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Found 5 papers, 0 papers with code
COMET: Convolutional Dimension Interaction for Collaborative Filtering
In this paper, we propose a novel representation learning-based model called COMET (COnvolutional diMEnsion inTeraction), which simultaneously models the high-order interaction patterns among historical interactions and embedding dimensions.
Improving Device Directedness Classification of Utterances with Semantic Lexical Features
User interactions with personal assistants like Alexa, Google Home and Siri are typically initiated by a wake term or wakeword.
Why do embedding spaces look as they do?
The power of embedding representations is a curious phenomenon.
Hierarchies over Vector Space: Orienting Word and Graph Embeddings
Word and graph embeddings are widely used in deep learning applications.
Provable Fairness for Neural Network Models using Formal Verification
Machine learning models are increasingly deployed for critical decision-making tasks, making it important to verify that they do not contain gender or racial biases picked up from training data.
