SiG-DML-P3.1
CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision
Aoi Ito, Hosei University, Japan; Kota Dohi, Yohei Kawaguchi, Hitachi, Ltd., Japan
Session:
SiG-DML-P3: Sequential Learning & Time-Series Analysis Poster
Track:
SiG-DML - Signal and Data Analytics for Machine Learning
Location:
Poster Area D
Presentation Time:
Wed, 10 Sep, 11:00 - 12:40 Italy Time (UTC +2)
Session Co-Chairs:
Paraskevi Nousi, SDSC, ETH Zurich and Kota Dohi, Hitachi, Ltd.
Presentation
Discussion
Resources
No resources available.
Session SiG-DML-P3
SiG-DML-P3.1: CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision
Aoi Ito, Hosei University, Japan; Kota Dohi, Yohei Kawaguchi, Hitachi, Ltd., Japan
SiG-DML-P3.2: MISTI: Multi-Style Transfer for Multivariate Time Series
Henri HOYEZ, Paul Wurth S.A.; RPTU Kaiserslautern, Luxembourg; Bruno Mirbach, Jason Rambach, German Research Center for Artificial Intelligence (DFKI), Germany; Cédric Schockaert, Paul Wurth S.A., Luxembourg; Didier Stricker, RPTU Kaiserslautern, Germany
SiG-DML-P3.3: Improving Electric Load Demand Forecasting With Hard Representation Regularization
Paraskevi Nousi, SDSC, ETH Zurich, Switzerland; Maria Tzelepi, Information Technologies Institute (ITI), Greece
SiG-DML-P3.4: RETRIEVING TIME-SERIES DIFFERENCES USING NATURAL LANGUAGE QUERIES
Kota Dohi, Tomoya Nishida, Harsh Purohit, Takashi Endo, Yohei Kawaguchi, Hitachi, Ltd., Japan
SiG-DML-P3.5: ANOMALY DETECTION VIA RE-ENCODING IN AUTOENCODER-BASED COMPRESSION FOR TIME SERIES MONITORING APPLICATIONS
Andriy Enttsel, Aldo Sean Sartor, Alex Marchioni, University of Bologna, Italy; Gianluca Setti, KAUST, Saudi Arabia; Riccardo Rovatti, Mauro Mangia, University of Bologna, Italy
SiG-DML-P3.6: Water Demand Forecasting of District Metered Areas through Learned Consumer Representations
Adithya Ramachandran, Pattern Recognition Lab, Friedrich Alexander University - Erlangen, Germany; Thorkil Flensmark Neergaard, Brønderslev Forsyning, Denmark; Tomas Arias-Vergara, Andreas Maier, Siming Bayer, Pattern Recognition Lab, Friedrich Alexander University - Erlangen, Germany
SiG-DML-P3.7: Optimizing Feature Extraction from Sequential Sensor Data Using Neural Network-Based Image Transformation
Chang-Hyun Kim, Seung-Hwan Choi, Hyoeun Kwon, Korea Institute of Industrial Technology, Korea (South); Hiroaki Kawamoto, University of Tsukuba, Japan; Sanghun Choi, Kyungpook National University, Korea (South); Suwoong Lee, Korea Institute of Industrial Technology, Korea (South)
SiG-DML-P3.8: Improvement-Based Acquisition Functions for Level Set Estimation
Anand Ravishankar, Stony Brook University, United States; Fernando Llorente, Brookhaven National Laboratory, United States; Petar Djuric, Stony Brook University, United States