6 papers
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens
Vittorio Erba, Emanuele Troiani, Luca Biggio +2
Current progress in artificial intelligence is centered around so-called large language models that consist of neural networks processing long sequences of high-dimensional vectors…
Fundamental computational limits of weak learnability in high-dimensional multi-index models
Emanuele Troiani, Yatin Dandi, Leonardo Defilippis +3
Multi-index models - functions which only depend on the covariates through a non-linear transformation of their projection on a subspace - are a useful benchmark for investigating…
Building Conformal Prediction Intervals with Approximate Message Passing
Lucas Clarté, Lenka Zdeborová
Conformal prediction has emerged as a powerful tool for building prediction intervals that are valid in a distribution-free way. However, its evaluation may be computationally cost…
The phase diagram of compressed sensing with -norm regularization
Damien Barbier, Carlo Lucibello, Luca Saglietti +2
Noiseless compressive sensing is a two-steps setting that allows for undersampling a sparse signal and then reconstructing it without loss of information. The LASSO algorithm, base…
Bayes-optimal learning of an extensive-width neural network from quadratically many samples
Antoine Maillard, Emanuele Troiani, Simon Martin +3
We consider the problem of learning a target function corresponding to a single hidden layer neural network, with a quadratic activation function after the first layer, and random…
Integer Traffic Assignment Problem: Algorithms and Insights on Random Graphs
Rayan Harfouche, Giovanni Piccioli, Lenka Zdeborová
Path optimization is a fundamental concern across various real-world scenarios, ranging from traffic congestion issues to efficient data routing over the internet. The Traffic Assi…