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Matteo Monti

Publications and source records attributed to Matteo Monti.

At least 19 recordsLinked to original sources
arXiv2026

Hardy spaces of discrete holomorphic functions on the upper half-lattice

We develop a theory of Hardy spaces $H^p$ of discrete holomorphic functions on the upper half-lattice, within the classical framework of discrete holomorphicity on the square lattice. We prove Cauchy and Poisson reproducing formulas, establish a boundary norm identity, and obtain Paley--Wiener type characterizations for these spaces. In the Hilbert space case, we describe the associated reproducing kernel and Szeg\H{o} projection, and we compare the discrete theory with the classical Hardy space on the upper half-plane through a family of discrete holomorphic approximants of classical $H^2$-functions. We also prove duality results for $H^p$, $1<p<\infty$, establish uniqueness and sampling results on horizontal lines, and introduce Bergman-type spaces, comparing two natural weighted scales.

math.CV↗
arXiv2026

Quadratic discrepancy estimates for probability measures on the Heisenberg group

We initiate the study of quadratic discrepancy for finite point sets on the Heisenberg group $\mathbb H^n$ with respect to upper Ahlfors regular probability measures. For a natural family of test sets given by left translations and dilations of cylindrically defined neighborhoods, we introduce an $L^2$-discrepancy and establish a Roth-type lower bound depending on the homogeneous dimension of $\mathbb H^n$. This result extends classical discrepancy estimates from the Euclidean and compact settings to a non-commutative, step-two nilpotent Lie group. It should be viewed as a first step toward the development of a discrepancy theory on the Heisenberg group.

math.CA↗
arXiv2024

Fast Byzantine Total Order Broadcast

This paper presents Flutter, the first Byzantine Total Order Broadcast implementation with a broadcast-to-delivery latency of $2\Delta + \epsilon$ time units, $\Delta$ being the message delay and $\epsilon$ an arbitrarily small constant margin, when all processes are correct, the network is synchronous, hence local clocks are well-synchronized. Under the same conditions, state-of-the-art protocols require at least $3\Delta$ time units in practical deployments where clients differ from servers. We prove Flutter's good-case latency is quasi-optimal, meaning it cannot be improved upon by any finite amount. Flutter is deterministic, leaderless, and signature-free hence quantum-resilient; it assumes partial synchrony and at least $5f + 1$ servers, where $f$ bounds the number of faults. Under the hood, Flutter builds upon Blink, a novel Binary Consensus implementation with Representative Validity, whose fast path enables decisions in $\Delta$ time units when all correct servers propose the same value.

cs.DC↗
arXiv2024

Endpoint estimates and sparse domination in nonhomogeneous trees

We prove endpoint and sparse-like bounds for Bergman projectors on nonhomogeneous, radial trees $X$ that model manifolds with possibly unbounded geometry. The natural Bergman measures on $X$ may fail to be doubling, and even locally doubling, with respect to the right metric in our setting. Weighted consequences of our sparse domination results are also considered, and are in line with the known results in the disk. Our endpoint results are partly a consequence of a new Calder\'on-Zygmund theory for discrete, non-locally doubling metric spaces.

math.CA↗
arXiv2024

POMONAG: Pareto-Optimal Many-Objective Neural Architecture Generator

Neural Architecture Search (NAS) automates neural network design, reducing dependence on human expertise. While NAS methods are computationally intensive and dataset-specific, auxiliary predictors reduce the models needing training, decreasing search time. This strategy is used to generate architectures satisfying multiple computational constraints. Recently, Transferable NAS has emerged, generalizing the search process from dataset-dependent to task-dependent. In this field, DiffusionNAG is a state-of-the-art method. This diffusion-based approach streamlines computation, generating architectures optimized for accuracy on unseen datasets without further adaptation. However, by focusing solely on accuracy, DiffusionNAG overlooks other crucial objectives like model complexity, computational efficiency, and inference latency -- factors essential for deploying models in resource-constrained environments. This paper introduces the Pareto-Optimal Many-Objective Neural Architecture Generator (POMONAG), extending DiffusionNAG via a many-objective diffusion process. POMONAG simultaneously considers accuracy, number of parameters, multiply-accumulate operations (MACs), and inference latency. It integrates Performance Predictor models to estimate these metrics and guide diffusion gradients. POMONAG's optimization is enhanced by expanding its training Meta-Dataset, applying Pareto Front Filtering, and refining embeddings for conditional generation. These enhancements enable POMONAG to generate Pareto-optimal architectures that outperform the previous state-of-the-art in performance and efficiency. Results were validated on two search spaces -- NASBench201 and MobileNetV3 -- and evaluated across 15 image classification datasets.

cs.LG↗
arXiv2023

Calder\'on-Zygmund theory on some Lie groups of exponential growth

Let $G = N \rtimes A$, where $N$ is a stratified Lie group and $A= \mathbb R_+$ acts on $N$ via automorphic dilations. We prove that the group $G$ has the Calder\'on-Zygmund property, in the sense of Hebisch and Steger, with respect to a family of flow measures and metrics. This generalizes in various directions previous works by Hebisch and Steger and Martini, Ottazzi and Vallarino, and provides a new approach in the development of Calder\'on-Zygmund theory in Lie groups of exponential growth. We also prove a weak type $(1,1)$ estimate for the Hardy-Littlewood maximal operator naturally arising in this setting.

math.FA↗
arXiv2023

Horocyclic harmonic Bergman spaces on homogeneous trees

The main focus of this contribution is on the harmonic Bergman spaces $\mathcal{B}_{\alpha}^{p}$ on the $q$-homogeneous tree $\mathfrak{X}_q$ endowed with a family of measures $\sigma_\alpha$ that are constant on the horocycles tangent to a fixed boundary point and turn out to be doubling with respect to the corresponding horocyclic Gromov distance. A central role is played by the reproducing kernel Hilbert space $\mathcal{B}_{\alpha}^{2}$ for which we find a natural orthonormal basis and formulae for the kernel. We also consider the atomic Hardy space and the bounded mean oscillation space. Appealing to an adaptation of Calder\'on-Zygmund theory and to standard boundedness results for integral operators on $L^p_\alpha$ spaces with H\"ormander-type kernels, we determine the boundedness properties of the Bergman projection.

math.FA↗
arXiv2023

Every Bit Counts in Consensus

Consensus enables n processes to agree on a common valid L-bit value, despite t < n/3 processes being faulty and acting arbitrarily. A long line of work has been dedicated to improving the worst-case communication complexity of consensus in partial synchrony. This has recently culminated in the worst-case word complexity of O(n^2). However, the worst-case bit complexity of the best solution is still O(n^2 L + n^2 kappa) (where kappa is the security parameter), far from the \Omega(n L + n^2) lower bound. The gap is significant given the practical use of consensus primitives, where values typically consist of batches of large size (L > n). This paper shows how to narrow the aforementioned gap while achieving optimal linear latency. Namely, we present a new algorithm, DARE (Disperse, Agree, REtrieve), that improves upon the O(n^2 L) term via a novel dispersal primitive. DARE achieves O(n^{1.5} L + n^{2.5} kappa) bit complexity, an effective sqrt{n}-factor improvement over the state-of-the-art (when L > n kappa). Moreover, we show that employing heavier cryptographic primitives, namely STARK proofs, allows us to devise DARE-Stark, a version of DARE which achieves the near-optimal bit complexity of O(n L + n^2 poly(kappa)). Both DARE and DARE-Stark achieve optimal O(n) latency.

cs.DC↗
arXiv2023

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

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. Such a drastic increase led to a growing interest in distributed ML, which in turn made worker failures and adversarial attacks an increasingly pressing concern. While distributed byzantine resilient algorithms have been proposed in a differentiable setting, none exist in a gradient-free setting. The goal of this work is to address this shortcoming. For that, we introduce a more general definition of byzantine-resilience in ML - the \textit{model-consensus}, that extends the definition of the classical distributed consensus. We then leverage this definition to show that a general class of gradient-free ML algorithms - ($1,\lambda$)-Evolutionary Search - can be combined with classical distributed consensus algorithms to generate gradient-free byzantine-resilient distributed learning algorithms. We provide proofs and pseudo-code for two specific cases - the Total Order Broadcast and proof-of-work leader election.

cs.DC↗
arXiv2023

Chop Chop: Byzantine Atomic Broadcast to the Network Limit

At the heart of state machine replication, the celebrated technique enabling decentralized and secure universal computation, lies Atomic Broadcast, a fundamental communication primitive that orders, authenticates, and deduplicates messages. This paper presents Chop Chop, a Byzantine Atomic Broadcast system that uses a novel authenticated memory pool to amortize the cost of ordering, authenticating and deduplicating messages, achieving "line rate" (i.e., closely matching the complexity of a protocol that does not ensure any ordering, authentication or Byzantine resilience) even when processing messages as small as 8 bytes. Chop Chop attains this performance by means of a new form of batching we call distillation. A distilled batch is a set of messages that are fast to authenticate, deduplicate, and order. Batches are distilled using a novel interactive protocol involving brokers, an untrusted layer of facilitating processes between clients and servers. In a geo-distributed deployment of 64 medium-sized servers, Chop Chop processes 43,600,000 messages per second with an average latency of 3.6 seconds. Under the same conditions, state-of-the-art alternatives offer two orders of magnitude less throughput for the same latency. We showcase three simple Chop Chop applications: a Payment system, an Auction house and a "Pixel war" game, respectively achieving 32, 2.3 and 35 million operations per second.

cs.DC↗
arXiv2023

$H^1$ and BMO spaces for exponentially decreasing measures on homogeneous trees

We consider a family of measures on a $q$-homogeneous tree that decrease exponentially with respect to the distance from the origin. Such measures are doubling with respect to the Gromov distance. We define atomic Hardy and BMO spaces for that measures, and we prove interpolation results regarding such spaces. As a consequence we have boundedness results for integral operators involving Hardy, BMO, and $L^p$ spaces.

math.AP↗
arXiv2022

Oracular Byzantine Reliable Broadcast [Extended Version]

Byzantine Reliable Broadcast (BRB) is a fundamental distributed computing primitive, with applications ranging from notifications to asynchronous payment systems. Motivated by practical consideration, we study Client-Server Byzantine Reliable Broadcast (CSB), a multi-shot variant of BRB whose interface is split between broadcasting clients and delivering servers. We present Draft, an optimally resilient implementation of CSB. Like most implementations of BRB, Draft guarantees both liveness and safety in an asynchronous environment. Under good conditions, however, Draft achieves unparalleled efficiency. In a moment of synchrony, free from Byzantine misbehaviour, and at the limit of infinitely many broadcasting clients, a Draft server delivers a $b$-bits payload at an asymptotic amortized cost of $0$ signature verifications, and $\log_2(c) + b$ bits exchanged, where $c$ is the number of clients in the system. This is the information-theoretical minimum number of bits required to convey the payload ($b$ bits, assuming it is compressed), along with an identifier for its sender ($\log_2(c)$ bits, necessary to enumerate any set of $c$ elements, and optimal if broadcasting frequencies are uniform or unknown). These two achievements have profound practical implications. Real-world BRB implementations are often bottlenecked either by expensive signature verifications, or by communication overhead. For Draft, instead, the network is the limit: a server can deliver payloads as quickly as it would receive them from an infallible oracle.

cs.DC↗
arXiv2022

Carbon: Scaling Trusted Payments with Untrusted Machines

This paper introduces Carbon, a high-throughput system enabling asynchronous (safe) and consensus-free (efficient) payments and votes within a dynamic set of clients. Carbon is operated by a dynamic set of validators that may be reconfigured asynchronously, offering its clients eclipse resistance as well as lightweight bootstrap. Carbon offers clients the ability to select validators by voting them in and out of the system thanks to its novel asynchronous and stake-less voting mechanism. Carbon relies on an asynchronous and deterministic implementation of Byzantine reliable broadcast that uniquely leverages a permissionless set of untrusted servers, brokers, to slash the cost of client authentication inherent to Byzantine fault tolerant systems. Carbon is able to sustain a throughput of one million payments per second in a geo-distributed environment, outperforming the state of the art by three orders of magnitude with equivalent latencies.

cs.DC↗
arXiv2022

Harmonic Bergman projectors on homogeneous trees

In this paper we investigate some properties of the harmonic Bergman spaces $\mathcal A^p(\sigma)$ on a $q$-homogeneous tree, where $q\geq 2$, $1\leq p<\infty$, and $\sigma$ is a finite measure on the tree with radial decreasing density, hence nondoubling. These spaces were introduced by J.~Cohen, F.~Colonna, M.~Picardello and D.~Singman. When $p=2$ they are reproducing kernel Hilbert spaces and we compute explicitely their reproducing kernel. We then study the boundedness properties of the Bergman projector on $L^p(\sigma)$ for $1<p<\infty$ and their weak type (1,1) boundedness for radially exponentially decreasing measures on the tree. The weak type (1,1) boundedness is a consequence of the fact that the Bergman kernel satisfies an appropriate integral H\"ormander's condition.

math.CV↗
arXiv2021

Unitarization of the Horocyclic Radon Transform on Symmetric Spaces

We consider the Radon transform for a dual pair $(X,\Xi)$, where $X=G/K$ is a noncompact symmetric space and $\Xi$ is the space of horocycles of $X$. We address the unitarization problem that was considered (and solved in some cases) by Helgason, namely the determination of a pseudo-differential operator such that the pre-composition with the Radon transform extends to a unitary operator $\mathcal{Q}\colon L^2(X)\to L_\flat^2(\Xi)$, where $L_\flat^2(\Xi)$ is a closed subspace of $L^2(\Xi)$ which accounts for the Weyl symmetries. Furthermore, we show that the unitary extension intertwines the quasi-regular representations of $G$ on $L^2(X)$ and $L_\flat^2(\Xi)$.

math.RT↗
arXiv2020

Online Payments by Merely Broadcasting Messages (Extended Version)

We address the problem of online payments, where users can transfer funds among themselves. We introduce Astro, a system solving this problem efficiently in a decentralized, deterministic, and completely asynchronous manner. Astro builds on the insight that consensus is unnecessary to prevent double-spending. Instead of consensus, Astro relies on a weaker primitive---Byzantine reliable broadcast---enabling a simpler and more efficient implementation than consensus-based payment systems. In terms of efficiency, Astro executes a payment by merely broadcasting a message. The distinguishing feature of Astro is that it can maintain performance robustly, i.e., remain unaffected by a fraction of replicas being compromised or slowed down by an adversary. Our experiments on a public cloud network show that Astro can achieve near-linear scalability in a sharded setup, going from $10K$ payments/sec (2 shards) to $20K$ payments/sec (4 shards). In a nutshell, Astro can match VISA-level average payment throughput, and achieves a $5\times$ improvement over a state-of-the-art consensus-based solution, while exhibiting sub-second $95^{th}$ percentile latency.

cs.DC↗
arXiv2020

Unitarization of the Horocyclic Radon Transform on Homogeneous Trees

Following previous work in the continuous setup, we construct the unitarization of the horocyclic Radon transform on a homogeneous tree X and we show that it intertwines the quasi regular representations of the group of isometries of X on the tree itself and on the space of horocycles.

math.RT↗