Olga Saukh

Olga Saukh

Technische Universität Graz

H-index: 23

Europe-Austria

About Olga Saukh

Olga Saukh, With an exceptional h-index of 23 and a recent h-index of 15 (since 2020), a distinguished researcher at Technische Universität Graz, specializes in the field of embedded intelligence, machine learning, deep learning, embedded systems, sensing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Datacomp: In search of the next generation of multimodal datasets

Poster: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints on IoT Devices

Mitigating Distribution Shifts in Pollen Classification from Microscopic Images Using Geometric Data Augmentations

Message from Program Chairs and the Steering Committee Chair

REDS: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints

Representing Input Transformations by Low-Dimensional Parameter Subspaces

Subspace-Configurable Networks

The role of pre-training data in transfer learning

Olga Saukh Information

University

Position

/ CSH Vienna

Citations(all)

3367

Citations(since 2020)

1552

Cited By

2465

hIndex(all)

23

hIndex(since 2020)

15

i10Index(all)

39

i10Index(since 2020)

21

Email

University Profile Page

Technische Universität Graz

Google Scholar

View Google Scholar Profile

Olga Saukh Skills & Research Interests

embedded intelligence

machine learning

deep learning

embedded systems

sensing

Top articles of Olga Saukh

Title

Journal

Author(s)

Publication Date

Datacomp: In search of the next generation of multimodal datasets

Advances in Neural Information Processing Systems

Samir Yitzhak Gadre

Gabriel Ilharco

Alex Fang

Jonathan Hayase

Georgios Smyrnis

...

2024/2/13

Poster: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints on IoT Devices

Francesco Corti

Balz Maag

Christopher Hinterer

Julian Rudolf

Joachim Schauer

...

2023/7/7

Mitigating Distribution Shifts in Pollen Classification from Microscopic Images Using Geometric Data Augmentations

Nam Cao

Olga Saukh

2023/12/17

Message from Program Chairs and the Steering Committee Chair

Salil Kanhere

Simone Silvestri

Olga Saukh

Sotiris Nikoletseas

2023/6/19

REDS: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints

arXiv preprint arXiv:2311.13349

Francesco Corti

Balz Maag

Joachim Schauer

Ulrich Pferschy

Olga Saukh

2023/11/22

Representing Input Transformations by Low-Dimensional Parameter Subspaces

arXiv preprint arXiv:2305.13536

Olga Saukh

Dong Wang

Xiaoxi He

Lothar Thiele

2023/5/22

Subspace-Configurable Networks

Olga Saukh

Dong Wang

Xiaoxi He

Lothar Thiele

2023/11/21

The role of pre-training data in transfer learning

arXiv preprint arXiv:2302.13602

Rahim Entezari

Mitchell Wortsman

Olga Saukh

M Moein Shariatnia

Hanie Sedghi

...

2023/2/27

Geometric Data Augmentations to Mitigate Distribution Shifts in Pollen Classification from Microscopic Images

arXiv preprint arXiv:2311.11029

Nam Cao

Olga Saukh

2023/11/18

Escaping Adversarial Attacks with Egyptian Mirrors

Olga Saukh

2023

Automatic Parameter Exploration for Low-Power Wireless Protocols

Mohamed Hassaan Mohamed Hydher

Markus Schuß

Olga Saukh

Carlo Alberto Boano

Kay Uwe Römer

2023/7/7

To share or not to share: On location privacy in IoT sensor data

Franz Papst

Naomi Stricker

Rahim Entezari

Olga Saukh

2022/5/4

Deep neural network pruning for nuclei instance segmentation in hematoxylin and eosin-stained histological images

Amirreza Mahbod

Rahim Entezari

Isabella Ellinger

Olga Saukh

2022/9/18

Challenges of integration and validation of farm and sensor data for dairy herd management

Katharina Schodl

Birgit Fuerst-Waltl

Hermann Schwarzenbacher

Franz Steininger

Marlene Suntinger

...

2022

How well do contrastively trained models transfer?

M Moein Shariatnia

Rahim Entezari

Mitchell Wortsman

Olga Saukh

Ludwig Schmidt

2022/7/23

Studying the impact of magnitude pruning on contrastive learning methods

arXiv preprint arXiv:2207.00200

Francesco Corti

Rahim Entezari

Sara Hooker

Davide Bacciu

Olga Saukh

2022/7/1

Understanding the effect of sparsity on neural networks robustness

arXiv preprint arXiv:2206.10915

Lukas Timpl

Rahim Entezari

Hanie Sedghi

Behnam Neyshabur

Olga Saukh

2022/6/22

SensorFormer: Efficient many-to-many sensor calibration with learnable input subsampling

IEEE Internet of Things Journal

Yun Cheng

Olga Saukh

Lothar Thiele

2022/5/25

Repair: Renormalizing permuted activations for interpolation repair

arXiv preprint arXiv:2211.08403

Keller Jordan

Hanie Sedghi

Olga Saukh

Rahim Entezari

Behnam Neyshabur

2022/11/15

Towards on-demand gas sensing

Markus-Philipp Gherman

Yun Cheng

Andres Gomez

Olga Saukh

2021/7/14

See List of Professors in Olga Saukh University(Technische Universität Graz)

Co-Authors

H-index: 67
Boi Faltings

Boi Faltings

École Polytechnique Fédérale de Lausanne

H-index: 65
Kurt Rothermel

Kurt Rothermel

Universität Stuttgart

H-index: 54
Kay Römer

Kay Römer

Technische Universität Graz

H-index: 46
Zimu Zhou

Zimu Zhou

Singapore Management University

H-index: 44
Jan Beutel

Jan Beutel

Universität Innsbruck

H-index: 32
Pedro Jose Marron

Pedro Jose Marron

Universität Duisburg-Essen

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