Communication-Efficient Heterogeneous Federated Learning with Generalized Heavy-Ball Momentum

Federated Learning (FL) is the state-of-the-art approach for learning from decentralized data in privacy-constrained scenarios. As the current literature reports, the main problems associated with FL refer to system and statistical challenges: the former ones demand for efficient learning from edge devices, including lowering communication bandwidth and frequency, while the latter require algorithms robust to non-iidness. State-of-art approaches either guarantee convergence at increased communication cost or are not sufficiently robust to handle extreme heterogeneous local distributions. In this work we propose a novel generalization of the heavy-ball momentum, and present FedHBM to effectively address statistical heterogeneity in FL without introducing any communication overhead. We conduct extensive experimentation on common FL vision and NLP datasets, showing that our FedHBM algorithm empirically yields better model quality and higher convergence speed w.r.t. the state-of-art, especially in pathological non-iid scenarios. While being designed for cross-silo settings, we show how FedHBM is applicable in moderate-to-high cross-device scenarios, and how good model initializations (e.g. pre-training) can be exploited for prompt acceleration. Extended experimentation on large-scale real-world federated datasets further corroborates the effectiveness of our approach for real-world FL applications

Inhomogeneous Phase of the Chiral Gross-Neveu Model

There is substantial evidence that the ground state of the 2D chiral Gross-Neveu model, in the presence of a U(1) fermion number chemical potential μ and in the large N limit, is given by a "chiral spiral"phase, namely an inhomogeneous phase with a chiral condensate having a spatially periodic phase. We show that the chiral spiral configuration persists at finite N and T=0 for any μ>0. Our analysis is based on nonabelian bosonization, that relates the model to a U(N)1 Wess-Zumino-Witten model deformed by current-current interactions. In this description, the appearance of the inhomogeneous phase is surprisingly simple. We also rederive the phase diagram of the large N chiral Gross-Neveu model via a direct diagrammatic computation, finding agreement with previous results in the literature

Anomalies and Persistent Order in the Chiral Gross-Neveu model

We study the $2d$ chiral Gross-Neveu model at finite temperature $T$ and chemical potential $\mu$. The analysis is performed by relating the theory to a $SU(N)\times U(1)$ Wess-Zumino-Witten model with appropriate levels and global identifications necessary to keep track of the fermion spin structures. At $\mu=0$ we show that a certain $\mathbb{Z}_2$-valued 't Hooft anomaly forbids the system to be trivially gapped when fermions are periodic along the thermal circle for any $N$ and any $T>0$. We also study the two-point function of a certain composite fermion operator which allows us to determine the remnants for $T>0$ of the inhomogeneous chiral phase configuration found at $T=0$ for any $N$ and any $\mu$. The inhomogeneous configuration decays exponentially at large distances for anti-periodic fermions while it persists for $T>0$ and any $\mu$ for periodic fermions, as expected from anomaly considerations. A large $N$ analysis confirms the above findings.Comment: 28+23 pages; v2: Several clarifications and improvements, reference adde

Inhomogeneous Phase of the Chiral Gross-Neveu Model

There is substantial evidence that the ground state of the 2D chiral Gross-Neveu model, in the presence of a U(1) fermion number chemical potential mu and in the large N limit, is given by a "chiral spiral" phase, namely an inhomogeneous phase with a chiral condensate having a spatially periodic phase. We show that the chiral spiral configuration persists at finite N and T = 0 for any mu > 0. Our analysis is based on nonabelian bosonization, that relates the model to a U(N)(1) Wess-Zumino-Witten model deformed by current-current interactions. In this description, the appearance of the inhomogeneous phase is surprisingly simple. We also rederive the phase diagram of the large N chiral Gross-Neveu model via a direct diagrammatic computation, finding agreement with previous results in the literature

Anomalies and Persistent Order in the Chiral Gross-Neveu model

We study the $2d$ chiral Gross-Neveu model at finite temperature $T$ and chemical potential $\mu$. The analysis is performed by relating the theory to a $SU(N)\times U(1)$ Wess-Zumino-Witten model with appropriate levels and global identifications necessary to keep track of the fermion spin structures. At $\mu=0$ we show that a certain $\mathbb{Z}_2$-valued 't Hooft anomaly forbids the system to be trivially gapped when fermions are periodic along the thermal circle for any $N$ and any T>0. We also study the two-point function of a certain composite fermion operator which allows us to determine the remnants for T>0 of the inhomogeneous chiral phase configuration found at $T=0$ for any $N$ and any $\mu$. The inhomogeneous configuration decays exponentially at large distances for anti-periodic fermions while it persists for T>0 and any $\mu$ for periodic fermions, as expected from anomaly considerations. A large $N$ analysis confirms the above findings

Speeding up Heterogeneous Federated Learning with Sequentially Trained Superclients

Federated Learning (FL) allows training machine learning models in privacy-constrained scenarios by enabling the cooperation of edge devices without requiring local data sharing. This approach raises several challenges due to the different statistical distribution of the local datasets and the clients' computational heterogeneity. In particular, the presence of highly non-i.i.d. data severely impairs both the performance of the trained neural network and its convergence rate, increasing the number of communication rounds requested to reach a performance comparable to that of the centralized scenario. As a solution, we propose FedSeq, a novel framework leveraging the sequential training of subgroups of heterogeneous clients, i.e. superclients, to emulate the centralized paradigm in a privacy-compliant way. Given a fixed budget of communication rounds, we show that FedSeq outperforms or match several state-of-the-art federated algorithms in terms of final performance and speed of convergence. Finally, our method can be easily integrated with other approaches available in the literature. Empirical results show that combining existing algorithms with FedSeq further improves its final performance and convergence speed. We test our method on CIFAR-10 and CIFAR-100 and prove its effectiveness in both i.i.d. and non-i.i.d. scenarios.Comment: Published at the 26th International Conference on Pattern Recognition (ICPR), 2022, pp. 3376-338

Identification of a Novel p53 Modulator Endowed with Antitumoural and Antibacterial Activity through a Scaffold Repurposing Approach

Intracellular pathogens, such as Chlamydia trachomatis, have been recently shown to induce degradation of p53 during infection, thus impairing the protective response of the host cells. Therefore, p53 reactivation by disruption of the p53-MDM2 complex could reduce infection and restore pro-apoptotic effect of p53. Here, we report the identification of a novel MDM2 inhibitor with potential antitumoural and antibacterial activity able to reactivate p53. A virtual screening was performed on an in-house chemical library, previously synthesised for other targets, and led to the identification of a hit compound with a benzo[a]dihydrocarbazole structure, RM37. This compound induced p53 up-regulation in U343MG glioblastoma cells by blocking MDM2-p53 interaction and reduced tumour cell growth. NMR studies confirmed its ability to dissociate the MDM2-p53 complex. Notably, RM37 reduced Chlamydia infection in HeLa cells in a concentration-dependent manner and ameliorated the inflammatory status associated with infection

Respiratory symptoms in children living near busy roads and their relationship to vehicular traffic: results of an Italian multicenter study (SIDRIA 2)

BACKGROUND: Epidemiological studies have provided evidence that exposure to vehicular traffic increases the prevalence of respiratory symptoms and may exacerbate pre-existing asthma in children. Self-reported exposure to road traffic has been questioned as a reliable measurement of exposure to air pollutants. The aim of this study was to investigate whether there were specific effects of cars and trucks traffic on current asthma symptoms (i.e. wheezing) and cough or phlegm, and to examine the validity of self-reported traffic exposure. METHODS: The survey was conducted in 2002 in 12 centers in Northern, Center and Southern Italy, different in size, climate, latitude and level of urbanization. Standardized questionnaires filled in by parents were used to collect information on health outcomes and exposure to traffic among 33,632 6-7 and 13-14 years old children and adolescents. Three questions on traffic exposure were asked: the traffic in the zone of residence, the frequency of truck and of car traffic in the street of residence. The presence of a possible response bias for the self-reported traffic was evaluated using external validation (comparison with measurements of traffic flow in the city of Turin) and internal validations (matching by census block, in the cities of Turin, Milan and Rome). RESULTS: Overall traffic density was weakly associated with asthma symptoms but there was a stronger association with cough or phlegm (high traffic density OR = 1.24; 95% CI: 1.04, 1.49). Car and truck traffic were independently associated with cough or phlegm. The results of the external validation did not support the existence of a reporting bias for the observed associations, for all the self-reported traffic indicators examined. The internal validations showed that the observed association between traffic density in the zone of residence and respiratory symptoms did not appear to be explained by an over reporting of traffic by parents of symptomatic subjects. CONCLUSION: Children living in zones with intense traffic are at higher risk for respiratory effects. Since population characteristics are specific, the results of validation of studies on self-reported traffic exposure can not be generalized

Different molecular mechanisms causing 9p21 deletions in acute lymphoblastic leukemia of childhood

Deletion of chromosome 9p21 is a crucial event for the development of several cancers including acute lymphoblastic leukemia (ALL). Double strand breaks (DSBs) triggering 9p21 deletions in ALL have been reported to occur at a few defined sites by illegitimate action of the V(D)J recombination activating protein complex. We have cloned 23 breakpoint junctions for a total of 46 breakpoints in 17 childhood ALL (9 B- and 8 T-lineages) showing different size deletions at one or both homologous chromosomes 9 to investigate which particular sequences make the region susceptible to interstitial deletion. We found that half of 9p21 deletion breakpoints were mediated by ectopic V(D)J recombination mechanisms whereas the remaining half were associated to repeated sequences, including some with potential for non-B DNA structure formation. Other mechanisms, such as microhomology-mediated repair, that are common in other cancers, play only a very minor role in ALL. Nucleotide insertions at breakpoint junctions and microinversions flanking the breakpoints have been detected at 20/23 and 2/23 breakpoint junctions, respectively, both in the presence of recombination signal sequence (RSS)-like sequences and of other unspecific sequences. The majority of breakpoints were unique except for two cases, both T-ALL, showing identical deletions. Four of the 46 breakpoints coincide with those reported in other cases, thus confirming the presence of recurrent deletion hotspots. Among the six cases with heterozygous 9p deletions, we found that the remaining CDKN2A and CDKN2B alleles were hypermethylated at CpG islands