Search Results for author: Aaqib Saeed

Found 11 papers, 2 papers with code

Federated Self-Training for Semi-Supervised Audio Recognition

no code implementations14 Jul 2021 Vasileios Tsouvalas, Aaqib Saeed, Tanir Ozcelebi

Notably, we show that with as little as 3% labeled data available, FedSTAR on average can improve the recognition rate by 13. 28% compared to the fully supervised federated model.

Audio Classification Federated Learning

ProcessTransformer: Predictive Business Process Monitoring with Transformer Network

1 code implementation1 Apr 2021 Zaharah A. Bukhsh, Aaqib Saeed, Remco M. Dijkman

Nevertheless, designing a deep neural architecture that performs competitively across various tasks is challenging as existing methods fail to capture long-range dependencies in the input sequences and perform poorly for lengthy process traces.

Damage detection using in-domain and cross-domain transfer learning

no code implementations7 Feb 2021 Zaharah A. Bukhsh, Nils Jansen, Aaqib Saeed

We, therefore, propose a combination of in-domain and cross-domain transfer learning strategies for damage detection in bridges.

Transfer Learning

Learning from Heterogeneous EEG Signals with Differentiable Channel Reordering

no code implementations21 Oct 2020 Aaqib Saeed, David Grangier, Olivier Pietquin, Neil Zeghidour

We propose CHARM, a method for training a single neural network across inconsistent input channels.


Contrastive Learning of General-Purpose Audio Representations

1 code implementation21 Oct 2020 Aaqib Saeed, David Grangier, Neil Zeghidour

We introduce COLA, a self-supervised pre-training approach for learning a general-purpose representation of audio.

Contrastive Learning

Sense and Learn: Self-Supervision for Omnipresent Sensors

no code implementations28 Sep 2020 Aaqib Saeed, Victor Ungureanu, Beat Gfeller

Likewise, the learned representations with self-supervision are found to be highly transferable between related datasets, even when few labeled instances are available from the target domains.

Continual Learning Few-Shot Learning +2

Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence

no code implementations25 Jul 2020 Aaqib Saeed, Flora D. Salim, Tanir Ozcelebi, Johan Lukkien

Federated learning provides a compelling framework for learning models from decentralized data, but conventionally, it assumes the availability of labeled samples, whereas on-device data are generally either unlabeled or cannot be annotated readily through user interaction.

Federated Learning Self-Supervised Learning +1

Multi-task Self-Supervised Learning for Human Activity Detection

no code implementations27 Jul 2019 Aaqib Saeed, Tanir Ozcelebi, Johan Lukkien

We learn a multi-task temporal convolutional network to recognize transformations applied on an input signal.

Action Detection Activity Detection +4

Learning behavioral context recognition with multi-stream temporal convolutional networks

no code implementations27 Aug 2018 Aaqib Saeed, Tanir Ozcelebi, Stojan Trajanovski, Johan Lukkien

In this paper, we propose a multi-stream temporal convolutional network to address the problem of multi-label behavioral context recognition.

Feature Engineering Multi-Task Learning

Personalized Driver Stress Detection with Multi-task Neural Networks using Physiological Signals

no code implementations15 Nov 2017 Aaqib Saeed, Stojan Trajanovski

Stress can be seen as a physiological response to everyday emotional, mental and physical challenges.

Multi-Task Learning

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