2 code implementations • 16 Apr 2024 • Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi, Ruben Vera-Rodriguez, Minchul Kim, Christian Rathgeb, Xiaoming Liu, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Zhizhou Zhong, Yuge Huang, Yuxi Mi, Shouhong Ding, Shuigeng Zhou, Shuai He, Lingzhi Fu, Heng Cong, Rongyu Zhang, Zhihong Xiao, Evgeny Smirnov, Anton Pimenov, Aleksei Grigorev, Denis Timoshenko, Kaleb Mesfin Asfaw, Cheng Yaw Low, Hao liu, Chuyi Wang, Qing Zuo, Zhixiang He, Hatef Otroshi Shahreza, Anjith George, Alexander Unnervik, Parsa Rahimi, Sébastien Marcel, Pedro C. Neto, Marco Huber, Jan Niklas Kolf, Naser Damer, Fadi Boutros, Jaime S. Cardoso, Ana F. Sequeira, Andrea Atzori, Gianni Fenu, Mirko Marras, Vitomir Štruc, Jiang Yu, Zhangjie Li, Jichun Li, Weisong Zhao, Zhen Lei, Xiangyu Zhu, Xiao-Yu Zhang, Bernardo Biesseck, Pedro Vidal, Luiz Coelho, Roger Granada, David Menotti
Synthetic data is gaining increasing relevance for training machine learning models.
no code implementations • 4 Apr 2024 • Andrea Atzori, Fadi Boutros, Naser Damer, Gianni Fenu, Mirko Marras
Finally, we assessed the effectiveness of data augmentation approaches on synthetic and authentic data, with the same goal in mind.
1 code implementation • 24 Jan 2024 • Ludovico Boratto, Francesco Fabbri, Gianni Fenu, Mirko Marras, Giacomo Medda
Efforts in the recommendation community are shifting from the sole emphasis on utility to considering beyond-utility factors, such as fairness and robustness.
1 code implementation • 17 Nov 2023 • Pietro Melzi, Ruben Tolosana, Ruben Vera-Rodriguez, Minchul Kim, Christian Rathgeb, Xiaoming Liu, Ivan DeAndres-Tame, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia, Weisong Zhao, Xiangyu Zhu, Zheyu Yan, Xiao-Yu Zhang, Jinlin Wu, Zhen Lei, Suvidha Tripathi, Mahak Kothari, Md Haider Zama, Debayan Deb, Bernardo Biesseck, Pedro Vidal, Roger Granada, Guilherme Fickel, Gustavo Führ, David Menotti, Alexander Unnervik, Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza, Parsa Rahimi, Sébastien Marcel, Ioannis Sarridis, Christos Koutlis, Georgia Baltsou, Symeon Papadopoulos, Christos Diou, Nicolò Di Domenico, Guido Borghi, Lorenzo Pellegrini, Enrique Mas-Candela, Ángela Sánchez-Pérez, Andrea Atzori, Fadi Boutros, Naser Damer, Gianni Fenu, Mirko Marras
Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail.
no code implementations • 25 Oct 2023 • Giacomo Balloccu, Ludovico Boratto, Christian Cancedda, Gianni Fenu, Mirko Marras
This mechanism ensures zero incidence of corrupted paths by enforcing adherence to valid KG connections at the decoding level, agnostic of the underlying model architecture.
1 code implementation • 23 Aug 2023 • Ludovico Boratto, Francesco Fabbri, Gianni Fenu, Mirko Marras, Giacomo Medda
In recommendation literature, explainability and fairness are becoming two prominent perspectives to consider.
no code implementations • 22 Aug 2023 • Andrea Atzori, Gianni Fenu, Mirko Marras
Law enforcement regularly faces the challenge of ranking suspects from their facial images.
1 code implementation • 12 Apr 2023 • Giacomo Medda, Francesco Fabbri, Mirko Marras, Ludovico Boratto, Gianni Fenu
Moreover, an empirical evaluation of the perturbed network uncovered relevant patterns that justify the nature of the unfairness discovered by the generated explanations.
1 code implementation • 14 Jan 2023 • Giacomo Balloccu, Ludovico Boratto, Christian Cancedda, Gianni Fenu, Mirko Marras
Path reasoning is a notable recommendation approach that models high-order user-product relations, based on a Knowledge Graph (KG).
no code implementations • 16 Dec 2022 • Roberta Galici, Tanja Käser, Gianni Fenu, Mirko Marras
This weakness is one of the main factors undermining users' trust, since model predictions could for instance lead an instructor to not intervene on a student in need.
no code implementations • 30 Sep 2022 • Andrea Atzori, Gianni Fenu, Mirko Marras
Commonly, the recognition threshold of a face recognition system is adjusted based on the degree of security for the considered use case.
1 code implementation • 11 Sep 2022 • Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras
However, the existing explainable recommendation approaches based on KG merely optimize the selected reasoning paths for product relevance, without considering any user-level property of the paths for explanation.
1 code implementation • 23 Aug 2022 • Andrea Atzori, Gianni Fenu, Mirko Marras
In this paper, we propose a novel explanatory framework aimed to provide a better understanding of how face recognition models perform as the underlying data characteristics (protected attributes: gender, ethnicity, age; non-protected attributes: facial hair, makeup, accessories, face orientation and occlusion, image distortion, emotions) on which they are tested change.
no code implementations • 23 Jun 2022 • Gianni Fenu, Roberta Galici, Mirko Marras
In recent years, there has been a stimulating discussion on how artificial intelligence (AI) can support the science and engineering of intelligent educational applications.
no code implementations • 24 Apr 2022 • Mirko Marras, Ludovico Boratto, Guilherme Ramos, Gianni Fenu
Engaging all content providers, including newcomers or minority demographic groups, is crucial for online platforms to keep growing and working.
1 code implementation • 24 Apr 2022 • Giacomo Balloccu, Ludovico Boratto, Gianni Fenu, Mirko Marras
Existing explainable recommender systems have mainly modeled relationships between recommended and already experienced products, and shaped explanation types accordingly (e. g., movie "x" starred by actress "y" recommended to a user because that user watched other movies with "y" as an actress).
Ranked #1 on Music Recommendation on Last.FM
1 code implementation • 21 Jan 2022 • Ludovico Boratto, Gianni Fenu, Mirko Marras, Giacomo Medda
In this paper, we conduct a systematic analysis of mitigation procedures against consumer unfairness in rating prediction and top-n recommendation tasks.
no code implementations • 29 Apr 2021 • Gianni Fenu, Giacomo Medda, Mirko Marras, Giacomo Meloni
The human voice conveys unique characteristics of an individual, making voice biometrics a key technology for verifying identities in various industries.
no code implementations • 7 Jun 2020 • Ludovico Boratto, Gianni Fenu, Mirko Marras
We characterize the recommendations of representative algorithms by means of the proposed metrics, and we show that the item probability of being recommended and the item true positive rate are biased against the item popularity.
no code implementations • 7 Jun 2020 • Mirko Marras, Ludovico Boratto, Guilherme Ramos, Gianni Fenu
To reduce this effect, we propose a novel post-processing approach that balances personalization and equality of recommended opportunities.
no code implementations • 7 Jun 2020 • Ludovico Boratto, Gianni Fenu, Mirko Marras
The resulting recommended lists show fairer visibility and exposure, higher minority item coverage, and negligible loss in recommendation utility.