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Marius Gassen; Benjamin Hättasch; Benjamin Hilprecht; Nadja Geisler; Alexander Fraser; Carsten Binnig

Demonstrating CAT: Synthesizing Data-Aware Conversational Agents for Transactional Databases

In: Proceedings of the VLDB Endowment (PVLDB), Vol. 15, No. 12, Pages 3586-3589, Association for Computing Machinery (ACM), 2022.
Benjamin Hilprecht; Carsten Binnig

Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction

In: Proceedings of the VLDB Endowment (PVLDB), Vol. 15, No. 11, Pages 2361-2374, Association for Computing Machinery (ACM), 2022.
Benjamin Hilprecht; Carsten Binnig

One Model to Rule them All: Towards Zero-Shot Learning for Databases

In: 12th Conference on Innovative Data Systems Research, CIDR 2022. Conference on Innovative Data Systems Research (CIDR-2022), January 9-12, …
Nijat Mehdiyev; Lea Götz; Johannes Lahann; Peter Fettke

Deep learning-based clustering of processes and their visual exploration: An industry 4.0 use case for small, medium‐sized enterprises

In: Expert Systems (EXSY), Vol. 39, Pages 1-24, Wiley, 2022.
Martin Mundt; Steven Lang; Quentin Delfosse; Kristian Kersting

CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability

In: The Tenth International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2022), April 25-29, …
Felix Friedrich; Patrick Schramowski; Christopher Tauchmann; Kristian Kersting

Interactively Providing Explanations for Transformer Language Models

In: Stefan Schlobach; María Pérez-Ortiz; Myrthe Tielman (Hrsg.). HHAI 2022: Augmenting Human Intellect - Proceedings of the First International …
Patrick Schramowski; Christopher Tauchmann; Kristian Kersting

Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?

In: FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and …
Lukas Struppek; Dominik Hintersdorf; Daniel Neider; Kristian Kersting

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

In: FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and Transparency (ACM …
Wolfgang Stammer; Marius Memmel; Patrick Schramowski; Kristian Kersting

Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations

In: IEEE/CVF Conference on Computer Vision and Pattern Recognition. International Conference on Computer Vision and Pattern Recognition (CVPR-2022), …
Mei Ling Fang; Devendra Singh Dhami; Kristian Kersting

DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs

In: Martin Michalowski; Syed Sibte Raza Abidi; Samina Abidi (Hrsg.). Artificial Intelligence in Medicine - 20th International Conference on Artificial …

Publikationen

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Aktive Filter:

Demonstrating CAT: Synthesizing Data-Aware Conversational Agents for Transactional Databases

Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction

One Model to Rule them All: Towards Zero-Shot Learning for Databases

Deep learning-based clustering of processes and their visual exploration: An industry 4.0 use case for small, medium‐sized enterprises

CLEVA-Compass: A Continual Learning Evaluation Assessment Compass to Promote Research Transparency and Comparability

Interactively Providing Explanations for Transformer Language Models

Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations

DP-CTGAN: Differentially Private Medical Data Generation Using CTGANs

Jahr