Publications by Marco Bondaschi

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We derive an upper bound on the reliability function of mismatched decoding for zero-rate codes. The bound is based on a result by Komlos that shows the existence of a subcode with certain symmetry properties. The bound is shown to coincide with the expurg ...

We revise the proof of low-rate upper bounds on the reliability function of discrete memoryless channels for ordinary and list-decoding schemes, in particular Berlekamp and Blinovsky's zero-rate bound, as well as Blahut's bound for low rates. The available ...

Large language models (LLMs) have recently gained much popularity due to their surprising ability at generating human-like English sentences. LLMs are essentially predictors, estimating the probability of a sequence of words given the past. Therefore, it i ...

Attention-based transformers have achieved tremendous success across a variety of disciplines including natural languages. To deepen our understanding of their sequential modeling capabilities, there is a growing interest in using Markov input processes to ...

Inspired by Sibson’s alpha-mutual information, we introduce a new parametric class of universal predictors. This class interpolates two well-known predictors, the mixture estimator, that includes the Laplace and the Krichevsky-Trofimov predictors, and the ...

In recent years, transformer-based models have revolutionized deep learning, particularly in sequence modeling. To better understand this phenomenon, there is a growing interest in using Markov input processes to study transformers. However, our current un ...

Marco Bondaschi

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Mismatched Decoding Reliability Function at Zero Rate

A Revisitation of Low-Rate Bounds on the Reliability Function of Discrete Memoryless Channels for List Decoding

Zero-rate Reliability Function for Mismatched Decoding

Batch Universal Prediction

Attention with Markov: A Curious Case of Single-layer Transformers

Alpha-NML Universal Predictors

Local to global: Learning dynamics and effect of initialization for transformers