21 citations · 125 across the 23 of their papers we have counts for
5 papers · 1 filter
AI Descartes: Combining Data and Theory for Derivable Scientific Discovery
Cristina Cornelio, Sanjeeb Dash, Vernon Austel +6
Scientists have long aimed to discover meaningful formulae which accurately describe experimental data. A common approach is to manually create mathematical models of natural pheno…
Quantum Topological Data Analysis with Linear Depth and Exponential Speedup
Shashanka Ubaru, Ismail Yunus Akhalwaya, Mark S. Squillante +2
Quantum computing offers the potential of exponential speedups for certain classical computations. Over the last decade, many quantum machine learning (QML) algorithms have been pr…
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time
Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham +1
In the numerical linear algebra community, it was suggested that to obtain nearly optimal bounds for various problems such as rank computation, finding a maximal linearly independe…
Sparse graph based sketching for fast numerical linear algebra
Dong Hu, Shashanka Ubaru, Alex Gittens +3
In recent years, a variety of randomized constructions of sketching matrices have been devised, that have been used in fast algorithms for numerical linear algebra problems, such a…
Order Embeddings from Merged Ontologies using Sketching
Kenneth L. Clarkson, Sanjana Sahayaraj
We give a simple, low resource method to produce order embeddings from ontologies. Such embeddings map words to vectors so that order relations on the words, such as hypernymy/hypo…