1 citations · 1 across the 3 of their papers we have counts for
9 papers
Optimizing accuracy and diversity: a multi-task approach to forecast combinations
Giovanni Felici, Antonio M. Sudoso
We present a multi-task optimization approach based on a deep learning architecture for time series forecasting. We leverage large collections of time series to identify the weight…
Beyond binarity: Semidefinite programming for ternary quadratic problems
Frank de Meijer, Veronica Piccialli, Renata Sotirov +1
We study the ternary quadratic problem (TQP), a quadratic optimization problem with linear constraints where the variables take values in . While semidefinite program…
Exact and Heuristic Algorithms for Constrained Biclustering
Antonio M. Sudoso
Biclustering, also known as co-clustering or two-way clustering, simultaneously partitions the rows and columns of a data matrix to reveal submatrices with coherent patterns. Incor…
Strong bounds for large-scale Minimum Sum-of-Squares Clustering
Anna Livia Croella, Veronica Piccialli, Antonio M. Sudoso
Clustering is a fundamental technique in data analysis and machine learning, used to group similar data points together. Among various clustering methods, the Minimum Sum-of-Square…
A column generation algorithm with dynamic constraint aggregation for minimum sum-of-squares clustering
Antonio M. Sudoso, Daniel Aloise
The minimum sum-of-squares clustering problem (MSSC), also known as -means clustering, refers to the problem of partitioning data points into clusters, with the objectiv…
Optimal Placement of Nature-Based Solutions for Urban Challenges
Diego Maria Pinto, Davide Donato Russo, Antonio M. Sudoso
Increased urbanization and climate change intensify urban heat islands and degrade air quality, making current mitigation strategies insufficient. Nature-based solutions (NBSs), su…