May 21, 2024, 4:44 a.m. | Fabio Bonassi, Carl Andersson, Per Mattsson, Thomas B. Sch\"on

cs.LG updates on arXiv.org arxiv.org

arXiv:2312.06211v2 Announce Type: replace-cross
Abstract: The goal of this paper is to provide a system identification-friendly introduction to the Structured State-space Models (SSMs). These models have become recently popular in the machine learning community since, owing to their parallelizability, they can be efficiently and scalably trained to tackle extremely-long sequence classification and regression problems. Interestingly, SSMs appear as an effective way to learn deep Wiener models, which allows to reframe SSMs as an extension of a model class commonly used …

abstract arxiv become classification community cs.lg cs.sy eess.sy identification introduction machine machine learning paper popular regression replace space ssms state type

Senior Data Engineer

@ Displate | Warsaw

Principal Architect

@ eSimplicity | Silver Spring, MD, US

Embedded Software Engineer

@ Carrier | CAN03: Carrier-Charlotte, NC 9701 Old Statesville Road, Charlotte, NC, 28269 USA

(USA) Software Engineer III

@ Roswell Park Comprehensive Cancer Center | (USA) CA SUNNYVALE Home Office SUNNYVALE III - 840 W CALIFORNIA

Experienced Manufacturing and Automation Engineer

@ Boeing | DEU - Munich, Germany

Software Engineering-Sr Engineer (Java 17, Python, Microservices, Spring Boot, REST)

@ FICO | Bengaluru, India