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Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
28 August 2023
Samuel Horváth
Stefanos Laskaridis
Shashank Rajput
Hongyi Wang
BDL
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Papers citing
"Maestro: Uncovering Low-Rank Structures via Trainable Decomposition"
10 / 10 papers shown
Title
Forget the Data and Fine-Tuning! Just Fold the Network to Compress
Dong Wang
Haris Šikić
Lothar Thiele
O. Saukh
42
0
0
17 Feb 2025
FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training
Philip Zmushko
Aleksandr Beznosikov
Martin Takáč
Samuel Horváth
32
0
0
12 Nov 2024
MELTing point: Mobile Evaluation of Language Transformers
Stefanos Laskaridis
Kleomenis Katevas
Lorenzo Minto
Hamed Haddadi
19
4
0
19 Mar 2024
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics
Soo Min Kwon
Zekai Zhang
Dogyoon Song
Laura Balzano
Qing Qu
25
2
0
08 Nov 2023
Cuttlefish: Low-Rank Model Training without All the Tuning
Hongyi Wang
Saurabh Agarwal
Pongsakorn U-chupala
Yoshiki Tanaka
Eric P. Xing
Dimitris Papailiopoulos
OffRL
39
21
0
04 May 2023
Efficient and Private Federated Learning with Partially Trainable Networks
Hakim Sidahmed
Zheng Xu
Ankush Garg
Yuan Cao
Mingqing Chen
FedML
34
13
0
06 Oct 2021
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild
Mario Almeida
Stefanos Laskaridis
Abhinav Mehrotra
L. Dudziak
Ilias Leontiadis
Nicholas D. Lane
HAI
91
41
0
28 Sep 2021
Initialization and Regularization of Factorized Neural Layers
M. Khodak
Neil A. Tenenholtz
Lester W. Mackey
Nicolò Fusi
63
56
0
03 May 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout
Samuel Horváth
Stefanos Laskaridis
Mario Almeida
Ilias Leondiadis
Stylianos I. Venieris
Nicholas D. Lane
162
206
0
26 Feb 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
948
20,214
0
17 Apr 2017
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