Publications

2024

• Self-Supervised Learning of Multi-level Audio Representations for Music Segmentation
  
  • Buisson Morgan
  • Mcfee Brian
  • Essid Slim
  • Crayencour Hélène
  IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2024, pp.1-13. The task of music structure analysis refers to automatically identifying the location and the nature of musical sections within a song. In the supervised scenario, structural annotations generally result from exhaustive data collection processes, which represents one of the main challenges of this task. Moreover, both the subjectivity of music structure and the hierarchical characteristics it exhibits make the obtained structural annotations not fully reliable, in the sense that they do not convey a "universal ground-truth" unlike other tasks in music information retrieval. On the other hand, the quickly growing quantity of available music data has enabled weakly supervised and self-supervised approaches to achieve impressive results on a wide range of music-related problems. In this work, a self-supervised learning method is proposed to learn robust multi-level music representations prior to structural segmentation using contrastive learning. To this end, sets of frames sampled at different levels of detail are used to train a deep neural network in a disentangled manner. The proposed method is evaluated on both flat and multi-level segmentation. We show that each distinct sub-region of the output embeddings can efficiently account for structural similarity at their own targeted level of detail, which ultimately improves performance of downstream flat and multi-level segmentation. Finally, complementary experiments are carried out to study how the obtained representations can be further adapted to specific datasets using a supervised fine-tuning objective in order to facilitate structure retrieval in domains where human annotations remain scarce. (10.1109/TASLP.2024.3379894)
  DOI : 10.1109/TASLP.2024.3379894
• The Non-Cancelling Intersections Conjecture
  
  • Amarilli Antoine
  • Monet Mikaël
  • Suciu Dan
  , 2024. In this note, we present a conjecture on intersections of set families, and a rephrasing of the conjecture in terms of principal downsets of Boolean lattices. The conjecture informally states that, whenever we can express the measure of a union of sets in terms of the measure of some of their intersections using the inclusion-exclusion formula, then we can express the union as a set from these same intersections via the set operations of disjoint union and subset complement. We also present a partial result towards establishing the conjecture.
• Reducing the Silicon Area Overhead of Counter-Based Rowhammer Mitigations
  
  • France Loïc
  • Bruguier Florent
  • Novo David
  • Mushtaq Maria
  • Benoit Pascal
  IEEE Computer Architecture Letters, Institute of Electrical and Electronics Engineers, 2024, 23 (1), pp.61-64. Modern computer memories have shown to have reliability issues. The main memory is the target of a security threat called Rowhammer, which causes bit flips in adjacent victim cells of aggressor rows. Numerous countermeasures have been proposed, some of the most efficient ones relying on row access counters, with different techniques to reduce the impact on performance, energy consumption and silicon area. In these proposals, the number of counters is calculated using the maximum number of row activations that can be issued to the protected bank. As reducing the number of counters results in lower silicon area and energy overheads, this can have a direct impact on the production and usage costs. In this work, we demonstrate that two of the most efficient countermeasures can have their silicon area overhead reduced by approximately 50% without impacting the protection level by changing their counting granularity. (10.1109/LCA.2023.3328824)
  DOI : 10.1109/LCA.2023.3328824
• Check-Bit Region Exploration in Two-Dimensional Error Correction Codes
  
  • Freitas David
  • Mota David
  • Coelho David
  • Fontinele Humberto
  • Coelho Alexandre
  • Silveira Jarbas
  • Naviner Lirida
  • Mota João
  • Marcon César
  IEEE Access, IEEE, 2024, 12, pp.131830-131841. The diversity of nanosatellite applications is increasingly attracting the scientific community’s attention. The main component of these satellites is the OnBoard Computer (OBC), which is responsible for all control and processing. Also, OBC encompasses memory elements highly susceptible to failure; due to spatial radiation, errors in these memories can cause severe damage. As integrated circuit technology advances, cluster errors are more and more frequent. Error Correction Code (ECC) is one of the most used techniques for mitigating errors, and two-dimensional ECCs are used to reach higher error correction power. The paper aims to assess the number of checkbit regions to include for code enhancement. Our analysis investigates the impact of incorporating up to three checkbit regions. The results are analyzed through adjacent and exhaustive error injection tests and compared to other ECCs. Besides, reliability, redundancy, and hardware implementation costs are investigated, and an evaluation metric is proposed to choose the best ECC. Experiments with random error patterns show that the proposal with three crossed check-bit regions achieves a correction of 100% for up to four bitflips and greater than 90% for up to seven bitflips. Additionally, considering adjacent error patterns, the proposal achieves a correction greater than 97.4% with up to five bitflips. (10.1109/ACCESS.2024.3456582)
  DOI : 10.1109/ACCESS.2024.3456582
• A Gaussian Process Based Approach for Validation of Multi-Variable Measurement Systems: Application to SAR Measurement Systems
  
  • Bujard Cédric
  • Neufeld Esra
  • Douglas Mark
  • Wiart Joe
  • Kuster Niels
  IEEE Access, IEEE, 2024, 12, pp.60404-60424. Resource-efficient and robust validation of systems designed to measure a multi-dimensional parameter space is an unsolved problem as it would require millions of test permutations for comprehensive validation coverage. In the paper, an efficient and comprehensive validation approach based on a Gaussian Process (GP) model of the test system has been developed that can operate system-agnostically, avoids calibration to a fixed set of known validation benchmarks, and supports large configuration spaces. The approach consists of three steps that can be performed independently by different parties: 1) GP model creation, 2) model confirmation, and 3) targeted search for critical cases. It has been applied to two systems that measure specific absorption rate (SAR) for compliance testing of wireless devices and apply different SAR measurement methods: a probe-scanning system (per IEC/IEEE 62209–1528), and a static sensor-array system (per IEC 62209–3). The results demonstrate that the approach is practical, feasible, suitable for proving effective equivalence, and can be applied to any measurement method and implementation. The presented method is sufficiently general to be of value not only for SAR system validation, but also in a wide variety of applications that require critical, independent, and efficient validation. (10.1109/ACCESS.2024.3393778)
  DOI : 10.1109/ACCESS.2024.3393778
• On Ranking-based Tests of Independence
  
  • Limnios Myrto
  • Clémençon Stéphan
  , 2024. In this paper we develop a novel nonparametric framework to test the independence of two random variables $\mathbf{X}$ and $\mathbf{Y}$ with unknown respective marginals $H(dx)$ and $G(dy)$ and joint distribution $F(dx dy)$, based on {\it Receiver Operating Characteristic} (ROC) analysis and bipartite ranking. The rationale behind our approach relies on the fact that, the independence hypothesis $\mathcal{H}_0$ is necessarily false as soon as the optimal scoring function related to the pair of distributions $(H\otimes G,\; F)$, obtained from a bipartite ranking algorithm, has a ROC curve that deviates from the main diagonal of the unit square. We consider a wide class of rank statistics encompassing many ways of deviating from the diagonal in the ROC space to build tests of independence. Beyond its great flexibility, this new method has theoretical properties that far surpass those of its competitors. Nonasymptotic bounds for the two types of testing errors are established. From an empirical perspective, the novel procedure we promote in this paper exhibits a remarkable ability to detect small departures, of various types, from the null assumption $\mathcal{H}_0$, even in high dimension, as supported by the numerical experiments presented here.