Co-Chair: Human Centered AI: Trustworthiness of AI Models and Data, AAAI 2019 Fall Symposium Series in Arlington, VA, USA, November 7–9, 2019
Join and discuss with us #HumanCenteredAI at the #AAAI 2019 #FallSymposiumSeries in Arlington, VA, #USA, November 7–9, 2019 – agenda is set and registration is now open: https://bit.ly/2nveduf #HumanCentered #AI: #Trustworthiness of AI #Models and #Data To facilitate the widespread…
NAACL-HLT 2019: News Article Teaser Tweets and How to Generate Them, Minneapolis, USA, June 2nd, 2019
Abstract: We define the task of teaser generation and provide an evaluation benchmark and baseline systems for it. A teaser is a short reading suggestion for an article that is illustrative and includes curiosity-arousing elements to entice potential readers to…
Talk: Trends in Machine Learning Research, CKI Conference Data Analytics and Artificial Intelligence, Technical University Munich (TUM), Munich, Germany, February 26th, 2018
Passion for Deep Learning Research: TUM University and Siemens – indeed a great match! Delighted to share some trends, collaborations and impact of Artificial Intelligence and Deep Learning Research at the TU Munich CKI Conference on „Data Analytics and Artificial…
Siemens AI Lab – Munich’s new idea lab on Artificial Intelligence – 09. December 2017
Siemens AI Lab – Munich’s new idea lab on Industrial Artificial Intelligence – a collaborative interdisciplinary platform for industrial research and exploration in Artificial Intelligence. The Siemens AI Lab is meant for the accelerated implementation of innovative ideas. We want to…
MOOC: Industrial Artificial Intelligence at Siemens – from the impact of Deep Learning, the creation of Conversational AI, to AI-centric API ecosystem
Awesome – finishing the MOOC on Artificial Intelligence at Siemens – from the impact of Deep Learning, the creation of Conversational AIs, to the acceleration via an AI-centric API ecosystem. Proud to push the Siemens AI Lab further – accelerating…
End-to-End Trainable Attentive Decoder for Hierarchical Entity Classification
Abstract: We address fine-grained entity classification and propose a novel attention-based recurrent neural network (RNN) encoderdecoder that generates paths in the type hierarchy and can be trained end-to-end. We show that our model performs better on fine-grained entity classification than…
AI & Machine Learning Research with Meaningful Impact
I am curious about the foundations of computational intelligence, specifically methodologies that bridge the areas of connectionist and symbolic learning applied to real-world AI, Machine Learning and NLP applications. I am passioned about enabling an open and interdisciplinary research and…
LinkedHealthAnswers: Towards Linked Data-driven Question Answering for the Health Care Domain
Abstract: This paper presents Linked Health Answers, a natural language question answering systems that utilizes health data drawn from the Linked Data Cloud. The contributions of this paper are three-fold: Firstly, we review existing state-of-the-art NLP platforms and components, with a special…
USI Answers: Natural Language Question Answering Over (Semi-) Structured Industry Data
Abstract: The paper reports on the progress towards the goal of offering easy access to enterprise data to a large number of business users, most of whom are not familiar with the specific syntax or semantics of the underlying data…
Connecting Question Answering and Conversational Agents: Contextualizing German Questions for Interactive Question Answering Systems
Abstract: Research results in the field of Question Answering (QA) have shown that the classification of natural language questions significantly contributes to the accuracy of the generated answers. In this paper we present an approach which extends the prevalent question…
