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2019/10/15
Our paper “DBMS Fitting: Why should we learn what we already know?” was accepted to CIDR 2020
In this paper, we propose an alternative approach to learn DBMS components.
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2019/07/01
Our paper “High-Performance In-Network Data Processing” was accepted for the Tenth International Workshop at ADMS 2019/VLDB 2019
As a first contribution of this paper, we propose a new switch architecture that can be employed as an in-network co-processor for analytical SQL workloads.
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2019/07/01
Best Student Paper Award for our paper “XAI – A Middleware for Scalable AI” which was accepted to Data 2019
Abdallah Salama received the Best Student Paper Award for his paper "XAI – A Middleware for Scalable AI" which runs on top of existing deep learning frameworks such as TensorFlow or MXNet and automates the hyper-parameter search for distributed deep
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2019/07/01
Our paper “BlockchainDB A – Shared Database on Blockchains” was accepted to VLDB 2019
We present BlockchainDB, which leverages blockchains as a storage layer and more..
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2019/07/01
Our paper “DBPal: Weak Supervision for Learning a Natural Language Interface to Databases” was accepted for the “Conversational Access to Data (CAST) Workshop” at VLDB 2019
A new system to translate natural language utterances into SQL statements using a neural machine translation model
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2019/06/12
Our paper “Model-based Approximate Query Processing” was accepted to AIDB workshop at VLDB 2019
New approach to Approximate Query Processing (AQP) called Model-based AQP
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2019/05/13
Our demo ProgressiveDB – Progressive Data Analytics as a Middleware was accepted to VLDB 2019
ProgressiveDB transforms any standard SQL database into a progressive database capable of continuous, approximate query processing.
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2019/04/24
Our paper about a Morsel-Driven Query Execution Engine for Heterogeneous Multi-Cores was accepted to VLDB 2019
A Morsel-Driven Query Execution Engine for Heterogeneous Multi-Cores
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2019/04/19
Our paper about interactive summarization was accepted to HILDA 2019
Interactive Summarization of Large Document Collections
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2019/04/15
Our paper about learned Database partitioning was accepted to aiDM 2019
Towards Learning a Partitioning Advisor with Deep Reinforcement Learning
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2019/03/22
Our paper about Interactive Curation of ML Pipelines was accepted to Sigmod 2019
Democratizing Data Science through Interactive Curation of ML Pipelines
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2019/03/22
Our FITing-Tree paper was accepted to Sigmod 2019
FITing-Tree: A Data-aware Index Structure
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2019/03/22
Our BlockchainDB demo was accepted to Sigmod 2019
BlockchainDB – Towards a Shared Database on Blockchains
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