2008 |
12 | EE | Alessandro Vullo,
Andrea Passerini,
Paolo Frasconi,
Fabrizio Costa,
Gianluca Pollastri:
On the Convergence of Protein Structure and Dynamics. Statistical Learning Studies of Pseudo Folding Pathways.
EvoBIO 2008: 200-211 |
11 | EE | Fabrizio Costa,
Björn Bringmann:
Towards Combining Structured Pattern Mining and Graph Kernels.
ICDM Workshops 2008: 192-201 |
2007 |
10 | EE | Fabrizio Costa,
Sauro Menchetti,
Paolo Frasconi:
Comparing Sequence Classification Algorithms for Protein Subcellular Localization.
Perspectives of Neural-Symbolic Integration 2007: 23-48 |
9 | EE | Alessio Ceroni,
Fabrizio Costa,
Paolo Frasconi:
Classification of small molecules by two- and three-dimensional decomposition kernels.
Bioinformatics 23(16): 2038-2045 (2007) |
2005 |
8 | EE | Sauro Menchetti,
Fabrizio Costa,
Paolo Frasconi:
Weighted decomposition kernels.
ICML 2005: 585-592 |
7 | EE | Sauro Menchetti,
Fabrizio Costa,
Paolo Frasconi,
Massimiliano Pontil:
Wide coverage natural language processing using kernel methods and neural networks for structured data.
Pattern Recognition Letters 26(12): 1896-1906 (2005) |
2004 |
6 | EE | Fabrizio Costa,
Paolo Frasconi:
Distributed community crawling.
WWW (Alternate Track Papers & Posters) 2004: 362-363 |
2003 |
5 | | Fabrizio Costa,
Paolo Frasconi,
Vincenzo Lombardo,
Giovanni Soda:
Towards Incremental Parsing of Natural Language Using Recursive Neural Networks.
Appl. Intell. 19(1-2): 9-25 (2003) |
2002 |
4 | | Fabrizio Costa,
Paolo Frasconi,
Vincenzo Lombardo,
Patrick Sturt,
Giovanni Soda:
Enhancing First-Pass Attachment Prediction.
ECAI 2002: 508-512 |
2001 |
3 | EE | Fabrizio Costa,
Vincenzo Lombardo,
Paolo Frasconi,
Giovanni Soda:
Wide Coverage Incremental Parsing by Learning Attachment Preferences.
AI*IA 2001: 297-307 |
2000 |
2 | EE | Fabrizio Costa,
Paolo Frasconi,
Vincenzo Lombardo,
Giovanni Soda:
Learning incremental syntactic structures with recursive neural networks.
KES 2000: 458-461 |
1999 |
1 | EE | Fabrizio Costa,
Paolo Frasconi,
Giovanni Soda:
A topological transformation for hidden recursive modelsarchitecture networks.
ESANN 1999: 51-56 |