Categories
Allgemein

2020 Pattern Recognition Best Paper Award

Home >

2020 Pattern Recognition Best Paper Award

2020 Pattern Recognition Best Paper Award

A team of scientists from TU Berlin, Fraunhofer Heinrich Hertz Institute (HHI) and University of Oslo has jointly received the 2020 “Pattern Recognition Best Paper Award” and “Pattern Recognition Medal” of the international scientific journal Pattern Recognition. The award committee honored the publication “Explaining Nonlinear Classification Decisions with Deep Taylor Decomposition” by Dr. Grégoire Montavon and Prof. Dr. Klaus-Robert Müller from TU Berlin, Prof. Dr. Alexander Binder from University of Oslo, as well as Dr. Wojciech Samek and Dr. Sebastian Lapuschkin from HHI.

Dr. Grégoire Montavon with the 2020 Pattern Recognition Best Paper Award in hand.

The publication addresses the so-called black box problem. Machine Learning methods, in particular Deep Learning, successfully solve a variety of tasks. However, in most cases they fail to provide the information that has led to a particular decision. The paper tackles this problem by using a pixel-by-pixel decomposition of nonlinear classifications and evaluates the procedure in different scenarios. This method provides a theoretical framework for Explainable Artificial Intelligence (XAI) that is generally applicable. XAI is a major research field of the Berlin Institute for the Foundations of Learning and Data (BIFOLD), of which the authors from TU Berlin and HHI are members.

The award was presented to Grégoire Montavon in January 2021, during the virtual International Conference on Pattern Recognition (ICPR). The “Pattern Recognition Best Paper Award” is granted every two years. It recognizes a highly cited paper in the area of pattern recognition and its application areas such as image processing, computer vision and biometrics.

“We are very proud to receive this award and for our work to be highlighted within the global scientific community.”

Dr. Grégoire Montavon.

Categories
Allgemein

“Data is the new soil!” – Interview with Prof. Markl

Home >

“Data is the new soil!” – Interview with Prof. Markl

“Data is not the new oil, but the new soil!” – Newspaper Interview with Prof. Markl

In an interview with the German newspaper ‘Der Tagesspiegel,’ one of BIFOLD’s directors, Prof. Dr. Markl, explains the necessary steps to drive Europe forward in terms of data sovereignty and innovation ecosystems.

In an interview with Oliver Voss (Tagesspiegel), Prof. Dr. Volker Markl, Head of the DIMA (TUB) and IAM (DFKI) research groups and one of the directors of the BIFOLD institute, explains the challenges and opportunities in handling data as a production factor in Europe. How can we achieve AI leadership across Europe and how can we make progress in research, training and innovation in the areas of big data management and machine learning?

Data is not the new oil, but the new soil. Because just as new grain is created from the soil, new information can be gained from data. And just as I have to fertilize or water the soil, I also have to maintain, clean and update data. But above all, you can import raw materials, but you have to have a production factor in your own country, which is why sovereignty in this area is so important.

Prof. Dr. Volker Markl

Among many other points, Prof. Markl suggests to concentrate on excellence in research and education in European AI Centers such as BIFOLD and the other Institutions in the German Network of National Centers of Excellence for AI Research. The combination of strong research and education as well as an extensive data analysis infrastructure to share and process data across different domains may create the innovation ecosystem Europe needs to compete internationally.

Read the full interview in Tagesspiegel (in german).

Categories
Allgemein

2nd Place at the SIGMOD 2020 Student Research Competition

Home >

2nd Place at the SIGMOD 2020 Student Research Competition

TU Berlin Master’s student wins 2nd place at the SIGMOD 2020 Student Research Competition

TU Berlin’s student Hendrik Makait reached the 2nd place at the ACM SIGMOD 2020 Student Research Competition at the 2020 ACM SIGMOD/PODS International Conference on the Management of Data [1] with his paper “Rethinking Message Brokers on RDMA and NVM” [2]. This is a joint work with the Data Engineering Systems Group at the Hasso Plattner Institute in Potsdam led by Prof. Rabl [3].

Short abstract:

Over the last years, message brokers have become an important part of enterprise systems. As microservice architectures become more popular and the need to analyze data produced by the individual services grows, companies increasingly rely on message brokers to orchestrate the flow of events between different applications as well as between data-producing services and stream processing engines that analyze the data in real-time. Current state-of-the-art message brokers such as Apache Kafka or Apache Pulsar were designed for slow networks and disk-based storage. In this work, we propose a new architecture that leverages remote direct memory access (RDMA) and non-volatile memory (NVM) to improve the weaknesses of existing message brokers and further scale these systems.

[1] ACM SIGMOD 2020 Student Research Competition
[2] ACM Paper “Rethinking Message Brokers on RDMA and NVM”
[3] Data Engineering Systems Group HPI Prof. Dr. Tilmann Rabl