Grazia Cecere
Institut Mines-Télécom Business School | Digital economy, Machine learning, Ethics of algorithms
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108 search results for: machine learning
Shedding some light on black box algorithms
In recent decades, algorithms have become increasingly complex, particularly through the introduction of deep learning architectures. This has gone hand in hand with increasing difficulty in explaining their internal functioning, which has become an important issue, both legally and socially. Winston Maxwell, legal researcher, and Florence d’Alché-Buc, researcher in machine learning, who both work for Télécom Paris, describe the current challenges involved in the explainability of algorithms.
Gérard Dray
IMT Mines Alès | Artificial Intelligence, Machine Learning
Chloé Clavel
Télécom Paris | Natural Language Processing, machine learning, affective computing, human-agent interaction
Boosting tomorrow’s IoT networks
The goal of the FITNESS project is to develop networks capable of adapting to the needs of massive IoT, industrial IoT and connected transport solutions. The project is supported by the expertise of several IMT schools to address the challenges that arise from the densification of connected objects, more robust applications, energy management and various protocols, and to optimize the performance of networks in real time.
The Cybaile Chair, securing AI tools for healthcare
Thanks to AI tools, it is now possible to identify signs of disease in medical images in a robust and secure way. However, developing such tools requires access to large volumes of sensitive health data. How can we protect this data, and the tools that use it? These are the questions that Cybaile, the industrial chair in cybersecurity, AI and trust in healthcare, is trying to answer.
Elsa Dupraz, 2024 IMT-Academy of Science Young Scientist Prize
Channel coding is the focus of Elsa Dupraz’s research, a key process for improving information transmission in telecommunications. While the technique’s effectiveness in this field is well known, the researcher is also exploring novel applications, such as data compression and DNA storage. Her research, at the intersection between several disciplines, has fostered multiple collaborations and earned her the 2024 IMT-Academy of Science Young Scientist Prize.
Do we still need structured information? (The answer is yes)
Large language models (LLM) are revolutionizing the relevance of natural language comprehension and text responses. Combining them with structured data for standardized organization only improves their accuracy. It is against this backdrop that Telecom Paris researcher Fabian Suchanek and his team are continuing to develop the YAGO knowledge base.
The cruel dilemma of health data in the ai era: privacy or equity?
Federated learning is a way to collaboratively train artificial intelligence models. It thus represents a possible solution to AI biases, often caused by training said models on samples that lack diversity. In the healthcare sector, these biases can lead to problems of equity between patients. The EQUIHid project explores how federated learning can help develop more equitable healthcare services.
A biocluster to boost innovation in cancer treatment
Paris Saclay Cancer Cluster offers a wide range of scientific and technical solutions to support the challenging field of research aimed at fighting cancer. Telecom Paris is invested in this ambitious initiative, which strengthens ties between those driving innovation in oncology and provides access to a combination of technological platforms, databases, expertise and training opportunities.
