Christos Louizos
23 papers · 2016–2026 · 8 venues · across top CS/AI venues
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Achievements
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Dynamic Duo
(13)
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Century Club Β· Bronze
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Conference Pioneer
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Renaissance Researcher
(8)
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Keyword Collector
(125)
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Research topics
Machine Learning
(22)
Artificial Intelligence
(15)
Optimization & Theory Β· Machine Learning
(15)
Deep Learning
(12)
Application Areas
(11)
Core AI
(9)
Models
(6)
Techniques
(5)
Learning Paradigms Β· Artificial Intelligence
(4)
Learning Types
(4)
Bayesian & Probabilistic
(3)
Core Methods
(3)
Learning Paradigms Β· Machine Learning
(3)
Optimization & Theory Β· Deep Learning
(3)
Data Science & Analytics
(2)
Keywords
federated learning
(6)
model compression
(6)
neural network pruning
(3)
weight quantization
(3)
neural network quantization
(3)
conformal prediction
(2)
neural network
(2)
user verification
(2)
bayesian neural network
(2)
uncertainty estimation
(2)
importance sampling
(2)
causal inference
(2)
bayesian inference
(2)
post-training quantization
(2)
variational inference
(2)
variational autoencoder
(2)
contact tracing
(2)
domain generalization
(1)
statistical inference
(1)
semi-supervised learning
(1)
Papers
Distilling Safe LLM Systems via Soft Prompts for On Device Settings
UAI 2026
Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence
ICLR 2025
Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits
ICLR 2025
A Mutual Information Perspective on Federated Contrastive Learning
ICLR 2024
An Information Theoretic Perspective on Conformal Prediction
NeurIPS 2024
Importance Matching Lemma for Lossy Compression with Side Information
AISTATS 2024
On Sampling Strategies for Spectral Model Sharding
NeurIPS 2024
Protect Your Score: Contact-Tracing with Differential Privacy Guarantees
AAAI 2024
Federated Learning Toolkit with Voice-based User Verification Demo
Interspeech 2023
Hyperparameter Optimization through Neural Network Partitioning
ICLR 2023
No time to waste: practical statistical contact tracing with few low-bit messages
AISTATS 2023
Federated Learning of User Verification Models Without Sharing Embeddings
ICML 2021
Bayesian Bits: Unifying Quantization and Pruning
NeurIPS 2020
DIVA: Domain Invariant Variational Autoencoders
MIDL 2020
Gradient β_1 Regularization for Quantization Robustness
ICLR 2020
Up or Down? Adaptive Rounding for Post-Training Quantization
ICML 2020
Relaxed Quantization for Discretized Neural Networks
ICLR 2019
The Functional Neural Process
NeurIPS 2019
Learning Sparse Neural Networks through L_0 Regularization
ICLR 2018
Bayesian Compression for Deep Learning
NeurIPS 2017
Causal Effect Inference with Deep Latent-Variable Models
NeurIPS 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
ICML 2017
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors
ICML 2016