Cornet Seminar – 23/02/2024

20 February 2024

The next seminar of the Cornet team will take place on February 23, 2024, at 11:35 a.m. in S3, and will consist of two parts. First, Sylvie Chaddad (LIA) will present her thesis topic on Stochastic Control for Optimizing Crowdfunding Project Dynamics. Then, Lorena Garrido (University of Veracruz) will present her work titled On the Monge-Kantorovich divergence. Abstract: The Monge-Kantorovich divergence is a measure of closeness between probability distributions. Historically, it arises from an optimal transport problem of sand movement, in the area of civil engineering. Today, the Monge-Kantorovich problem has given rise to many theoretical studies, as well as various applications, including data analysis. In this talk, a couple of applications in data analysis will be mentioned.

Best paper award

19 February 2024

Congratulations to Grace Tessa Masse and Abderrahim Benslimane, for the best paper award they obtained at International Conference on Computing, Networking and Communications (IEEE ICNC 2024) Title: A Secure Hierarchical Federated Learning Using Dirichlet-based Trust Management Abstract—Hierarchical Federated Learning (HFL) is a distributed machine learning training system in which a server works with several clients and edge nodes while maintaining data privacy. Distributed machine learning training systems are also known as Federated Learning, but HFL is a type of Federated Learning that utilizes a hierarchical network architecture to address computational issues when dealing with a high number of clients. However, HFL is vulnerable to attacks such as data poisoning, which may jeopardize the entire training process and result in misclassifications. As system defenders, we have to tackle this issue. Using a label-flipping attack, we investigate the effect of data poisoning attacks on HFL training. We propose a trust management-based strategy to mitigate data poisoning attacks, which assesses client trustworthiness using a Dirichlet distribution. We maintain a record of previous activities, allowing the server to enhance its knowledge based on client reliability. We demonstrate the proposed approach’s effectiveness through improvements in model performance after removing malicious clients, using the MNIST dataset Plus d'infos

SLG Seminar- 15/02/2024

13 February 2024

Thibault Roux will organize a debate on the subject mentioned below: “Recent advances in technology have raised many questions and concerns about their impact on our societies. Many people are concerned about military use, mass surveillance or disinformation. From a more global perspective, Nick Bostrom, a philosopher, theorizes the vulnerable world hypothesis which predicts that science will destroy humanity.In this debate, we will question our own biases as researchers and try to answer the ethical questions raised by this hypothesis. Is science a threat to humanity? Should we stop science? Or more seriously, can we find a solution to prevent ourselves from self-destruction ?”

Cornet Seminar – 31/01/2024

26 January 2024

The next seminar of the Cornet team will take place on January 31, 2024, at 11:35 am in S3 and will consist of two parts. Firstly, Felipe Albuquerque (LIA) will present his thesis topic on ‘The p-Median Problem with Coverage Constraints: New Resolution Methods and Application to the Design of Public Services.’ Following that, Luca Dini and Pierre Jourlin will present their ongoing work on the theme of ‘Hybrid Methods for Cognitive Attitudes Detection.’ Summary: In this seminar, we will present ongoing work on the transformation of a keyword spotting system into a concept-based labeling engine. We will highlight four major axes of this work:

SLG Seminar – Ryan Whetten – 01/02/2024

25 January 2024

The next SLG meeting will take place in room S5 on Thursday, February 1st, from 12:00 PM to 1:00 PM. Ryan Whetten will present his work, and you can find a brief introduction below. ——————————————————————— Open Implementation and Study of BEST-RQ for Speech Processing Abstract: Self-Supervised Learning (SSL) has proven to be useful in various speech tasks. However, these methods are generally very demanding in terms of data, memory, and computational resources. Recently, Google came out with a model called BEST-RQ (BERT-based Speech pre-Training with Random-projection Quantizer). Despite BEST-RQ’s great performance and simplicity, details are lacking in the original paper and there is no official easy-to-use open-source implementation. Furthermore, BEST-RQ has not been evaluated on other downstream tasks aside from ASR. In this presentation, we will discuss the details of my implementation of BEST-RQ and then see results from our preliminary study on four downstream tasks. Results show that a random projection quantizer can achieve similar downstream performance as wav2vec 2.0 while decreasing training time by over a factor of two.

SLG Seminar – Paul Gauthier Noé – 18/01/2024

10 January 2024

On 18 January from 12 am, we will host a talk from Dr. Paul Gauthier Noé on « Explaining probabilistic predictions … ». The presentation will be hosted on room S6.    More details will follow   Bio: Paul Gauthier Noe just received a PhD in Computer Science in Avignon Université under the supervision of Prof. Jean-François Bonastre and Dr. Driss Matrouf. He was working for the international JST-ANR VoicePersonae project and his main research interests are Speaker verification, Bayesian decision theory, Calibration of probabilities and Privacy in Speech.

PhD defense of Noé Cécillon – 18 January 2024

8 January 2024

Date: Thursday, January 18, 2023 at 14:00. Place: University of Avignon, Campus JH Fabre, Ada Lovelace amphitheater Jury : Title: Combining Graph and Text to Model Conversations: An Application to Online Abuse Detection. Abstract: Online abusive behaviors can have devastating consequences on individuals and communities. With the global expansion of internet and the social networks, anyone can be confronted with these behaviors. Over the past few years, laws and regulations have been established to regulate this kind of abuse but the responsibility ultimately lies with the platforms that host online communications. They are asked to monitor their users in order to prevent the proliferation of abusive content. Timely detection and moderation is a key factor to reduce the quantity and impact of abusive behaviors. However, due to the sheer quantity of online messages posted every day, platforms struggle to provide adequate resources. Since this implies high human and financial costs, companies have a keen interest in automating this process. Although it may seem a relatively simple task, it turns out to be quite complex. Indeed, malicious users have developed numerous techniques to bypass the standard automated methods. Allusions or implied meaning are other examples of strategies that automatic methods struggle Plus d'infos

SLG Seminar – Fenna Poletiek – 12/01/2024

8 January 2024

On 12 January from 12 am, we will host a virtual talk from Dr. Fenna Poletiek from Institute of Psychology at Leiden University on « Language learning in the lab ».   The presentation will be hosted on room S6.   Abstract: Language learning in the lab Language learning skills have been considered a defining feature of humanness. In this view language cannot be acquired by mere associative or statistical learning processes, only, like many other skills are learned by human and nonhuman primates during development. Indeed, the high (recursive) complexity of human grammars have been shown to make them impossible to learn by exposure to language exemplars only. Some research suggests, however, that at least some statistical learning is recruited in language acquisition (Perruchet & Pacton, 2006). And primates have been shown to mimic complex grammatical patterns after being trained on a sequence of stimulus responses (Rey et al., 2012). We performed series of studies with artificial languages in the lab, to investigate associative and statistical learning processes that support language learning. The results thus far suggest a fine tuned cooperation between three crucial features of the natural language learning process: first, learning proceeds ‘starting small’ with short simple sentences growing in complexity Plus d'infos

PhD defense of Julio Perez-Garcia – 18 December 2023

14 December 2023

Place: University of Avignon, Campus Hannah Arendt, Salle des ThèsesDate: Monday, December 18, 2023 at 14:00. Title: Contribution to security and privacy in the Blockchain-based Internet of Things: Robustness, Reliability, and Scalability. Abstract: The Internet of Things (IoT) is a diverse network of objects or ”things” typically interconnected via the Internet. Given the sensitivity of the information exchanged in IoT applications, it is essential to guarantee security and privacy. This problem is aggravated by the open nature of wireless communications, and the power and computing resource limitations of most IoT devices. At the same time, existing IoT security solutions are based on centralized architectures, which raises scalability issues and the single point of failure problem, making them susceptible to denial-of-service attacks and technical failures. Blockchain has emerged as an attractive solution to IoT security and centralization issues. Blockchains replicate a permanent, append-only record of all transactions occurring on a network across multiple devices, keeping them synchronized through a consensus protocol. Blockchain implementation may involve high computational and energy costs for devices. Consequently, solutions based on Fog/Edge computing have been considered in the integration with IoT. This approach shifts the higher computational load and higher energy consumption to the devices with higher Plus d'infos

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