Thomas Schneider | DeepAI

DeepAI AI Chat

Featured Co-authors

Roland Siegwart
172 publications
Kristian Kersting
114 publications
Kamalika Chaudhuri
74 publications
Cesar Cadena
66 publications
Juan Nieto
60 publications
Farinaz Koushanfar
55 publications
Nicholas Evans
50 publications
Carsten Lutz
41 publications
N. Asokan
41 publications
Ahmad-Reza Sadeghi
40 publications
Massimiliano Todisco
39 publications

∙ 08/18/2023

Attesting Distributional Properties of Training Data for Machine Learning

The success of machine learning (ML) has been accompanied by increased c...

0 Vasisht Duddu, et al. ∙

∙ 06/01/2023

ExTRUST: Reducing Exploit Stockpiles with a Privacy-Preserving Depletion System for Inter-State Relationships

Cyberspace is a fragile construct threatened by malicious cyber operatio...

0 Thomas Reinhold, et al. ∙

∙ 04/21/2022

SPIKE: Secure and Private Investigation of the Kidney Exchange problem

Background: The kidney exchange problem (KEP) addresses the matching of ...

0 Timm Birka, et al. ∙

∙ 06/08/2021

LaserShark: Establishing Fast, Bidirectional Communication into Air-Gapped Systems

Physical isolation, so called air-gapping, is an effective method for pr...

0 Niclas Kühnapfel, et al. ∙

∙ 01/06/2021

FLGUARD: Secure and Private Federated Learning

Recently, a number of backdoor attacks against Federated Learning (FL) h...

0 Thien Duc Nguyen, et al. ∙

∙ 11/19/2020

Conservative Extensions in Horn Description Logics with Inverse Roles

We investigate the decidability and computational complexity of conserva...

0 Jean Christoph Jung, et al. ∙

∙ 08/10/2020

Trustworthy AI Inference Systems: An Industry Research View

In this work, we provide an industry research view for approaching the d...

37 Rosario Cammarota, et al. ∙

∙ 07/05/2020

Offline Model Guard: Secure and Private ML on Mobile Devices

Performing machine learning tasks in mobile applications yields a challe...

0 Sebastian P. Bayerl, et al. ∙

∙ 02/03/2020

CryptoSPN: Privacy-preserving Sum-Product Network Inference

AI algorithms, and machine learning (ML) techniques in particular, are i...

4 Amos Treiber, et al. ∙

∙ 07/08/2019

Privacy-Preserving Speaker Recognition with Cohort Score Normalisation

In many voice biometrics applications there is a requirement to preserve...

0 Andreas Nautsch, et al. ∙

∙ 06/11/2019

A Comment on Privacy-Preserving Scalar Product Protocols as proposed in "SPOC"

Privacy-preserving scalar product (PPSP) protocols are an important buil...

0 Thomas Schneider, et al. ∙

∙ 04/01/2019

Experimental Comparison of Visual-Aided Odometry Methods for Rail Vehicles

Today, rail vehicle localization is based on infrastructure-side Balises...

0 Florian Tschopp, et al. ∙

∙ 01/22/2019

Observability-aware Self-Calibration of Visual and Inertial Sensors for Ego-Motion Estimation

External effects such as shocks and temperature variations affect the ca...

0 Thomas Schneider, et al. ∙

∙ 07/12/2018

Faster than Nyquist Transmission by Non-Orthogonal Time Division Multiplexing of Nyquist Sinc Sequences

One possibility to break down the capacity limit in optical transmission...

0 Ali Dorostkar, et al. ∙

∙ 05/28/2018

Long-term Large-scale Mapping and Localization Using maplab

This paper discusses a large-scale and long-term mapping and localizatio...

0 Marcin Dymczyk, et al. ∙

∙ 03/26/2018

Visual-Inertial Teach and Repeat for Aerial Inspection

Industrial facilities often require periodic visual inspections of key i...

0 Marius Fehr, et al. ∙

∙ 01/10/2018

Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications

We present Chameleon, a novel hybrid (mixed-protocol) framework for secu...

0 M. Sadegh Riazi, et al. ∙

∙ 11/28/2017

maplab: An Open Framework for Research in Visual-inertial Mapping and Localization

Robust and accurate visual-inertial estimation is crucial to many of tod...

0 Thomas Schneider, et al. ∙

∙ 05/31/2013

Algebraic Properties of Qualitative Spatio-Temporal Calculi

Qualitative spatial and temporal reasoning is based on so-called qualita...

0 Frank Dylla, et al. ∙

∙ 07/06/2012

Syntactic vs. Semantic Locality: How Good Is a Cheap Approximation?

Extracting a subset of a given OWL ontology that captures all the ontolo...

0 Chiara Del Vescovo, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world