Tommy S. Alstrøm

Orcid: 0000-0003-0941-3146

According to our database1, Tommy S. Alstrøm authored at least 25 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity.
Trans. Mach. Learn. Res., 2024

Investigating the Design Space of Diffusion Models for Speech Enhancement.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

The Effect of Training Dataset Size on Discriminative and Diffusion-Based Speech Enhancement Systems.
IEEE Signal Process. Lett., 2024

Explaining time series models using frequency masking.
CoRR, 2024

An improved analysis of per-sample and per-update clipping in federated learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Diffusion-Based Speech Enhancement in Matched and Mismatched Conditions Using a Heun-Based Sampler.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Assessing the Generalization Gap of Learning-Based Speech Enhancement Systems in Noisy and Reverberant Environments.
IEEE ACM Trans. Audio Speech Lang. Process., 2023

On convex conceptual regions in deep network representations.
CoRR, 2023

Amortized Variational Peak Fitting For Spectroscopic Data.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Multi-View Self-Supervised Learning For Multivariate Variable-Channel Time Series.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

On Batching Variable Size Inputs for Training End-to-End Speech Enhancement Systems.
Proceedings of the IEEE International Conference on Acoustics, 2023

On the Effectiveness of Partial Variance Reduction in Federated Learning with Heterogeneous Data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Partial Variance Reduction improves Non-Convex Federated learning on heterogeneous data.
CoRR, 2022

Raman Spectrum Matching with Contrastive Representation Learning.
CoRR, 2022

2021
Road Roughness Estimation Using Machine Learning.
CoRR, 2021

2020
On uncertainty estimation in active learning for image segmentation.
CoRR, 2020

2019
A Bayesian Generative Model With Gaussian Process Priors For Thermomechanical Analysis Of Micro-Resonators.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Insights Into The Behaviour Of Multi-Task Deep Neural Networks For Medical Image Segmentation.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Peak Detection and Baseline Correction Using a Convolutional Neural Network.
Proceedings of the IEEE International Conference on Acoustics, 2019

2017
A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Click chemistry based biomolecular conjugation monitoring using surface-enhanced Raman spectroscopy mapping.
Proceedings of the 2016 IEEE SENSORS, Orlando, FL, USA, October 30 - November 3, 2016, 2016

2014
Improving the robustness of Surface Enhanced Raman Spectroscopy based sensors by Bayesian Non-negative Matrix Factorization.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

2012
Haussdorff and hellinger for colorimetric sensor array classification.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Feature extraction using distribution representation for colorimetric sensor arrays used as explosives detectors.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Data representation and feature selection for colorimetric sensor arrays used as explosives detectors.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011


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