Christos Louizos

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 49

Top Topics

Variational Bayesian

Quantization Noise

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Top Venues

Publications

Alvaro H. C. Correia, Fabio Valerio Massoli, Christos Louizos, Arash Behboodi
An Information Theoretic Perspective on Conformal Prediction. CoRR (2024)
Fabio Valerio Massoli, Christos Louizos, Arash Behboodi
Variational Learning ISTA. CoRR (2024)
Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling
DNA: Differentially private Neural Augmentation for contact tracing. CoRR (2024)
Christos Louizos, Matthias Reisser, Denis Korzhenkov
A Mutual Information Perspective on Federated Contrastive Learning. ICLR (2024)
Christos Louizos, Matthias Reisser, Denis Korzhenkov
A Mutual Information Perspective on Federated Contrastive Learning. CoRR (2024)
Buu Phan, Ashish Khisti, Christos Louizos
Importance Matching Lemma for Lossy Compression with Side Information. CoRR (2024)
Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling
Protect Your Score: Contact-Tracing with Differential Privacy Guarantees. AAAI (2024)
Buu Phan, Ashish Khisti, Christos Louizos
Importance Matching Lemma for Lossy Compression with Side Information. AISTATS (2024)
Fabio Valerio Massoli, Christos Louizos, Arash Behboodi
Variational Learning ISTA. Trans. Mach. Learn. Res. 2024 (2024)
Babak Ehteshami Bejnordi, Gaurav Kumar, Amelie Royer, Christos Louizos, Tijmen Blankevoort, Mohsen Ghafoorian
InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning. CoRR (2024)
Mahdi Morafah, Matthias Reisser, Bill Lin, Christos Louizos
Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data. CoRR (2024)
Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling
Protect Your Score: Contact Tracing With Differential Privacy Guarantees. CoRR (2023)
Bruno Mlodozeniec, Matthias Reisser, Christos Louizos
Hyperparameter Optimization through Neural Network Partitioning. ICLR (2023)
Bruno Mlodozeniec, Matthias Reisser, Christos Louizos
Hyperparameter Optimization through Neural Network Partitioning. CoRR (2023)
Rob Romijnders, Yuki M. Asano, Christos Louizos, Max Welling
No time to waste: practical statistical contact tracing with few low-bit messages. AISTATS (2023)
Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel
Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices. Trans. Mach. Learn. Res. 2023 (2023)
Prathamesh Mandke, Rachel Oberst, Matthias Reisser, Avijit Chakraborty, Christos Louizos, Joseph Soriaga, Daniel Madrigal Diaz, Andre Manoel, Nalin Singal, Jeff Omhover, Robert Sim
Federated Learning Toolkit with Voice-based User Verification Demo. INTERSPEECH (2023)
Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel
Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices. CoRR (2022)
Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling
Federated Learning of User Verification Models Without Sharing Embeddings. ICML (2021)
Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling
Federated Learning of User Verification Models Without Sharing Embeddings. CoRR (2021)
Aleksei Triastcyn, Matthias Reisser, Christos Louizos
DP-REC: Private & Communication-Efficient Federated Learning. CoRR (2021)
Matthias Reisser, Christos Louizos, Efstratios Gavves, Max Welling
Federated Mixture of Experts. CoRR (2021)
Christos Louizos, Matthias Reisser, Joseph Soriaga, Max Welling
An Expectation-Maximization Perspective on Federated Learning. CoRR (2021)
Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling
Gradient $\ell_1$ Regularization for Quantization Robustness. ICLR (2020)
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
DIVA: Domain Invariant Variational Autoencoders. MIDL (2020)
Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling
Bayesian Bits: Unifying Quantization and Pruning. NeurIPS (2020)
Mart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling
Bayesian Bits: Unifying Quantization and Pruning. CoRR (2020)
Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling
Regularization for Quantization Robustness. CoRR (2020)
Markus Nagel, Rana Ali Amjad, Mart van Baalen, Christos Louizos, Tijmen Blankevoort
Up or Down? Adaptive Rounding for Post-Training Quantization. CoRR (2020)
Rik Helwegen, Christos Louizos, Patrick Forré
Improving Fair Predictions Using Variational Inference In Causal Models. CoRR (2020)
Markus Nagel, Rana Ali Amjad, Mart van Baalen, Christos Louizos, Tijmen Blankevoort
Up or Down? Adaptive Rounding for Post-Training Quantization. ICML (2020)
Hossein Hosseini, Sungrack Yun, Hyunsin Park, Christos Louizos, Joseph Soriaga, Max Welling
Federated Learning of User Authentication Models. CoRR (2020)
Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling
The Functional Neural Process. NeurIPS (2019)
Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling
The Functional Neural Process. CoRR (2019)
Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling
Relaxed Quantization for Discretized Neural Networks. ICLR (Poster) (2019)
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
DIVA: Domain Invariant Variational Autoencoders. CoRR (2019)
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
DIVA: Domain Invariant Variational Autoencoder. DGS@ICLR (2019)
Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling
Relaxed Quantization for Discretized Neural Networks. CoRR (2018)
Christos Louizos, Max Welling, Diederik P. Kingma
Learning Sparse Neural Networks through L_0 Regularization. ICLR (Poster) (2018)
Christos Louizos, Max Welling
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks. CoRR (2017)
Christos Louizos, Karen Ullrich, Max Welling
Bayesian Compression for Deep Learning. NIPS (2017)
Christos Louizos, Max Welling
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks. ICML (2017)
Christos Louizos, Uri Shalit, Joris M. Mooij, David A. Sontag, Richard S. Zemel, Max Welling
Causal Effect Inference with Deep Latent-Variable Models. NIPS (2017)
Christos Louizos, Max Welling, Diederik P. Kingma
Regularization. CoRR (2017)
Christos Louizos, Karen Ullrich, Max Welling
Bayesian Compression for Deep Learning. CoRR (2017)
Christos Louizos, Uri Shalit, Joris M. Mooij, David A. Sontag, Richard S. Zemel, Max Welling
Causal Effect Inference with Deep Latent-Variable Models. CoRR (2017)
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard S. Zemel
The Variational Fair Autoencoder. ICLR (2016)
Christos Louizos, Max Welling
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors. ICML (2016)
Christos Louizos, Max Welling
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors. CoRR (2016)
Theodosios Goudas, Christos Louizos, Georgios Petasis, Vangelis Karkaletsis
Argument Extraction from News, Blogs, and the Social Web. Int. J. Artif. Intell. Tools 24 (5) (2015)
Theodosios Goudas, Christos Louizos, Georgios Petasis, Vangelis Karkaletsis
Argument Extraction from News, Blogs, and Social Media. SETN (2014)