2 citations · 3 across the 7 of their papers we have counts for
7 papers
A Probabilistic Approach to Pose Synchronization for Multi-Reference Alignment with Applications to MIMO Wireless Communication Systems
Rob Romijnders, Gabriele Cesa, Christos Louizos +2
From molecular imaging to wireless communications, the ability to align and reconstruct signals from multiple misaligned observations is crucial for system performance. We study th…
On Sampling Strategies for Spectral Model Sharding
Denis Korzhenkov, Christos Louizos
The problem of heterogeneous clients in federated learning has recently drawn a lot of attention. Spectral model sharding, i.e., partitioning the model parameters into low-rank mat…
Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits
Ashish Khisti, M. Reza Ebrahimi, Hassan Dbouk +3
We consider multi-draft speculative sampling, where the proposal sequences are sampled independently from different draft models. At each step, a token-level draft selection scheme…
Variational Learning ISTA
Fabio Valerio Massoli, Christos Louizos, Arash Behboodi
Compressed sensing combines the power of convex optimization techniques with a sparsity-inducing prior on the signal space to solve an underdetermined system of equations. For many…
An Information Theoretic Perspective on Conformal Prediction
Alvaro H. C. Correia, Fabio Valerio Massoli, Christos Louizos +1
Conformal Prediction (CP) is a distribution-free uncertainty estimation framework that constructs prediction sets guaranteed to contain the true answer with a user-specified probab…
Importance Matching Lemma for Lossy Compression with Side Information
Buu Phan, Ashish Khisti, Christos Louizos
We propose two extensions to existing importance sampling based methods for lossy compression. First, we introduce an importance sampling based compression scheme that is a variant…
Improving Fair Predictions Using Variational Inference In Causal Models
Rik Helwegen, Christos Louizos, Patrick Forré
The importance of algorithmic fairness grows with the increasing impact machine learning has on people's lives. Recent work on fairness metrics shows the need for causal reasoning…