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Paolo Garza
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- affiliation: Polytechnic University of Turin, Italy
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2020 – today
- 2024
- [j43]Tailai Song
, Paolo Garza
DeX: Deep learning-based throughput prediction for real-time communications with emphasis on traffic eXtremes. Comput. Networks 249: 110507 (2024) - [j42]Lorenzo Vaiani
Emotion Recognition from Videos Using Multimodal Large Language Models. Future Internet 16(7): 247 (2024) - [c74]Yihao Ding, Lorenzo Vaiani, Soyeon Caren Han, Jean Lee, Paolo Garza, Josiah Poon, Luca Cagliero:
3MVRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding. ACL (Findings) 2024: 15233-15244 - [c73]Tailai Song
BitFormer: Transformer-Based Neural Network for Bitrate Prediction in Real-Time Communications. CCNC 2024: 65-70 - [c72]Daniele Rege Cambrin
DQNC2S: DQN-Based Cross-Stream Crisis Event Summarizer. ECIR (3) 2024: 422-430 - [c71]Daniele Rege Cambrin, Giuseppe Gallipoli, Irene Benedetto, Luca Cagliero, Paolo Garza:
Beyond Accuracy Optimization: Computer Vision Losses for Large Language Model Fine-Tuning. EMNLP (Findings) 2024: 12060-12079 - [c70]Moreno La Quatra, Alkis Koudounas, Lorenzo Vaiani, Elena Baralis, Luca Cagliero, Paolo Garza, Sabato Marco Siniscalchi:
Benchmarking Representations for Speech, Music, and Acoustic Events. ICASSP Workshops 2024: 505-509 - [c69]Daniele Rege Cambrin, Paolo Garza:
Paraphrase Loss for Abstractive Summarization. Tiny Papers @ ICLR 2024 - [c68]Tailai Song, Paolo Garza, Michela Meo, Maurizio Matteo Munafò:
Throughput Prediction in Real-Time Communications: Spotlight on Traffic Extremes. ISCC 2024: 1-7 - [c67]Tailai Song, Paolo Garza, Michela Meo, Maurizio Matteo Munafò:
Towards the Detection of Unobservable Losses in Real-Time Communications. LANMAN 2024: 21-26 - [c66]Paolo Pertino, Leonardo Pavarino, Simone Lomolino, Enrico Miotto, Daniele Rege Cambrin, Paolo Garza, Emanuele Ogliari:
Ground-Based Contrail Detection by Means of Computer Vision Models: A Comparison Between Visible and Infrared Images. RTSI 2024: 254-259 - [i13]Daniele Rege Cambrin, Luca Cagliero, Paolo Garza:
DQNC2S: DQN-based Cross-stream Crisis event Summarizer. CoRR abs/2401.06683 (2024) - [i12]Daniele Rege Cambrin, Luca Colomba, Paolo Garza:
CaBuAr: California Burned Areas dataset for delineation. CoRR abs/2401.11519 (2024) - [i11]Luca Colomba, Paolo Garza:
ViGEO: an Assessment of Vision GNNs in Earth Observation. CoRR abs/2402.09962 (2024) - [i10]Yihao Ding, Lorenzo Vaiani, Soyeon Caren Han, Jean Lee
M3-VRD: Multimodal Multi-task Multi-teacher Visually-Rich Form Document Understanding. CoRR abs/2402.17983 (2024) - [i9]Daniele Rege Cambrin, Paolo Garza:
QuakeSet: A Dataset and Low-Resource Models to Monitor Earthquakes through Sentinel-1. CoRR abs/2403.18116 (2024) - [i8]Moreno La Quatra, Alkis Koudounas, Lorenzo Vaiani, Elena Baralis, Luca Cagliero, Paolo Garza, Sabato Marco Siniscalchi:
Benchmarking Representations for Speech, Music, and Acoustic Events. CoRR abs/2405.00934 (2024) - [i7]Daniele Rege Cambrin, Isaac Corley, Paolo Garza, Peyman Najafirad:
Estimating Earthquake Magnitude in Sentinel-1 Imagery via Ranking. CoRR abs/2407.18128 (2024) - [i6]Daniele Rege Cambrin, Isaac Corley, Paolo Garza:
Depth Any Canopy: Leveraging Depth Foundation Models for Canopy Height Estimation. CoRR abs/2408.04523 (2024) - [i5]Daniele Rege Cambrin, Eleonora Poeta, Eliana Pastor, Tania Cerquitelli, Elena Baralis, Paolo Garza:
KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation. CoRR abs/2408.07040 (2024) - [i4]Daniele Rege Cambrin, Gabriele Scaffidi Militone, Luca Colomba, Giovanni Malnati, Daniele Apiletti, Paolo Garza:
Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment. CoRR abs/2408.08396 (2024) - [i3]Daniele Rege Cambrin, Giuseppe Gallipoli, Irene Benedetto, Luca Cagliero, Paolo Garza:
Beyond Accuracy Optimization: Computer Vision Losses for Large Language Model Fine-Tuning. CoRR abs/2409.13641 (2024) - [i2]Tailai Song, Paolo Garza, Michela Meo, Maurizio Matteo Munafò:
Modelling Concurrent RTP Flows for End-to-end Predictions of QoS in Real Time Communications. CoRR abs/2410.15846 (2024) - 2023
- [j41]Luca Cagliero
Shortlisting machine learning-based stock trading recommendations using candlestick pattern recognition. Expert Syst. Appl. 216: 119493 (2023) - [j40]Luca Colomba
Density-Based Clustering by Means of Bridge Point Identification. IEEE Trans. Knowl. Data Eng. 35(11): 11274-11287 (2023) - [c65]Luca Colomba, Paolo Garza:
ViGEO: an Assessment of Vision GNNs in Earth Observation. ICDM (Workshops) 2023: 816-822 - [c64]Andrea Avignone, Silvia Chiusano, Alessandro Fiori, Paolo Garza, Emanuele Marchetta:
A Novel DB CASE Tool for Relational Databases. SEBD 2023: 100 - [c63]Lorenzo Vaiani, Luca Cagliero
PoliTo at SemEval-2023 Task 1: CLIP-based Visual-Word Sense Disambiguation Based on Back-Translation. SemEval@ACL 2023: 1447-1453 - 2022
- [j39]Gianluca Perna, Dena Markudova
Retina: An open-source tool for flexible analysis of RTC traffic. Comput. Networks 202: 108637 (2022) - [j38]Jacopo Fior
Leveraging Explainable AI to Support Cryptocurrency Investors. Future Internet 14(9): 251 (2022) - [j37]Elena Daraio
Complementing Location-Based Social Network Data With Mobility Data: A Pattern-Based Approach. IEEE Trans. Intell. Transp. Syst. 23(11): 21216-21227 (2022) - [j36]Gianluca Perna, Dena Markudova, Martino Trevisan
Real-Time Classification of Real-Time Communications. IEEE Trans. Netw. Serv. Manag. 19(4): 4676-4690 (2022) - [c62]Luca Colomba, Alessandro Farasin, Simone Monaco
A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery. CIKM 2022: 3893-3897 - [c61]Luca Colomba, Luca Cagliero
Mining spatiotemporally invariant patterns. SIGSPATIAL/GIS 2022: 63:1-63:4 - [c60]Lorenzo Vaiani
ViPER: Video-based Perceiver for Emotion Recognition. MuSe @ ACM Multimedia 2022: 67-73 - [c59]Lorenzo Vaiani
Transformer-based Non-Verbal Emotion Recognition: Exploring Model Portability across Speakers' Genders. MuSe @ ACM Multimedia 2022: 89-94 - [c58]Moreno La Quatra
How Much Attention Should we Pay to Mosquitoes? ACM Multimedia 2022: 7135-7139 - [c57]Daniele Rege Cambrin, Luca Colomba, Paolo Garza:
Vision Transformers for Burned Area Delineation. MACLEAN@PKDD/ECML 2022 - [c56]Lorenzo Vaiani
Leveraging multimodal content for podcast summarization. SAC 2022: 863-870 - [d1]Luca Colomba
Satellite Burned Area Dataset. Zenodo, 2022 - 2021
- [j35]Dena Markudova, Martino Trevisan, Paolo Garza, Michela Meo
What's my App?: ML-based classification of RTC applications. SIGMETRICS Perform. Evaluation Rev. 48(4): 41-44 (2021) - [j34]Luca Cagliero
Additional Reviewer Assignment by Means of Weighted Association Rules. IEEE Trans. Emerg. Top. Comput. 9(1): 329-341 (2021) - [c55]Luca Cagliero
Cross-lingual timeline summarization. AIKE 2021: 45-53 - [c54]Gianluca Perna, Dena Markudova, Martino Trevisan, Paolo Garza, Michela Meo
Online Classification of RTC Traffic. CCNC 2021: 1-6 - [c53]Simone Monaco, Andrea Pasini, Daniele Apiletti, Luca Colomba, Alessandro Farasin, Paolo Garza, Elena Baralis:
Double-Step deep learning framework to improve wildfire severity classification. EDBT/ICDT Workshops 2021 - [c52]Matteo Corain, Paolo Garza, Abolfazl Asudeh:
DBSCOUT: A Density-based Method for Scalable Outlier Detection in Very Large Datasets. ICDE 2021: 37-48 - [c51]Lorenzo Vaiani, Moreno La Quatra, Luca Cagliero, Paolo Garza:
PoliTO at TREC 2021 Podcast Summarization Track. TREC 2021 - 2020
- [j33]Luca Cagliero
Training ensembles of faceted classification models for quantitative stock trading. Computing 102(5): 1213-1225 (2020) - [j32]Mohammad Reza Kavoosifar, Daniele Apiletti
Effective video hyperlinking by means of enriched feature sets and monomodal query combinations. Int. J. Multim. Inf. Retr. 9(3): 215-227 (2020) - [c50]Simone Monaco
Improving Wildfire Severity Classification of Deep Learning U-Nets from Satellite Images. IEEE BigData 2020: 5786-5788 - [c49]Giuseppe Attanasio, Flavio Giobergia, Andrea Pasini, Francesco Ventura, Elena Baralis, Luca Cagliero
DSLE: A Smart Platform for Designing Data Science Competitions. COMPSAC 2020: 133-142 - [c48]Flavio Giobergia, Luca Cagliero, Paolo Garza, Elena Baralis:
Cross-Lingual Propagation of Sentiment Information Based on Bilingual Vector Space Alignment. EDBT/ICDT Workshops 2020 - [c47]Elena Daraio, Luca Cagliero
An explainable data-driven approach to web directory taxonomy mapping. KES 2020: 1101-1110 - [c46]Jacopo Fior, Luca Cagliero
Price series cross-correlation analysis to enhance the diversification of itemset-based stock portfolios. DSMM@SIGMOD 2020: 1:1-1:6 - [c45]Alessandro Farasin, Francesco Peciarolo, Marco Grangetto, Elena Gianaria, Paolo Garza:
Real-time Object Detection and Tracking in Mixed Reality using Microsoft HoloLens. VISIGRAPP (4: VISAPP) 2020: 165-172
2010 – 2019
- 2019
- [j31]Luca Cagliero
ELSA: A Multilingual Document Summarization Algorithm Based on Frequent Itemsets and Latent Semantic Analysis. ACM Trans. Inf. Syst. 37(2): 21:1-21:33 (2019) - [c44]Luca Cagliero
CarPredictor: Forecasting the Number of Free Floating Car Sharing Vehicles within Restricted Urban Areas. BigData Congress 2019: 72-76 - [c43]Andrea Pasini, Elena Baralis, Paolo Garza, Davide Floriello, Michela Idiomi, Andrea Ortenzi, Simone Ricci:
Adaptive Hierarchical Clustering for Petrographic Image Analysis. EDBT/ICDT Workshops 2019 - [c42]Giuseppe Attanasio, Luca Cagliero
Combining News Sentiment and Technical Analysis to Predict Stock Trend Reversal. ICDM Workshops 2019: 514-521 - [c41]Mirko Zaffaroni, Laura Lopez-Fuentes, Alessandro Farasin, Paolo Garza, Harald Skinnemoen:
AI-Based Flood Event Understanding and Quantifying Using Online Media and Satellite Data. MediaEval 2019 - [c40]Alessandro Farasin, Giovanni Nini, Paolo Garza, Claudio Rossi:
Unsupervised Burned Area Estimation through Satellite Tiles: A Multimodal Approach by Means of Image Segmentation over Remote Sensing Imagery. MACLEAN@PKDD/ECML 2019 - [c39]Giuseppe Attanasio, Luca Cagliero
Quantitative cryptocurrency trading: exploring the use of machine learning techniques. DSMM@SIGMOD 2019: 1:1-1:6 - 2018
- [j30]Luca Cagliero
Characterizing unpredictable patterns in Wireless Sensor Network data. Inf. Sci. 467: 149-162 (2018) - [j29]Luca Cagliero
Discovering cross-topic collaborations among researchers by exploiting weighted association rules. Scientometrics 116(2): 1273-1301 (2018) - [c38]Elena Baralis, Paolo Garza, Eliana Pastor
A Density-based Preprocessing Technique to Scale Out Clustering. IEEE BigData 2018: 2078-2087 - [c37]Luca Cagliero, Paolo Garza:
Study of the Applicability of an Itemset-Based Portfolio Planner in a Multi-Market Context. EDBT/ICDT Workshops 2018: 50-55 - [c36]Alessandro Farasin, Paolo Garza:
PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences. ISCRAM 2018 - [c35]Laura Lopez-Fuentes, Alessandro Farasin, Harald Skinnemoen, Paolo Garza:
Deep Learning Models for Passability Detection of Flooded Roads. MediaEval 2018 - [i1]Luca Venturini, Elena Baralis, Paolo Garza:
Scaling associative classification for very large datasets. CoRR abs/1805.03887 (2018) - 2017
- [j28]Daniele Apiletti
Frequent Itemsets Mining for Big Data: A Comparative Analysis. Big Data Res. 9: 67-83 (2017) - [j27]Daniele Apiletti
A Parallel MapReduce Algorithm to Efficiently Support Itemset Mining on High Dimensional Data. Big Data Res. 10: 53-69 (2017) - [j26]Luca Cagliero
Predicting critical conditions in bicycle sharing systems. Computing 99(1): 39-57 (2017) - [j25]Elena Baralis, Luca Cagliero
Planning stock portfolios by means of weighted frequent itemsets. Expert Syst. Appl. 86: 1-17 (2017) - [j24]Elena Baralis, Luca Cagliero
Discovering profitable stocks for intraday trading. Inf. Sci. 405: 91-106 (2017) - [j23]Luca Venturini
Scaling associative classification for very large datasets. J. Big Data 4: 44 (2017) - [c34]Luca Cagliero
Discovering High-Utility Itemsets at Multiple Abstraction Levels. ADBIS (Short Papers and Workshops) 2017: 224-234 - [c33]Elena Baralis, Andrea Dalla Valle, Paolo Garza, Claudio Rossi
SQL versus NoSQL databases for geospatial applications. IEEE BigData 2017: 3388-3397 - [c32]Luca Cagliero, Paolo Garza, Mohammad Reza Kavoosifar, Elena Baralis:
Identifying Collaborations among Researchers: a pattern-based approach. BIRNDL@SIGIR (1) 2017: 56-68 - [c31]Benoit Huet, Elena Baralis, Paolo Garza, Mohammad Reza Kavoosifar:
Eurecom-Polito at TRECVID 2017: Hyperlinking task. TRECVID 2017 - 2016
- [j22]Devis Bianchini, Paolo Garza
Characterization and search of web services through intensional knowledge. J. Intell. Inf. Syst. 47(3): 375-401 (2016) - [j21]Daniele Apiletti
SeLINA: A Self-Learning Insightful Network Analyzer. IEEE Trans. Netw. Serv. Manag. 13(3): 696-710 (2016) - [c30]Paolo Garza, Elisa Quintarelli
Reducing Big Data by Means of Context-Aware Tailoring. ADBIS (Short Papers and Workshops) 2016: 115-127 - [c29]Luca Venturini, Paolo Garza, Daniele Apiletti:
BAC: A Bagged Associative Classifier for Big Data Frameworks. ADBIS (Short Papers and Workshops) 2016: 137-146 - [c28]Luca Cagliero
Discovering air quality patterns in urban environments. UbiComp Adjunct 2016: 25-28 - [c27]Elena Baralis, Tania Cerquitelli, Silvia Chiusano, Paolo Garza, Mohammad Reza Kavoosifar:
Analyzing air pollution on the urban environment. MIPRO 2016: 1464-1469 - [c26]Daniele Apiletti, Elena Baralis, Tania Cerquitelli, Paolo Garza, Luca Venturini
SaFe-NeC: A scalable and flexible system for network data characterization. NOMS 2016: 812-816 - [c25]Luca Cagliero
Modeling Correlations among Air Pollution-Related Data through Generalized Association Rules. SMARTCOMP 2016: 1-6 - [c24]Benoit Huet, Elena Baralis, Paolo Garza, Mohammad Reza Kavoosifar:
Eurecom-Polito at TRECVID 2016: Hyperlinking Tasks. TRECVID 2016 - 2015
- [j20]Elena Baralis, Luca Cagliero
Digging deep into weighted patient data through multiple-level patterns. Inf. Sci. 322: 51-71 (2015) - [j19]Luca Cagliero
Pattern set mining with schema-based constraint. Knowl. Based Syst. 84: 224-238 (2015) - [j18]Cristiana Bolchini
An Expert CAD Flow for Incremental Functional Diagnosis of Complex Electronic Boards. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 34(5): 835-848 (2015) - [j17]Dario Antonelli
MeTA: Characterization of Medical Treatments at Different Abstraction Levels. ACM Trans. Intell. Syst. Technol. 6(4): 57:1-57:25 (2015) - [j16]Elena Baralis, Luca Cagliero
MWI-Sum: A Multilingual Summarizer Based on Frequent Weighted Itemsets. ACM Trans. Inf. Syst. 34(1): 5:1-5:35 (2015) - [c23]Daniele Apiletti, Paolo Garza
A Review of Scalable Approaches for Frequent Itemset Mining. ADBIS (Short Papers and Workshops) 2015: 243-247 - [c22]Elena Baralis, Luca Cagliero
PaWI: Parallel Weighted Itemset Mining by Means of MapReduce. BigData Congress 2015: 25-32 - [c21]Daniele Apiletti, Elena Baralis, Tania Cerquitelli, Paolo Garza
PaMPa-HD: A Parallel MapReduce-Based Frequent Pattern Miner for High-Dimensional Data. ICDM Workshops 2015: 839-846 - 2014
- [j15]Luca Cagliero
Misleading Generalized Itemset discovery. Expert Syst. Appl. 41(4): 1400-1410 (2014) - [j14]Elena Baralis, Luca Cagliero
Expressive generalized itemsets. Inf. Sci. 278: 327-343 (2014) - [j13]Luca Cagliero
Twitter data analysis by means of Strong Flipping Generalized Itemsets. J. Syst. Softw. 94: 16-29 (2014) - [j12]Luca Cagliero
Infrequent Weighted Itemset Mining Using Frequent Pattern Growth. IEEE Trans. Knowl. Data Eng. 26(4): 903-915 (2014) - [c20]Elena Baralis, Luca Cagliero
Misleading Generalized Itemset Mining in the Cloud. ISPA 2014: 211-216 - [c19]Elena Baralis, Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Luigi Grimaudo, Fabio Pulvirenti, Paolo Garza:
MGI-Cloud: discovery of misleading generalized itemsets. SEBD 2014: 45-52 - [c18]Elena Baralis, Luca Cagliero
NEMICO: Mining Network Data through Cloud-Based Data Mining Techniques. UCC 2014: 503-504 - 2013
- [j11]Luca Cagliero
Improving classification models with taxonomy information. Data Knowl. Eng. 86: 85-101 (2013) - [j10]Luca Cagliero
Itemset generalization with cardinality-based constraints. Inf. Sci. 244: 161-174 (2013) - [j9]Elena Baralis, Luca Cagliero
EnBay: A Novel Pattern-Based Bayesian Classifier. IEEE Trans. Knowl. Data Eng. 25(12): 2780-2795 (2013) - [c17]Paolo Garza, Paolo Margara, Nicolò Nepote, Luigi Grimaudo, Elio Piccolo:
Hadoop on a Low-Budget General Purpose HPC Cluster in Academia. ADBIS (2) 2013: 187-192 - [c16]Elena Baralis, Luca Cagliero
Frequent weighted itemset mining from gene expression data. BIBE 2013: 1-4 - [c15]Cristiana Bolchini
A data mining approach to incremental adaptive functional diagnosis. DFTS 2013: 13-18 - 2012
- [j8]Elena Baralis, Paolo Garza
I-prune: Item selection for associative classification. Int. J. Intell. Syst. 27(3): 279-299 (2012) - [j7]Elena Baralis, Luca Cagliero
Generalized association rule mining with constraints. Inf. Sci. 194: 68-84 (2012) - 2011
- [j6]Luca Cagliero
Semi-Automatic Ontology Construction by Exploiting Functional Dependencies and Association Rules. Int. J. Semantic Web Inf. Syst. 7(2): 1-22 (2011) - [j5]Elena Baralis, Luca Cagliero
CAS-Mine: providing personalized services in context-aware applications by means of generalized rules. Knowl. Inf. Syst. 28(2): 283-310 (2011) - [c14]Paolo Garza
Structured data classification by means of matrix factorization. CIKM 2011: 2165-2168 - 2010
- [j4]Giulia Bruno
TOD: Temporal outlier detection by using quasi-functional temporal dependencies. Data Knowl. Eng. 69(6): 619-639 (2010) - [c13]Elena Baralis, Luca Cagliero
Support driven opportunistic aggregation for generalized itemset extraction. IEEE Conf. of Intelligent Systems 2010: 102-107
2000 – 2009
- 2009
- [c12]Elena Baralis, Luca Cagliero
Context-Aware User and Service Profiling by Means of Generalized Association Rules. KES (2) 2009: 50-57 - [c11]Elena Baralis, Luca Cagliero, Tania Cerquitelli, Paolo Garza, Marco Marchetti:
Generalized Association Rules to Support Context-aware User and Service Profiling. SEBD 2009: 101-108 - 2008
- [j3]Elena Baralis, Silvia Chiusano
A Lazy Approach to Associative Classification. IEEE Trans. Knowl. Data Eng. 20(2): 156-171 (2008) - 2007
- [j2]Giulia Bruno, Paolo Garza, Elisa Quintarelli, Rosalba Rossato:
Anomaly detection through quasi-functional dependency analysis. J. Digit. Inf. Manag. 5(4): 191-200 (2007) - [j1]Elena Baralis, Paolo Garza
Answering XML queries by means of data summaries. ACM Trans. Inf. Syst. 25(3): 10 (2007) - [c10]Giulia Bruno
Anomaly Detection in XML databases by means of Association Rules. DEXA Workshops 2007: 387-391 - [c9]Giulia Bruno, Paolo Garza, Elisa Quintarelli, Rosalba Rossato:
RADAR: Research of Anomalous Data through Association Rules. SEBD 2007: 290-297 - 2006
- [c8]Elena Baralis, Paolo Garza:
Associative text categorization exploiting negated words. SAC 2006: 530-535 - 2005
- [b1]Paolo Garza:
Associative classification algorithms. Polytechnic University of Turin, Italy, 2005 - 2004
- [c7]Elena Baralis, Paolo Garza, Elisa Quintarelli, Letizia Tanca:
Summarizing XML Data by Means of Association Rules. EDBT Workshops 2004: 260-269 - [c6]Elena Baralis, Silvia Chiusano, Paolo Garza:
On support thresholds in associative classification. SAC 2004: 553-558 - [c5]Elena Baralis, Paolo Garza, Elisa Quintarelli, Letizia Tanca:
Answering Queries on XML Data by means of Association Rules. SEBD 2004: 262-269 - 2003
- [c4]Carla-Fabiana Chiasserini
Towards Feasible Topology Formation Algorithms for Bluetooth-based WPANs. HICSS 2003: 313 - [c3]Elena Baralis, Paolo Garza:
Majority Classification by Means of Association Rules. PKDD 2003: 35-46 - 2002
- [c2]Elena Baralis, Paolo Garza:
A Lazy Approach to Pruning Classification Rules. ICDM 2002: 35-42 - [c1]Elena Baralis, Paolo Garza:
Accurate Classification by means of Association Rules. SEBD 2002: 273-280
Coauthor Index
[c70] [i8] [i5] [c62] [c59] [c58] [d1] [j34] [c55] [c53] [j33] [j32] [c50] [c49] [c48] [j31] [c43] [c42] [c39] [j29] [c38] [i1] [j28] [j27] [j25] [j24] [j23] [c33] [c32] [c31] [j21] [c27] [c26] [c24] [j20] [j17] [j16] [c22] [c21] [j14] [c20] [c19] [c18] [j9] [c16] [j8] [j7] [j5] [c13] [c12] [c11] [j3] [j1] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
[j42] [c74] [c72] [c71] [c70] [i13] [i10] [i8] [i3] [j41] [j40] [c63] [j38] [j37] [c61] [c60] [c59] [c58] [c56] [j34] [c55] [c51] [j33] [c49] [c48] [c47] [c46] [j31] [c44] [c42] [c39] [j30] [j29] [c37] [j26] [j25] [j24] [c34] [c32] [c28] [c25] [j20] [j19] [j17] [j16] [c22] [j15] [j14] [j13] [j12] [c20] [c19] [c18] [j11] [j10] [j9] [c16] [j7] [j6] [j5] [c13] [c12] [c11]
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