Florian Schmidt | DeepAI

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∙ 03/10/2022

Efficient Runtime Profiling for Black-box Machine Learning Services on Sensor Streams

In highly distributed environments such as cloud, edge and fog computing...

0 Soeren Becker, et al. ∙

∙ 09/27/2021

LOS: Local-Optimistic Scheduling of Periodic Model Training For Anomaly Detection on Sensor Data Streams in Meshed Edge Networks

Anomaly detection is increasingly important to handle the amount of sens...

0 Soeren Becker, et al. ∙

∙ 09/27/2021

EdgePier: P2P-based Container Image Distribution in Edge Computing Environments

Edge and fog computing architectures utilize container technologies in o...

0 Soeren Becker, et al. ∙

∙ 03/10/2021

Towards a Cognitive Compute Continuum: An Architecture for Ad-Hoc Self-Managed Swarms

In this paper we introduce our vision of a Cognitive Computing Continuum...

0 Ana Juan Ferrer, et al. ∙

∙ 02/12/2021

Towards AIOps in Edge Computing Environments

Edge computing was introduced as a technical enabler for the demanding r...

0 Soeren Becker, et al. ∙

∙ 01/25/2021

Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series

Forecasting of time series in continuous systems becomes an increasingly...

0 Kevin Styp-Rekowski, et al. ∙

∙ 01/15/2021

Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper

Artificial Intelligence for IT Operations (AIOps) is an emerging interdi...

0 Jasmin Bogatinovski, et al. ∙

∙ 12/17/2020

The voice of COVID-19: Acoustic correlates of infection

COVID-19 is a global health crisis that has been affecting many aspects ...

0 Katrin D. Bartl-Pokorny, et al. ∙

∙ 06/09/2020

Sensor Artificial Intelligence and its Application to Space Systems – A White Paper

Information and communication technologies have accompanied our everyday...

0 Anko Börner, et al. ∙

∙ 03/05/2020

BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward

Measuring the quality of a generated sequence against a set of reference...

0 Florian Schmidt, et al. ∙

∙ 10/01/2019

Generalization in Generation: A closer look at Exposure Bias

Exposure bias refers to the train-test discrepancy that seemingly arises...

0 Florian Schmidt, et al. ∙

∙ 08/30/2019

Autoregressive Text Generation Beyond Feedback Loops

Autoregressive state transitions, where predictions are conditioned on p...

0 Florian Schmidt, et al. ∙

∙ 04/01/2019

Application-Agnostic Offloading of Packet Processing

As network speed increases, servers struggle to serve all requests direc...

0 Oliver Hohlfeld, et al. ∙

∙ 10/12/2018

Grand Challenge: Real-time Destination and ETA Prediction for Maritime Traffic

In this paper, we present our approach for solving the DEBS Grand Challe...

0 Oleh Bodunov, et al. ∙

∙ 09/17/2018

On the Fly Orchestration of Unikernels: Tuning and Performance Evaluation of Virtual Infrastructure Managers

Network operators are facing significant challenges meeting the demand f...

0 Pier Luigi Ventre, et al. ∙

∙ 06/12/2018

Deep State Space Models for Unconditional Word Generation

Autoregressive feedback is considered a necessity for successful uncondi...

0 Florian Schmidt, et al. ∙

∙ 04/23/2018

BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism

Neural network frameworks such as PyTorch and TensorFlow are the workhor...

0 Nicolas Weber, et al. ∙

∙ 02/02/2018

Representation Learning for Resource Usage Prediction

Creating a model of a computer system that can be used for tasks such as...

0 Florian Schmidt, et al. ∙

∙ 12/01/2016

Neural Document Embeddings for Intensive Care Patient Mortality Prediction

We present an automatic mortality prediction scheme based on the unstruc...

0 Paulina Grnarova, et al. ∙

∙ 12/20/2013

Support for Error Tolerance in the Real-Time Transport Protocol

Streaming applications often tolerate bit errors in their received data ...

0 Florian Schmidt, et al. ∙