Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| personal:portfolio:home [2022/06/05 16:50] – antonello | personal:portfolio:home [2025/05/02 09:41] (current) – external edit 127.0.0.1 | ||
|---|---|---|---|
| Line 4: | Line 4: | ||
| This page refers to some IT related projects I have been involved in recent years.\\ | This page refers to some IT related projects I have been involved in recent years.\\ | ||
| For a list of academic publications refer [[: | For a list of academic publications refer [[: | ||
| + | |||
| + | |||
| + | ===== StrategicGames: | ||
| + | The StrategicGames package provides functionalities to work with n-players strategic games, including finding mixed or pure Nash equilibria in simultaneous games (currently using support enumeration or solving the complementarity problem).\\ | ||
| + | **Skills**: Computational game theory, Nash equilibrium\\ | ||
| + | **Year**: 2023\\ | ||
| + | [[https:// | ||
| ===== BDisposal: A library to perform non parametric efficiency and productivity analysis through the B-disposal scheme ===== | ===== BDisposal: A library to perform non parametric efficiency and productivity analysis through the B-disposal scheme ===== | ||
| - | The BDisposal package proposes a serie of environmental efficiency and productivity algorithms for non-parametric modelling when we relax the disposability assumption of some of the outputs and/or inputs (e.g. pollution). These efficiency and productivity measures are implemented through convex and non-convex Data Envelopment Analysis (DEA) (aka Frontier Efficiency Analysis) models. | + | The BDisposal package proposes a serie of environmental efficiency and productivity algorithms for non-parametric modelling when we relax the disposability assumption of some of the outputs and/or inputs (e.g. pollution). These efficiency and productivity measures are implemented through convex and non-convex Data Envelopment Analysis (DEA) (aka Frontier Efficiency Analysis) models.\\ |
| **Skills**: Data Envelopment Analysis, Production frontiers\\ | **Skills**: Data Envelopment Analysis, Production frontiers\\ | ||
| **Year**: 2021\\ | **Year**: 2021\\ | ||
| Line 13: | Line 20: | ||
| ===== BetaML: The Beta Machine Learning Toolkit ===== | ===== BetaML: The Beta Machine Learning Toolkit ===== | ||
| - | A rather complete library of Machine learning algorithms (supervised and unsupervised) and ML-workflow related utility functions (kernels, losses, optimisers, samples, encoders...) | + | A rather complete library of Machine learning algorithms (supervised and unsupervised) and ML-workflow related utility functions (kernels, losses, optimisers, samples, encoders...)\\ |
| **Skills**: Julia, ML\\ | **Skills**: Julia, ML\\ | ||
| **Year**: 2021\\ | **Year**: 2021\\ | ||
| Line 20: | Line 27: | ||
| ===== Vcat: Cut and merge video segments ===== | ===== Vcat: Cut and merge video segments ===== | ||
| - | Python script to cut and merge video segments in a easy-to-use interface (useful when you discover in a one hours filmed lesson you said something idiot on minute X ;-) ) | + | Python script to cut and merge video segments in a easy-to-use interface (useful when you discover in a one hours filmed lesson you said something idiot on minute X ;-) )\\ |
| **Skills**: python, ffmpeg, moviepy\\ | **Skills**: python, ffmpeg, moviepy\\ | ||
| **Year**: 2019\\ | **Year**: 2019\\ | ||
