NEPTUNE: Network-and GPU-aware management of serverless functions at the edge
Nowadays a wide range of applications is constrained by low-latency requirements that
cloud infrastructures cannot meet. Multiaccess Edge Computing (MEC) has been proposed …
cloud infrastructures cannot meet. Multiaccess Edge Computing (MEC) has been proposed …
Multicriteria classifier ensemble learning for imbalanced data
One of the vital problems with the imbalanced data classifier training is the definition of an
optimization criterion. Typically, since the exact cost of misclassification of the individual …
optimization criterion. Typically, since the exact cost of misclassification of the individual …
NEPTUNE: A Comprehensive Framework for Managing Serverless Functions at the Edge
Applications that are constrained by low-latency requirements can hardly be executed on
cloud infrastructures, given the high network delay required to reach remote servers. Multi …
cloud infrastructures, given the high network delay required to reach remote servers. Multi …
A methodology for the offline evaluation of recommender systems in a user interface with multiple carousels
N Felicioni, M Ferrari Dacrema… - Adjunct Proceedings of the …, 2021 - dl.acm.org
Many video-on-demand and music streaming services provide the user with a page
consisting of several recommendation lists, ie, widgets or swipeable carousels, each built …
consisting of several recommendation lists, ie, widgets or swipeable carousels, each built …
Predicting tweet engagement with graph neural networks
Social Networks represent one of the most important online sources to share content across
a world-scale audience. In this context, predicting whether a post will have any impact in …
a world-scale audience. In this context, predicting whether a post will have any impact in …
SVM ensemble training for imbalanced data classification using multi-objective optimization techniques
One of the main problems with classifier training for imbalanced data is defining the correct
learning criterion. On the one hand, we want the minority class to be correctly recognized …
learning criterion. On the one hand, we want the minority class to be correctly recognized …
Measuring the user satisfaction in a recommendation interface with multiple carousels
N Felicioni, M Ferrari Dacrema… - Proceedings of the 2021 …, 2021 - dl.acm.org
It is common for video-on-demand and music streaming services to adopt a user interface
composed of several recommendation lists, ie, widgets or swipeable carousels, each …
composed of several recommendation lists, ie, widgets or swipeable carousels, each …
Context-Based Tweet Engagement Prediction
J Jeromela - arXiv preprint arXiv:2310.03147, 2023 - arxiv.org
Twitter is currently one of the biggest social media platforms. Its users may share, read, and
engage with short posts called tweets. For the ACM Recommender Systems Conference …
engage with short posts called tweets. For the ACM Recommender Systems Conference …
Exploiting Contextual Normalizations and Article Endorsement for News Recommendation
A Alari, L Campana, FG Ciliberto, S Maggese… - Proceedings of the …, 2024 - dl.acm.org
We provide an overview of the approach used as team FeatureSalad for the ACM RecSys
Challenge 2024, organized by Ekstra Bladet. The competition addressed the problem of …
Challenge 2024, organized by Ekstra Bladet. The competition addressed the problem of …
Pessimistic Rescaling and Distribution Shift of Boosting Models for Impression-Aware Online Advertising Recommendation
P Basso, A Benedetti, N Cecere, A Maranelli… - Proceedings of the …, 2023 - dl.acm.org
In this paper, we provide an overview of the approach we used as team Gabibboost for the
ACM RecSys Challenge 2023, organized by ShareChat and Moj. The challenge focused on …
ACM RecSys Challenge 2023, organized by ShareChat and Moj. The challenge focused on …