Sparse tensors are prevalent in many data-intensive applications, yet
ex...
Automatic differentiation (AD) is a technique for computing the derivati...
Reverse-mode differentiation is used for optimization, but it introduces...
Tensor algebra is essential for data-intensive workloads in various
comp...
Tensor programs often need to process large tensors (vectors, matrices, ...
This article introduces hinted dictionaries for expressing efficient ord...
We introduce a framework for automatically choosing data structures to
s...
This paper introduces semi-ring dictionaries, a powerful class of
compos...
Cardinality estimation is one of the fundamental problems in database
ma...
While large-scale distributed data processing platforms have become an
a...
We consider the problem of training machine learning models over
multi-r...
In this paper, we present a framework to generate compilers for embedded...
There is a trend towards increased specialization of data management sof...
We present a system for the automatic differentiation of a higher-order
...