collaborators

11 papers

cs.LG2026

A Unified Framework for Quantized and Continuous Strong Lottery Tickets

Aakash Kumar, Emanuele Natale

The Strong Lottery Ticket Hypothesis (SLTH) asserts that sufficiently overparameterized, randomly initialized neural networks contain sparse subnetworks that, even without any trai…

cs.LG2026

Structured vs. Unstructured Pruning: An Exponential Gap

Davide Ferre', Frédéric Giroire, Frederik Mallmann-Trenn +1

The Strong Lottery Ticket Hypothesis (SLTH) states that large, randomly initialized neural networks contain sparse subnetworks capable of approximating a target function at initial…

cs.LG2026

Compositional Generalization in Autoregressive Models via Logit Composition

Aakash Kumar, Maria Sofia Bucarelli, Emanuele Natale

Composing autoregressive models remains a core challenge in understanding how large language models can combine behaviors or skills learned across tasks. We introduce a new and pri…

cs.LG2026

Beyond Fixed Points: Superpolynomial Capacity of Asymmetric Hopfield Networks

Aakash Kumar, Anatoly Khina, Frederik Mallmann-Trenn +1

Classical Hopfield networks are limited to static patterns due to symmetric weights, whereas asymmetric networks can encode temporal sequences via limit-cycle attractors. Achieving…

cs.DC2026

DejaVu: A Minimalistic Mechanism for Distributed Plurality Consensus

Francesco d'Amore, Niccolò D'Archivio, George Giakkoupis +2

We study the plurality consensus problem in distributed systems where a population of extremely simple agents, each initially holding one of opinions, aims to agree on the init…

cs.DS2026

Intermittent Cauchy walks enable optimal 3D search across target shapes and sizes

Matteo Stromieri, Emanuele Natale, Amos Korman

Target shape, not just size, plays a pivotal role in determining detectability during random search. We analyze intermittent Lévy walks in three dimensions, and mathematically pro…