TY - GEN
T1 - An intermediate representation for hybrid database and machine learning workloads
AU - Shaikhha, Amir
AU - Schleich, Maximilian
AU - Olteanu, Dan
PY - 2021/7/1
Y1 - 2021/7/1
N2 - IFAQ is an intermediate representation and compilation framework for hybrid database and machine learning workloads expressible using iterative programs with functional aggregate queries. We demonstrate IFAQ for several OLAP queries, linear algebra expressions, and learning factorization machines over training datasets defined by feature extraction queries over relational databases.
AB - IFAQ is an intermediate representation and compilation framework for hybrid database and machine learning workloads expressible using iterative programs with functional aggregate queries. We demonstrate IFAQ for several OLAP queries, linear algebra expressions, and learning factorization machines over training datasets defined by feature extraction queries over relational databases.
UR - http://www.scopus.com/inward/record.url?scp=85119131022&partnerID=8YFLogxK
U2 - 10.14778/3476311.3476356
DO - 10.14778/3476311.3476356
M3 - Conference contribution
AN - SCOPUS:85119131022
VL - 14
T3 - Proceedings of the VLDB Endowment
SP - 2831
EP - 2834
BT - Proceedings of the VLDB Endowment
A2 - Dong, Xin Luna
A2 - Naumann, Felix
PB - ACM
T2 - 47th International Conference on Very Large Data Bases
Y2 - 16 August 2021 through 20 August 2021
ER -