Donnerstag, 22. Juni 2017
Montag, 19. Juni 2017
[HIForum] [Kolloquium] REMINDER: Informatics Colloquium Mo 19 June 2017, 17:15, B-201 "Adaptive Language Technologies" by Prof. Chris Biemann - Inaugural Lecture
Dear all,
May we kindly remind you of the today's inaugural lecture with Prof. Chris Biemann at 17:15 in room B-201. Please find the details below.
Best regards
On behalf of the colloquium committee
Stephanie Schulte Hemming
Universität Hamburg
Von: Fbi-alle <fbi-alle-bounces@mailhost.informatik.uni-hamburg.de> im Auftrag von "Schulte Hemming, Stephanie" <schulte@informatik.uni-hamburg.de>
Datum: Dienstag, 6. Juni 2017 um 11:27
An: "kolloquium@informatik.uni-hamburg.de" <kolloquium@informatik.uni-hamburg.de>
Betreff: [Fbi-alle] [Kolloquium] INVITATION: Informatics Colloquium Mo 19 June 2017, 17:15, B-201 "Adaptive Language Technologies" by Prof. Chris Biemann - Inaugural Lecture
This is an invitation to the next Informatics Colloquium on Monday, 19 June 2017, 17:15 s.t., Campus "Informatikum/Stellingen", Room B-201 (Konrad-Zuse lecture hall). The talk entitled "Adaptive Language Technologies" will be held by Prof. Dr. Chris Biemann, since October 2016 Professor for language technology at Universität Hamburg, department of informatics.
This inaugural lecture will be held in English. The colloquium committee is looking forward to seeing you all there and to sharing this talk with you. For details on the series of colloquiums planned, please visit https://www.inf.uni-hamburg.de/home/kolloquium/sose17.html
On behalf of the colloquium committee
Stephanie Schulte Hemming
Universität Hamburg
ABSTRACT:
Automatic natural language understanding enables natural communication with computers and computer-assisted access to the content of large document collections. While classical approaches to artificial intelligence anticipate all possible situations and interactions in form of a fully specified dialogue model or ontology, they are hard to adapt to new domains and do not cope well with language change. In this talk, I will motivate an adaptive, purely data-driven approach to natural language processing. Illustrated by recent research prototypes, three stages of data-driven adaptation will be illustrated: feature/resource induction, induction of processing components and continuous data-driven learning. Finally, I will discuss current research and future directions regarding the integration of symbolic and statistical knowledge, interpretability of language processing components as well as advanced forms of information access.
BIO:
Chris Biemann obtained his doctorate in Computer Science / Natural Language Processing in 2007 from the University of Leipzig, before joining the San-Francisco-based semantic search startup Powerset, which was acquired by Microsoft to form the Bing.com search engine. In 2011, he got appointed as assistant professor for language technology in the computer science department at TU Darmstadt; since October 2016, Chris is professor for language technology at the University of Hamburg. His current research is focused on adaptive natural language processing in the cognitive computing paradigm, web-scale statistical semantic methods, machine learning from crowdsourcing signals and on applications in the humanities and social sciences.
CONTACT:
Prof. Dr. Tilo Böhmann, ITMC
Dienstag, 6. Juni 2017
[HIForum] [Kolloquium] INVITATION: Informatics Colloquium Mo 19 June 2017, 17:15, B-201 "Adaptive Language Technologies" by Prof. Chris Biemann - Inaugural Lecture
This is an invitation to the next Informatics Colloquium on Monday, 19 June 2017, 17:15 s.t., Campus "Informatikum/Stellingen", Room B-201 (Konrad-Zuse lecture hall). The talk entitled "Adaptive Language Technologies" will be held by Prof. Dr. Chris Biemann, since October 2016 Professor for language technology at Universität Hamburg, department of informatics.
This inaugural lecture will be held in English. The colloquium committee is looking forward to seeing you all there and to sharing this talk with you. For details on the series of colloquiums planned, please visit https://www.inf.uni-hamburg.de/home/kolloquium/sose17.html
On behalf of the colloquium committee
Stephanie Schulte Hemming
Universität Hamburg
ABSTRACT:
Automatic natural language understanding enables natural communication with computers and computer-assisted access to the content of large document collections. While classical approaches to artificial intelligence anticipate all possible situations and interactions in form of a fully specified dialogue model or ontology, they are hard to adapt to new domains and do not cope well with language change. In this talk, I will motivate an adaptive, purely data-driven approach to natural language processing. Illustrated by recent research prototypes, three stages of data-driven adaptation will be illustrated: feature/resource induction, induction of processing components and continuous data-driven learning. Finally, I will discuss current research and future directions regarding the integration of symbolic and statistical knowledge, interpretability of language processing components as well as advanced forms of information access.
BIO:
Chris Biemann obtained his doctorate in Computer Science / Natural Language Processing in 2007 from the University of Leipzig, before joining the San-Francisco-based semantic search startup Powerset, which was acquired by Microsoft to form the Bing.com search engine. In 2011, he got appointed as assistant professor for language technology in the computer science department at TU Darmstadt; since October 2016, Chris is professor for language technology at the University of Hamburg. His current research is focused on adaptive natural language processing in the cognitive computing paradigm, web-scale statistical semantic methods, machine learning from crowdsourcing signals and on applications in the humanities and social sciences.
CONTACT:
Prof. Dr. Tilo Böhmann, ITMC
Montag, 29. Mai 2017
[HIForum] [Kolloquium] REMINDER: Informatics Colloquium Mo 29.05.17 at 17:15 in B-201 with Prof. Dr.-Ing. Kai Uwe Barthel/ HTW Berlin
Dear all,
May we kindly remind you of the today's talk at 17:15 in room B-201. Please find the details below.
Best regards
On behalf of the colloquium committee
Stephanie Schulte Hemming
Universität Hamburg
Von: Fbi-alle <fbi-alle-bounces@mailhost.informatik.uni-hamburg.de> im Auftrag von "Schulte Hemming, Stephanie" <schulte@informatik.uni-hamburg.de>
Datum: Dienstag, 16. Mai 2017 um 09:47
An: "kolloquium@informatik.uni-hamburg.de" <kolloquium@informatik.uni-hamburg.de>
Betreff: [Fbi-alle] [Kolloquium] INVITATION: Informatics Colloquium Mo 29.05.17 at 17:15 in B-201 with Prof. Dr.-Ing. Kai Uwe Barthel/ HTW Berlin
This is an invitation to the next Informatics Colloquium on Monday, 29 May 2017, 17:15, Campus "Informatikum/Stellingen", Room B-201 (Konrad-Zuse lecture hall). The talk entitled "Visually Browsing Millions of Images using Image Graphs" will be held by Prof. Dr.-Ing. Kai Uwe Barthel, Hochschule für Technik und Wirtschaft, HTW Berlin.
This talk will be held in English. The colloquium committee is looking forward to seeing you all there and to sharing this talk with you. For details on the series of colloquiums planned, please visit https://www.inf.uni-hamburg.de/home/kolloquium/sose17.html
On behalf of the colloquium committee
Stephanie Schulte Hemming
Universität Hamburg
ABSTRACT:
In the past an efficient and satisfactory image search was only possible by using a combation of keywords and low-level visual image features. Recently Convolutional Neural Networks (CNNs) have enabled automatic understanding of images. This results in a multitude of new applications and improved visual image search systems. This talk provides an overview of the different methods for image search, gives an overview of the principle of CNNs and shows how future image search systems could look like. We present a new approach to visually explore very large sets of untagged images. High quality image descriptors are generated using transformed activations of a convolutional neural network. These features are used to model image similarities, from which a hierarchical image graph is build. We show how such a graph can be constructed efficiently. Best user experience for navigating this graph is achieved by projecting sub-graphs onto a regular 2D-image map. This allows users to explore the image graph similar to navigation services.
BIO:
Prof. Dr. Kai Uwe Barthel studied Electrical Engineering at the Technical University of Berlin. At the university's department for image and signal processing he finished in 1996 his PhD thesis about fractal image compression. In 1998 he became head of R&D with LuraTech Inc. where hard- and software for image compression were developed. He also participated in the JPEG2000 standardization committee. His research topic of that time was the segmentation of documents for Mixed-Raster-Content compression. In 2001 he became a professor for visual computing at HTW Berlin, University of Applied Sciences. At HTW Berlin he is teaching courses such as image processing, computer vision, visual information retrieval, and machine learning. Main research topics are visual image search and automatic image understanding. In 2009 he founded pixolution, a company for visual image search. His latest research includes automatic keywording of images, image clustering and the development of visual image navigation systems such as www.picsbuffet.com
CONTACT:
Prof. Dr.-Ing. H.-Siegfried Stiehl, BV/HCC
Montag, 22. Mai 2017
[HIForum] [Kolloquium] REMINDER: Informatics Colloquium Mo 22 May 2017, 17:15, B-201 "Signal Processing for Speech Enhancement" by Prof. Dr. Timo Gerkmann
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May we kindly remind you of the today's inaugural lecture with Prof. Timo Gerkmann at 17:15 in room B-201. Please find the details below.
On behalf of the colloquium committee
Gesendet: Dienstag, 9. Mai 2017 09:10
An: kolloquium@informatik.uni-hamburg.de
Betreff: [Fbi-alle] [Kolloquium] INVITATION: Informatics Colloquium Mo 22 May 2017, 17:15, B-201 "Signal Processing for Speech Enhancement" by Prof. Dr. Timo Gerkmann
In the Signal Processing (SP) group, we focus on audio signal processing and in particular aim at making speech communication work more robustly in noisy and reverberant environments. To achieve this, we combine prior knowledge about the signal (e.g. speech), the environment (e.g. the room) and the sink (e.g. the human ear) with rigorous mathematical optimization procedures. In this talk, we will introduce the general concepts used for signal enhancement and highlight our recent contributions.
* 2015-2016: Principal Scientist Audio & Acoustics, Technicolor Research & Innovation
* 2011-2015: Juniorprofessor of Speech Signal Processing, Cluster of Excellence Hearing4all, Universität Oldenburg
* 2010-2011: Postdoctoral Researcher, Sound and Image Proc. Lab, KTH, Royal Institute of Technology, Stockholm
* 2005-2010: PhD Student, Institute of Communication Acoustics, Ruhr-Universität Bochum
* 2005: Siemens Corporate Research, Princeton, NJ, USA