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ORCIDGiovanni Motta
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2020 – today
- 2023
[c30]Lillian Zhou, Yuxin Ding, Mingqing Chen, Harry Zhang, Rohit Prabhavalkar, Dhruv Guliani, Giovanni Motta, Rajiv Mathews:
The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections Through Federated Learning. ASRU 2023: 1-7- [c29]Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen:
Online Model Compression for Federated Learning with Large Models. ICASSP 2023: 1-5 - [i9]Lillian Zhou, Yuxin Ding, Mingqing Chen, Harry Zhang, Rohit Prabhavalkar, Dhruv Guliani, Giovanni Motta, Rajiv Mathews:
The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections through Federated Learning. CoRR abs/2310.00141 (2023) - 2022
- [c28]Lillian Zhou, Dhruv Guliani, Andreas Kabel, Giovanni Motta, Françoise Beaufays:
Exploring Heterogeneous Characteristics of Layers in ASR Models for More Efficient Training. ICASSP 2022: 3658-3662 - [c27]Tien-Ju Yang, Dhruv Guliani, Françoise Beaufays, Giovanni Motta:
Partial Variable Training for Efficient on-Device Federated Learning. ICASSP 2022: 4348-4352 - [c26]Dhruv Guliani, Lillian Zhou, Changwan Ryu, Tien-Ju Yang, Harry Zhang, Yonghui Xiao, Françoise Beaufays, Giovanni Motta:
Enabling On-Device Training of Speech Recognition Models With Federated Dropout. ICASSP 2022: 8757-8761 - [c25]Rongmei Lin, Yonghui Xiao, Tien-Ju Yang, Ding Zhao, Li Xiong, Giovanni Motta, Françoise Beaufays:
Federated Pruning: Improving Neural Network Efficiency with Federated Learning. INTERSPEECH 2022: 1701-1705 - [i8]Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Françoise Beaufays, Rajiv Mathews, Mingqing Chen:
Online Model Compression for Federated Learning with Large Models. CoRR abs/2205.03494 (2022) - [i7]Rongmei Lin, Yonghui Xiao, Tien-Ju Yang, Ding Zhao, Li Xiong, Giovanni Motta, Françoise Beaufays:
Federated Pruning: Improving Neural Network Efficiency with Federated Learning. CoRR abs/2209.06359 (2022) - 2021
- [c24]Dhruv Guliani, Françoise Beaufays, Giovanni Motta:
Training Speech Recognition Models with Federated Learning: A Quality/Cost Framework. ICASSP 2021: 3080-3084 - [i6]Dhruv Guliani, Lillian Zhou, Changwan Ryu, Tien-Ju Yang, Harry Zhang, Yonghui Xiao, Françoise Beaufays, Giovanni Motta:
Enabling On-Device Training of Speech Recognition Models with Federated Dropout. CoRR abs/2110.03634 (2021) - [i5]Lillian Zhou, Dhruv Guliani, Andreas Kabel, Giovanni Motta, Françoise Beaufays:
Exploring Heterogeneous Characteristics of Layers in ASR Models for More Efficient Training. CoRR abs/2110.04267 (2021) - [i4]Tien-Ju Yang, Dhruv Guliani, Françoise Beaufays, Giovanni Motta:
Partial Variable Training for Efficient On-Device Federated Learning. CoRR abs/2110.05607 (2021) - 2020
- [c23]Mary Gooneratne, Khe Chai Sim, Petr Zadrazil, Andreas Kabel, Françoise Beaufays, Giovanni Motta:
Low-Rank Gradient Approximation for Memory-Efficient on-Device Training of Deep Neural Network. ICASSP 2020: 3017-3021 - [i3]Mary Gooneratne, Khe Chai Sim, Petr Zadrazil, Andreas Kabel, Françoise Beaufays, Giovanni Motta:
Low-rank Gradient Approximation For Memory-Efficient On-device Training of Deep Neural Network. CoRR abs/2001.08885 (2020) - [i2]Dhruv Guliani, Françoise Beaufays, Giovanni Motta:
Training Speech Recognition Models with Federated Learning: A Quality/Cost Framework. CoRR abs/2010.15965 (2020)
2010 – 2019
- 2019
- [c22]Khe Chai Sim, Leif Johnson, Giovanni Motta, Lillian Zhou, Françoise Beaufays, Arnaud Benard, Dhruv Guliani, Andreas Kabel, Nikhil Khare, Tamar Lucassen, Petr Zadrazil, Harry Zhang:
Personalization of End-to-End Speech Recognition on Mobile Devices for Named Entities. ASRU 2019: 23-30 - [i1]Khe Chai Sim, Françoise Beaufays, Arnaud Benard, Dhruv Guliani, Andreas Kabel, Nikhil Khare, Tamar Lucassen, Petr Zadrazil, Harry Zhang, Leif Johnson, Giovanni Motta, Lillian Zhou:
Personalization of End-to-end Speech Recognition On Mobile Devices For Named Entities. CoRR abs/1912.09251 (2019) - 2018
- [j6]Jiannong Cao, Aniello Castiglione
, Giovanni Motta, Florin Pop, Yanjiang Yang, Wanlei Zhou:
Human-Driven Edge Computing and Communication: Part 2. IEEE Commun. Mag. 56(2): 134-135 (2018) - 2017
- [j5]Jiannong Cao, Aniello Castiglione, Giovanni Motta, Florin Pop, Yanjiang Yang, Wanlei Zhou:
Human-Driven Edge Computing and Communication: Part 1. IEEE Commun. Mag. 55(11): 70-71 (2017) - 2012
- [j4]Antonella Di Lillo, Ajay H. Daptardar, Kevin Thomas, James A. Storer, Giovanni Motta:
Compression-Based Tools for Navigation with an Image Database. Algorithms 5(1): 1-17 (2012) - 2011
- [j3]Giovanni Motta, Erik Ordentlich, Ignacio Ramírez, Gadiel Seroussi, Marcelo J. Weinberger:
The iDUDE Framework for Grayscale Image Denoising. IEEE Trans. Image Process. 20(1): 1-21 (2011) - [c21]Antonella Di Lillo, Ajay H. Daptardar, Kevin Thomas, James A. Storer, Giovanni Motta:
Applications of Compression to Content Based Image Retrieval and Object Recognition. CCP 2011: 179-189 - 2010
- [b1]David Salomon, Giovanni Motta:
Handbook of Data Compression (5. ed.). Springer 2010, ISBN 978-1-84882-902-2, pp. I-XXII, 1-1359 - [c20]Yan Ye, Giovanni Motta, Marta Karczewicz:
Enhanced Adaptive Interpolation Filters for Video Coding. DCC 2010: 435-444 - [c19]Antonella Di Lillo, Giovanni Motta, James A. Storer:
Shape Recognition Using Vector Quantization. DCC 2010: 484-493 - [c18]Antonella Di Lillo, Giovanni Motta, James A. Storer:
A rotation and scale invariant descriptor for shape recognition. ICIP 2010: 257-260 - [c17]Antonella Di Lillo, Giovanni Motta, Kevin Thomas, James A. Storer:
Shape recognition, with applications to a passive assistant. PETRA 2010
2000 – 2009
- 2008
- [c16]Giovanni Motta, Erik Ordentlich, Marcelo J. Weinberger:
Defect List Compression. DCC 2008: 3-12 - [c15]Antonella Di Lillo, Giovanni Motta, James A. Storer:
Multiresolution Rotation-Invariant Texture Classification Using Feature Extraction in the Frequency Domain and Vector Quantization. DCC 2008: 452-461 - [c14]Giovanni Motta, Erik Ordentlich, Marcelo J. Weinberger:
Defect list compression. ISIT 2008: 1000-1004 - 2007
- [c13]Giovanni Motta, James Gustafson, Samson Chen:
Differential Compression of Executable Code. DCC 2007: 103-112 - [c12]Antonella Di Lillo, James A. Storer, Giovanni Motta:
Texture Classification Using VQ with Feature Extraction based on Transforms Motivated by the Human Visual System. DCC 2007: 392 - [c11]Antonella Di Lillo, Giovanni Motta, James A. Storer:
Supervised Segmentation Based on Texture Signatures Extracted in the Frequency Domain. IbPRIA (1) 2007: 89-96 - [c10]Antonella Di Lillo, Giovanni Motta, James A. Storer:
Texture Classification Based on Discriminative Features Extracted in the Frequency Domain. ICIP (2) 2007: 53-56 - 2006
- [p2]Francesco Rizzo, Bruno Carpentieri, Giovanni Motta, James A. Storer:
Compression of hyperspectral imagery via linear prediction. e-Business and Telecommunication Networks 2006: 284-291 - [p1]Giovanni Motta, Francesco Rizzo, James A. Storer:
Locally Optimal Partitioned Vector Quantization of Hyperspectral Data. Hyperspectral Data Compression 2006: 107-146 - [e1]Giovanni Motta, Francesco Rizzo, James A. Storer:
Hyperspectral Data Compression. Springer 2006, ISBN 978-0-387-28579-5 [contents] - 2005
- [j2]Francesco Rizzo, Bruno Carpentieri, Giovanni Motta, James A. Storer:
Low-complexity lossless compression of hyperspectral imagery via linear prediction. IEEE Signal Process. Lett. 12(2): 138-141 (2005) - [c9]Gadiel Seroussi, Giovanni Motta, Erik Ordentlich, Ignacio Ramírez, Marcelo J. Weinberger:
The DUDE framework for continuous tone image denoising. ICIP (3) 2005: 345-348 - 2004
- [c8]Francesco Rizzo, Bruno Carpentieri, Giovanni Motta, James A. Storer:
High Performance Compression of Hyperspectral Imagery with Reduced Search Complexity in the Compressed Domain. Data Compression Conference 2004: 479-488 - [c7]Bruno Carpentieri, James A. Storer, Giovanni Motta, Francesco Rizzo:
Compression of Hyperspectral Imagery. ICETE (3) 2004: 317-324 - 2003
- [c6]Giovanni Motta, Francesco Rizzo, James A. Storer:
Compression of Hyperspectral Imagery. DCC 2003: 333-342 - [c5]Giovanni Motta, Francesco Rizzo, James A. Storer:
Partitioned vector quantization: application to lossless compression of hyperspectral images. ICASSP (3) 2003: 241-244 - [c4]Giovanni Motta, Francesco Rizzo, James A. Storer:
Partitioned vector quantization: application to lossless compression of hyperspectral images. ICME 2003: 553-556 - 2000
- [j1]Giovanni Motta, James A. Storer, Bruno Carpentieri:
Lossless image coding via adaptive linear prediction and classification. Proc. IEEE 88(11): 1790-1796 (2000) - [c3]Giovanni Motta, James A. Storer, Bruno Carpentieri:
Improving Scene Cut Quality for Real-Time Video Decoding. Data Compression Conference 2000: 470-479
1990 – 1999
- 1999
- [c2]Giovanni Motta, James A. Storer, Bruno Carpentieri:
Adaptive Linear Prediction Lossless Image Coding. Data Compression Conference 1999: 491-500 - 1997
- [c1]Giovanni Motta, Bruno Carpentieri:
A new trellis vector residual quantizer: applications to image coding. ICASSP 1997: 2929-2931
Coauthor Index
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