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10/06/2022
To Softmax, or not to Softmax: that is the question when applying Active Learning for Transformer Models
Despite achieving state-of-the-art results in nearly all Natural Languag...
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08/24/2022
ImitAL: Learned Active Learning Strategy on Synthetic Data
Active Learning (AL) is a well-known standard method for efficiently obt...
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08/17/2021
ImitAL: Learning Active Learning Strategies from Synthetic Data
One of the biggest challenges that complicates applied supervised machin...
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05/31/2021
Accurate and Efficient Time Series Matching by Season- and Trend-aware Symbolic Approximation – Extended Version Including Additional Evaluation and Proofs
Processing and analyzing time series datasets have become a central iss...
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05/19/2020
Machine Learning-based Cardinality Estimation in DBMS on Pre-Aggregated Data
Cardinality estimation is a fundamental task in database query processin...
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04/20/2020
MorphStore: Analytical Query Engine with a Holistic Compression-Enabled Processing Model
In this paper, we present MorphStore, an open-source in-memory columnar ...
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11/28/2019
RETRO: Relation Retrofitting For In-Database Machine Learning on Textual Data
There are massive amounts of textual data residing in databases, valuabl...
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05/23/2019
Conjunctive Queries with Theta Joins Under Updates
Modern application domains such as Composite Event Recognition (CER) and...
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05/16/2019
Persistent Buffer Management with Optimistic Consistency
Finding the best way to leverage non-volatile memory (NVM) on modern dat...
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06/11/2018
A Cost-based Storage Format Selector for Materialization in Big Data Frameworks
Modern big data frameworks (such as Hadoop and Spark) allow multiple use...
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06/13/2017