Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Davidson, Susan B."'
In data exploration, executing complex non-aggregate queries over large databases can be time-consuming. Our paper introduces a novel approach to address this challenge, focusing on finding an optimized subset of data, referred to as the approximatio
Externí odkaz:
http://arxiv.org/abs/2401.17059
We present a framework for creating small, informative sub-tables of large data tables to facilitate the first step of data science: data exploration. Given a large data table table T, the goal is to create a sub-table of small, fixed dimensions, by
Externí odkaz:
http://arxiv.org/abs/2203.02754
High-quality labels are expensive to obtain for many machine learning tasks, such as medical image classification tasks. Therefore, probabilistic (weak) labels produced by weak supervision tools are used to seed a process in which influential samples
Externí odkaz:
http://arxiv.org/abs/2107.08588
Publikováno v:
published in ICML 2020
Machine learning models are not static and may need to be retrained on slightly changed datasets, for instance, with the addition or deletion of a set of data points. This has many applications, including privacy, robustness, bias reduction, and unce
Externí odkaz:
http://arxiv.org/abs/2006.14755
The ubiquitous use of machine learning algorithms brings new challenges to traditional database problems such as incremental view update. Much effort is being put in better understanding and debugging machine learning models, as well as in identifyin
Externí odkaz:
http://arxiv.org/abs/2002.11791
Publikováno v:
In Information Systems November 2022 109
This paper proposes a novel approach for efficiently evaluating regular path queries over provenance graphs of workflows that may include recursion. The approach assumes that an execution g of a workflow G is labeled with query-agnostic reachability
Externí odkaz:
http://arxiv.org/abs/1408.0528
We study the problem of searching a repository of complex hierarchical workflows whose component modules, both composite and atomic, have been annotated with keywords. Since keyword search does not use the graph structure of a workflow, we develop a
Externí odkaz:
http://arxiv.org/abs/1305.4195
We study the problem of concealing functionality of a proprietary or private module when provenance information is shown over repeated executions of a workflow which contains both `public' and `private' modules. Our approach is to use `provenance vie
Externí odkaz:
http://arxiv.org/abs/1212.2251
Publikováno v:
Proceedings of the VLDB Endowment (PVLDB), Vol. 5, No. 11, pp. 1208-1219 (2012)
This paper considers the problem of efficiently answering reachability queries over views of provenance graphs, derived from executions of workflows that may include recursion. Such views include composite modules and model fine-grained dependencies
Externí odkaz:
http://arxiv.org/abs/1208.0083