| Vol-3375 urn:nbn:de:0074-3375-8 Copyright © 2022 for the individual papers by the papers' authors. Copyright © 2022 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# AMLTS 2022
Applied Machine Learning Methods for Time Series Forecasting 2022

### Proceedings of the Workshop on Applied Machine Learning Methods for Time Series Forecasting (AMLTS 2022)
co-located with 31st ACM International Conference on Information and Knowledge Management (CIKM 2022)

### Atlanta, Georgia, USA, October 21, 2022.

Edited by

### Wei Liu *
Linsey Pang **

* University of Technology Sydney , Sydney, NSW, Australia
** Salesforce, San Francisco, California, USA

## Table of Contents

- Preface
  Summary: There were 18 papers submitted for peer-review to this workshop. Out of these, 8 papers were accepted for this volume, 5 as regular papers and 3 as short papers.

### Papers

- On the Inductive Bias Transfer with Knowledge Distillation for Real-World Data
  Byeong Tak Leei, Yong-Yeon Jo, Joon-myoung Kwon
- Event2Graph: Event-driven Bipartite Graph for Multivariate Time Series Forecasting and Anomaly Detection
  Yuhang Wu, Mengting Gu, Lan Wang, Yu-san Lin, Fei Wang, Hao Yang
- Multivariate Time Series-based Solar Flare Prediction by Functional Network Embedding and Sequence Modeling
  Shah Muhammad Hamdi, Abu Fuad Ahmad, Soukaina Filali Boubrahimi
- Forecasting Multivariate Time Series of the Magnetic Field Parameters of the Solar Events
  Khaznah Alshammari, Shah Muhammad Hamdi, Ali Ahsan Muhummad Muzaheed, Soukaina Filali Boubrahimi
- GreenEyes: An Air Quality Evaluating Model based on WaveNet
  Kan Huang, Kai Zhang, Ming Liu
- Real-time Anomaly Detection for Multivariate Data Streams
  Kenneth Odoh
- Machine Learning Methods for Equity Time Series Forecasting: A Compendium
  Alberto Matuozzo, Paul D. Yoo, Alessandro Provetti, Maria H. Kim
- Time Series Anomaly Detection in Smart Homes: A Deep Learning Approach
  Somayeh Zamani, Hamed Talebi, Gunnar Stevens

2023-04-15: submitted by Linsey Pang, metadata incl. bibliographic data published under Creative Commons CC0
2023-04-16: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|