#infrastructure #mle #apache_airflow #aws #l2r #ranking #learning_to_rank #google #team #bert #w2v #embeddings #complexity #complexity_per_layer #self_attention #rnn #linformer #big_bird
#indeed #team #Contextual_Embeddings
https://www.youtube.com/watch?v=2ipKSJBwriM&ab_channel=MLTArtificialIntelligence
#indeed #team #Contextual_Embeddings
https://www.youtube.com/watch?v=2ipKSJBwriM&ab_channel=MLTArtificialIntelligence
YouTube
Document Embeddings in Recommendation Systems
Talk by Jerry Chi, Data Science Manager at Indeed Tokyo. https://www.linkedin.com/in/jerrychi/
The talk includes:
* Brief overview of related concepts: Transformers, embeddings, and approximate nearest neighbors
* Using embeddings for retrieval vs. ranking…
The talk includes:
* Brief overview of related concepts: Transformers, embeddings, and approximate nearest neighbors
* Using embeddings for retrieval vs. ranking…
#contextual_embeddings #visualization #visualization_conference
https://www.youtube.com/watch?v=H9E7IeivX-Y&ab_channel=IEEEVisualizationConference
https://www.youtube.com/watch?v=H9E7IeivX-Y&ab_channel=IEEEVisualizationConference
YouTube
Visually Analyzing Contextualized Embeddings
Authors: Matthew Berger
VIS website: http://ieeevis.org/year/2020/welcome
In this paper we introduce a method for visually analyzing contextualized embeddings produced by deep neural network-based language models. Our approach is inspired by linguistic probes…
VIS website: http://ieeevis.org/year/2020/welcome
In this paper we introduce a method for visually analyzing contextualized embeddings produced by deep neural network-based language models. Our approach is inspired by linguistic probes…
#Contextual_Embeddings #ner #metrics #coNLL #stanford #team #glove #BERT
https://www.youtube.com/watch?v=bCPeg0Tp64s&ab_channel=HazyResearch
https://www.youtube.com/watch?v=bCPeg0Tp64s&ab_channel=HazyResearch
YouTube
Contextual Embeddings: When are they worth it? (ACL 2020)
Contextual embeddings have revolutionized NLP, but are highly computationally expensive. In this work we focus on the question of when contextual embeddings are worth their cost, versus when it is possible to use more efficient word representations without…