learning with domain adaptation for few-shot learning under domain shift, 2019
Doyen Sahoo, Hung Le, Chenghao Liu, and Steven C. H. Hoi · 2019
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Tal Schuster, Ori Ram, Regina Barzilay, and Amir Globerson · 2019
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Cross-lingual alignment vs joint training: A comparative study and a simple unified framework
Zirui Wang, Jiateng Xie, Ruochen Xu, Yiming Yang, Graham Neubig, and Jaime Carbonell · 2019
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Adaptive cross-modal few-shot learning
Chen Xing, Negar Rostamzadeh, Boris Oreshkin, and Pedro O O. Pinheiro · 2019
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Category anchor-guided unsupervised domain adaptation for semantic segmentation
Qiming Zhang, Jing Zhang, Wei Liu, and Dacheng Tao · 2019
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Meta-learning in neural networks: A survey
Timothy Hospedales, Antreas Antoniou, Paul Micaelli, and Amos Storkey · 2020
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Geometry-aware domain adaptation for unsupervised alignment of word embeddings
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Tresnet: High performance gpu-dedicated architecture
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Foundations of multimodal co-learning
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