Learning Compressed Embeddings for On-Device Inference

no code implementations • 18 Mar 2022 • Niketan Pansare, Jay Katukuri, Aditya Arora, Frank Cipollone, Riyaaz Shaik, Noyan Tokgozoglu, Chandru Venkataraman

MEmCom outperforms the state-of-the-art techniques, which achieved 16%, 6%, 10%, and 8% relative loss in nDCG at the respective compression ratios.

Model Compression Recommendation Systems

Deep Learning with Apache SystemML

no code implementations • 8 Feb 2018 • Niketan Pansare, Michael Dusenberry, Nakul Jindal, Matthias Boehm, Berthold Reinwald, Prithviraj Sen

Enterprises operate large data lakes using Hadoop and Spark frameworks that (1) run a plethora of tools to automate powerful data preparation/transformation pipelines, (2) run on shared, large clusters to (3) perform many different analytics tasks ranging from model preparation, building, evaluation, and tuning for both machine learning and deep learning.

BIG-bench Machine Learning

Declarative Machine Learning - A Classification of Basic Properties and Types

no code implementations • 19 May 2016 • Matthias Boehm, Alexandre V. Evfimievski, Niketan Pansare, Berthold Reinwald

Specification alternatives range from ML algorithms expressed in domain-specific languages (DSLs) with optimization for performance, to ML task (learning problem) specifications with optimization for performance and accuracy.

BIG-bench Machine Learning Classification +1