Efficient large-scale neural network training and inference on commodity...
More than 70
of these idle compute are cheap CPUs with few cores that ar...
Neural models have transformed the fundamental information retrieval pro...
Softmax classifiers with a very large number of classes naturally occur ...
Dense embedding models are commonly deployed in commercial search engine...
In the last decade, it has been shown that many hard AI tasks, especiall...
Approximate set membership is a common problem with wide applications in...
Zero-Shot Learning (ZSL) is a classification task where we do not have e...
Deep Learning (DL) algorithms are the central focus of modern machine
le...
We present Merged-Averaged Classifiers via Hashing (MACH) for
K-classifi...