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Increasing biases can be more efficient than increasing weights

Increasing biases can be more efficient than increasing weights

3 January 2023
C. Metta
M. Fantozzi
Andrea Papini
G. Amato
Matteo Bergamaschi
S. Galfrè
Alessandro Marchetti
Michelangelo Vegliò
Maurizio Parton
F. Morandin
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Papers citing "Increasing biases can be more efficient than increasing weights"

6 / 6 papers shown
Title
Achieving Predictive Precision: Leveraging LSTM and Pseudo Labeling for
  Volvo's Discovery Challenge at ECML-PKDD 2024
Achieving Predictive Precision: Leveraging LSTM and Pseudo Labeling for Volvo's Discovery Challenge at ECML-PKDD 2024
C. Metta
Marco Gregnanin
Andrea Papini
S. Galfrè
Andrea Fois
F. Morandin
M. Fantozzi
Maurizio Parton
18
0
0
20 Sep 2024
Volvo Discovery Challenge at ECML-PKDD 2024
Volvo Discovery Challenge at ECML-PKDD 2024
M. Rahat
Peyman Sheikholharam Mashhadi
Sławomir Nowaczyk
Shamik Choudhury
Leo Petrin
Thorsteinn Rognvaldsson
Andreas Voskou
Carlo Metta
Claudio Savelli
23
1
0
17 Sep 2024
A Systematization of the Wagner Framework: Graph Theory Conjectures and
  Reinforcement Learning
A Systematization of the Wagner Framework: Graph Theory Conjectures and Reinforcement Learning
Flora Angileri
Giulia Lombardi
Andrea Fois
Renato Faraone
C. Metta
...
M. Fantozzi
S. Galfrè
Daniele Pavesi
Maurizio Parton
F. Morandin
24
2
0
18 Jun 2024
GloNets: Globally Connected Neural Networks
GloNets: Globally Connected Neural Networks
Antonio Di Cecco
C. Metta
M. Fantozzi
F. Morandin
Maurizio Parton
19
2
0
27 Nov 2023
Score vs. Winrate in Score-Based Games: which Reward for Reinforcement
  Learning?
Score vs. Winrate in Score-Based Games: which Reward for Reinforcement Learning?
Luca Pasqualini
G. Amato
Maurizio Parton
R. Gini
Alessandro Marchetti
C. Metta
F. Morandin
M. Fantozzi
17
2
0
31 Jan 2022
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable Convolutions
François Chollet
MDE
BDL
PINN
206
14,368
0
07 Oct 2016
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