Cornet Seminar – Judith Agueda Roldan Ahumada – 15/03/2024

12 March 2024

In the context of team Cornet’s seminars, Judith Agueda Roldan Ahumada (Universidad Veracruzana) will present her research work on Modeling and optimization of a vehicle routing problem in a coffee company, on March 15, 2023, at 11:35 in the meeting room. Abstract: In the central region of Veracruz, Mexico, given the weather and soil conditions, there are different companies dedicated to the coffee bean production. To carry out the different activities such as planting, harvesting,cleaning, among others, it is necessary to transport the harvesters to different agricultural lands; usually, this logistics problem is solved empirically without considering the cost per transfer. The problem, that will be shown, arose from the needing to solve a transport logistic problem for a coffee bean company in the central region of Veracruz.We consider a single vehicle with maximum capacity of N items, the vehicle starts the path with out items from a parking and it can collect the items in places that are along the way, that goes from parking to the place where the items are delivered (agricultural lands). The places are ordered consecutively, such that, once the vehicle goes through one, it can not return to the previous sites and it is Plus d'infos

SLG Seminar – Antoine Caubrière – 03/15/2024

11 March 2024

Next SLG meeting will take place on 03/15/2024, from 10 AM to 11 AM. We will host Antoine Caubrière from the company Orange, who will present his recent work Title: Representation of Multilingual Speech through Self-Supervised Learning in an Exclusively Sub-Saharan Context. Abstract: The Orange group operates in over a dozen sub-Saharan African countries with the ambition of offering services tailored to the needs of clients in this region. To provide localized and accessible services to digitally underserved and low-literate individuals, Orange is investing in the development of voice-based conversational agents to inform and assist its clients and employees.The implementation of such a service requires, first and foremost, a technological component for speech recognition and understanding.The strong linguistic diversity of the African continent, coupled with the challenges of limited annotated data, poses one of the challenges in implementing speech processing technology for these languages. One potential solution could be the utilization of self-supervised learning techniques. Leveraging this type of learning enables the training of a speech representation extractor capable of capturing rich features. This approach utilizes a large quantity of unlabeled data for pre-training a model before fine-tuning it for specific tasks. While numerous self-supervised models are shared within the Plus d'infos

LIA Doctoral Fellowship 2024

27 February 2024

The 2024 doctoral fellowship from the LIA has been awarded to the Cornet team. Several topics have been proposed, and they are available on the Adum platform. In alphabetical order by title: Interested candidates should apply on the Adum platform. Most importantly, before doing so, contact the researchers who propose the topics to discuss them further.

Position for Assistant Professor in Computer Science at Avignon Institute of Technology

27 February 2024

As part of the national synchronized recruitment campaign for teaching and research faculty in 2024, Avignon University is offering a position for an Assistant Professor in Computer Science. Teaching will take place at the Avignon University Institute of Technology, mainly in the field of Data Science, and research will be conducted at the LIA (Avignon University CS Lab). The position description is available here (in French):

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.

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