7 citations · 16 across the 13 of their papers we have counts for
15 papers
Advantage of Entangled Learning Rules in Quantum Measurement Class Learning
Arka Prabha Das, Abram Magner
Learning with data in the form of quantum states is of current interest and has led to a variety of problems that boil down to interaction with the available data via quantum measu…
Multi-Dictionary Learning for Low Rank Sparse Coding
Boya Ma, Abram Magner, Maxwell McNeil +1
Sparse dictionary coding represents signals as linear combinations of a few dictionary atoms. It has been applied to images, time series, graph signals and multi-way spatio-tempora…
Continuous Symmetry Discovery and Enforcement Using Infinitesimal Generators of Multi-parameter Group Actions
Ben Shaw, Sasidhar Kunapuli, Abram Magner +1
Symmetry-informed machine learning can exhibit advantages over machine learning which fails to account for symmetry. In the context of continuous symmetry detection, current state…
Low Rank Multi-Dictionary Selection at Scale
Boya Ma, Maxwell McNeil, Abram Magner +1
The sparse dictionary coding framework represents signals as a linear combination of a few predefined dictionary atoms. It has been employed for images, time series, graph signals…
Symmetry Discovery Beyond Affine Transformations
Ben Shaw, Abram Magner, Kevin R. Moon
Symmetry detection can improve various machine learning tasks. In the context of continuous symmetry detection, current state of the art experiments are limited to detecting affine…
Fat Shattering, Joint Measurability, and PAC Learnability of POVM Hypothesis Classes
Abram Magner, Arun Padakandla
We characterize learnability for quantum measurement classes by establishing matching necessary and sufficient conditions for their PAC learnability, along with corresponding sampl…