Sequential Proximity: Towards Provably Scalable Concurrent Search Algorithms

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Vision Transformer Adapters for Generalizable Multitask Learning

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We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains. Integrated into an off-the-shelf vision transformer backbone, our adapters can simultaneously solve mu ...

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Results on Sparse Integer Programming and Geometric Independent Sets

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An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

EPFL2023

Fairness and Explainability in Clustering Problems

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In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...

EPFL2023

Learning Sparse Graphons And The Generalized Kesten-Stigum Threshold

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The problem of learning graphons has attracted considerable attention across several scientific communities, with significant progress over the re-cent years in sparser regimes. Yet, the current techniques still require diverg-ing degrees in order to succe ...

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Capturing Types

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Type systems usually characterize the shape of values but not their free variables. However, many desirable safety properties could be guaranteed if one knew the free variables captured by values. We describe CC

Assoc Computing Machinery2023

Algorithms push forward the application of MALDI-TOF mass fingerprinting in rapid precise diagnosis

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Macromolecular mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is a quick tool for biochemical analysis. In combination with algorithms for automated data analysis and interpretation, it has wide appli ...

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Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

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Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms but also to a drastic increase in computational power used to train them.|S ...

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Language Model Decoding as Likelihood–Utility Alignment

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A critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm re- main unclear. Previous works only compare decoding algorithms in narrow sc ...

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Sketches, metrics and fast algorithms

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As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...

EPFL2022

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