Roberto Esposito

According to our database1, Roberto Esposito authored at least 30 papers between 2001 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
Constraining deep representations with a noise module for fair classification.
Proceedings of the SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, online event, [Brno, Czech Republic], March 30, 2020

2019
Taxonomic and Whole Object Constraints: A Deep Architecture.
Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

Partitioned Least Squares.
Proceedings of the AI*IA 2019 - Advances in Artificial Intelligence, 2019

2017
A Neural Network Model for Taxonomic Responding with Realistic Visual Inputs.
Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2015
Prediction and interpretation of the lipophilicity of small peptides.
J. Comput. Aided Mol. Des., 2015

2013
CDoT: Optimizing MAP Queries on Trees.
Proceedings of the AI*IA 2013: Advances in Artificial Intelligence, 2013

2011
Restructuring the Gene Ontology to emphasise regulative pathways and to improve gene similarity queries.
Int. J. Comput. Biol. Drug Des., 2011

Tackling the DREAM Challenge for Gene Regulatory Networks Reverse Engineering.
Proceedings of the AI*IA 2011: Artificial Intelligence Around Man and Beyond, 2011

2010
BREVE: An HMPerceptron-Based Chord Recognition System.
Proceedings of the Advances in Music Information Retrieval, 2010

2009
CarpeDiem: Optimizing the Viterbi Algorithm and Applications to Supervised Sequential Learning.
J. Mach. Learn. Res., 2009

OpenCDLig: a free web application for sharing resources about cyclodextrin/ligand complexes.
J. Comput. Aided Mol. Des., 2009

Empirical Assessment of Two Strategies for Optimizing the Viterbi Algorithm.
Proceedings of the AI*IA 2009: Emergent Perspectives in Artificial Intelligence, 2009

2007
Incremental Extraction of Association Rules in Applicative Domains.
Applied Artificial Intelligence, 2007

CarpeDiem: an algorithm for the fast evaluation of SSL classifiers.
Proceedings of the Machine Learning, 2007

Tonal Harmony Analysis: A Supervised Sequential Learning Approach.
Proceedings of the AI*IA 2007: Artificial Intelligence and Human-Oriented Computing, 2007

Trip Around the HMPerceptron Algorithm: Empirical Findings and Theoretical Tenets.
Proceedings of the AI*IA 2007: Artificial Intelligence and Human-Oriented Computing, 2007

2006
Answering constraint-based mining queries on itemsets using previous materialized results.
J. Intell. Inf. Syst., 2006

A Conditional Model for Tonal Analysis.
Proceedings of the Foundations of Intelligent Systems, 16th International Symposium, 2006

2005
Experimental comparison between bagging and Monte Carlo ensemble classification.
Proceedings of the Machine Learning, 2005

Optimization of Association Rules Extraction Through Exploitation of Context Dependent Constraints.
Proceedings of the AI*IA 2005: Advances in Artificial Intelligence, 2005

2004
Integrating Web Conceptual Modeling and Web Usage Mining.
Proceedings of the Advances in Web Mining and Web Usage Analysis, 2004

A Monte Carlo analysis of ensemble classification.
Proceedings of the Machine Learning, 2004

Query Rewriting in Itemset Mining.
Proceedings of the Flexible Query Answering Systems, 6th International Conference, 2004

Empirical Evaluation of the Effects of Concept Complexity on Generalization Error.
Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

Employing Inductive Databases in Concrete Applications.
Proceedings of the Constraint-Based Mining and Inductive Databases, 2004

A Novel Incremental Approach to Association Rules Mining in Inductive Databases.
Proceedings of the Constraint-Based Mining and Inductive Databases, 2004

2003
Monte Carlo Theory as an Explanation of Bagging and Boosting.
Proceedings of the IJCAI-03, 2003

Explaining Bagging with Monte Carlo Theory.
Proceedings of the AI*IA 2003: Advances in Artificial Intelligence, 2003

2002
Is a Greedy Covering Strategy an Extreme Boosting?
Proceedings of the Foundations of Intelligent Systems, 13th International Symposium, 2002

2001
Boosting as a Monte Carlo Algorithm.
Proceedings of the AI*IA 2001: Advances in Artificial Intelligence, 2001


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