Christos Louizos

According to our database, Christos Louizos authored at least 29 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning.

Babak Ehteshami Bejnordi, Gaurav Kumar, Amelie Royer, Christos Louizos, Tijmen Blankevoort, Mohsen Ghafoorian

CoRR, 2024

Importance Matching Lemma for Lossy Compression with Side Information.

Buu Phan, Ashish Khisti, Christos Louizos

CoRR, 2024

Protect Your Score: Contact-Tracing with Differential Privacy Guarantees.

Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Hyperparameter Optimization through Neural Network Partitioning.

Bruno Mlodozeniec, Matthias Reisser, Christos Louizos

Proceedings of the Eleventh International Conference on Learning Representations, 2023

No time to waste: practical statistical contact tracing with few low-bit messages.

Rob Romijnders, Yuki M. Asano, Christos Louizos, Max Welling

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices.

Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel

CoRR, 2022

2021

An Expectation-Maximization Perspective on Federated Learning.

Christos Louizos, Matthias Reisser, Joseph Soriaga, Max Welling

CoRR, 2021

DP-REC: Private & Communication-Efficient Federated Learning.

Aleksei Triastcyn, Matthias Reisser, Christos Louizos

CoRR, 2021

Federated Mixture of Experts.

Matthias Reisser, Christos Louizos, Efstratios Gavves, Max Welling

CoRR, 2021

Federated Learning of User Verification Models Without Sharing Embeddings.

Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Improving Fair Predictions Using Variational Inference In Causal Models.

Rik Helwegen, Christos Louizos, Patrick Forré

CoRR, 2020

Federated Learning of User Authentication Models.

Hossein Hosseini, Sungrack Yun, Hyunsin Park, Christos Louizos, Joseph Soriaga, Max Welling

CoRR, 2020

Gradient 𝓁₁ Regularization for Quantization Robustness.

Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling

CoRR, 2020

Bayesian Bits: Unifying Quantization and Pruning.

Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

DIVA: Domain Invariant Variational Autoencoders.

Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Up or Down? Adaptive Rounding for Post-Training Quantization.

Markus Nagel, Rana Ali Amjad, Mart van Baalen, Christos Louizos, Tijmen Blankevoort

Proceedings of the 37th International Conference on Machine Learning, 2020

Gradient $\ell_1$ Regularization for Quantization Robustness.

Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

The Functional Neural Process.

Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Relaxed Quantization for Discretized Neural Networks.

Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling

Proceedings of the 7th International Conference on Learning Representations, 2019

DIVA: Domain Invariant Variational Autoencoder.

Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Learning Sparse Neural Networks through L_0 Regularization.

Christos Louizos, Max Welling, Diederik P. Kingma

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Learning Sparse Neural Networks through L₀ Regularization.

Christos Louizos, Max Welling, Diederik P. Kingma

CoRR, 2017

Bayesian Compression for Deep Learning.

Christos Louizos, Karen Ullrich, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Causal Effect Inference with Deep Latent-Variable Models.

Christos Louizos, Uri Shalit, Joris M. Mooij, David A. Sontag, Richard S. Zemel, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Multiplicative Normalizing Flows for Variational Bayesian Neural Networks.

Christos Louizos, Max Welling

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

The Variational Fair Autoencoder.

Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard S. Zemel

Proceedings of the 4th International Conference on Learning Representations, 2016

Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors.

Christos Louizos, Max Welling

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Argument Extraction from News, Blogs, and the Social Web.

Theodosios Goudas, Christos Louizos, Georgios Petasis, Vangelis Karkaletsis

Int. J. Artif. Intell. Tools, 2015

2014

Argument Extraction from News, Blogs, and Social Media.

Theodosios Goudas, Christos Louizos, Georgios Petasis, Vangelis Karkaletsis

Proceedings of the Artificial Intelligence: Methods and Applications, 2014