5 citations · 11 across the 8 of their papers we have counts for
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cs.LG2021
ImitAL: Learning Active Learning Strategies from Synthetic Data
Julius Gonsior, Maik Thiele, Wolfgang Lehner
One of the biggest challenges that complicates applied supervised machine learning is the need for huge amounts of labeled data. Active Learning (AL) is a well-known standard metho…
cs.DB2021
Accurate and Efficient Time Series Matching by Season- and Trend-aware Symbolic Approximation -- Extended Version Including Additional Evaluation and Proofs
Lars Kegel, Claudio Hartmann, Maik Thiele +1
Processing and analyzing time series data\-sets have become a central issue in many domains requiring data management systems to support time series as a native data type. A crucia…