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Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces
In extreme classification settings, embedding-based neural network models are currently not competitive with sparse linear and tree-based methods in terms of accuracy.
Multiscale Quantization for Fast Similarity Search
We propose a multiscale quantization approach for fast similarity search on large, high-dimensional datasets.
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