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Azzalini, Davide
32  results:
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1

A Transfer Learning Approach for Remaining Useful Life Esti..:

, In: 2024 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0 & IoT),
Martiri, Luca ; Azzalini, Davide ; Cristaldi, Loredana. - p. 557-561 , 2024
Link: https://doi.org/10.1109/..
 
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2

Adversarial Data Augmentation for HMM-Based Anomaly Detecti..:

Castellini, Alberto ; Masillo, Francesco ; Azzalini, Davide..
IEEE Transactions on Pattern Analysis and Machine Intelligence.  45 (2023)  12 - p. 14131-14143 , 2023
Link: https://doi.org/10.1109/..
 
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3

Improving Remaining Useful Life Estimation of Lithium-Ion B..:

, In: 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE),
Martiri, Luca ; Azzalini, Davide ; Flammini, Benedetta.. - p. 317-322 , 2023
Link: https://doi.org/10.1109/..
 
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4

SoCRATe: A Recommendation System with Limited-Availability ..:

, In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management,
Azzalini, Davide ; Azzalini, Fabio ; Criscuolo, Chiara... - p. 4793-4797 , 2022
Link: https://dl.acm.org/doi/1..
 
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5

FARGO: A Fair, Context-AwaRe, Group RecOmmender System:

, In: Communications in Computer and Information Science; Advances in Bias and Fairness in Information Retrieval,
Azzalini, Davide ; Quintarelli, Elisa ; Rabosio, Emanuele. - p. 143-154 , 2022
Link: https://doi.org/10.1007/..
 
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6

Modeling and Comparing Robot Behaviors for Anomaly Detectio:

, In: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems,
Azzalini, Davide - p. 2171-2173 , 2020
Link: https://dl.acm.org/doi/1..
 
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7

HMMs for Anomaly Detection in Autonomous Robots:

, In: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems,
Azzalini, Davide ; Castellini, Alberto ; Luperto, Matteo.. - p. 105-113 , 2020
Link: https://dl.acm.org/doi/1..
 
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8

Tracking the Evolution of Financial Time Series Clusters:

, In: Proceedings of the 5th Workshop on Data Science for Macro-modeling with Financial and Economic Datasets,
Azzalini, Davide ; Azzalini, Fabio ; Mazuran, Mirjana. - p. 1-5 , 2019
Link: https://dl.acm.org/doi/1..
 
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9

Tracking the Evolution of Financial Time Series Clusters:

Tanca, Letizia ; Azzalini, Davide ; Azzalini, Fabio.
hal-02191810.  , 2019
Link: https://inria.hal.scienc..
 
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10

Evolution of Financial Time Series Clusters (Discussion Pap..:

Azzalini, Davide ; Azzalini, Fabio ; Mazuran, Mirjana.
hal-02191794.  , 2019
Link: https://hal.inria.fr/hal..
 
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11

Evolution of Financial Time Series Clusters (Discussion Pap..:

Azzalini, Davide ; Azzalini, Fabio ; Mazuran, Mirjana.
hal-02191794.  , 2019
Link: https://inria.hal.scienc..
 
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12

Tracking the Evolution of Financial Time Series Clusters:

Tanca, Letizia ; Azzalini, Davide ; Azzalini, Fabio.
hal-02191810.  , 2019
Link: https://hal.inria.fr/hal..
 
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13

Tracking the Evolution of Financial Time Series Clusters:

Tanca, Letizia ; Azzalini, Davide ; Azzalini, Fabio.
hal-02191810.  , 2019
Link: https://inria.hal.scienc..
 
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14

Evolution of Financial Time Series Clusters (Discussion Pap..:

Azzalini, Davide ; Azzalini, Fabio ; Mazuran, Mirjana.
hal-02191794.  , 2019
Link: https://inria.hal.scienc..
 
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15

Tracking the Evolution of Financial Time Series Clusters:

Tanca, Letizia ; Azzalini, Davide ; Azzalini, Fabio.
hal-02191810.  , 2019
Link: https://inria.hal.scienc..
 
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