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An Exploration of Softmax Alternatives Belonging to the Spherical Loss
  Family

An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family

16 November 2015
A. D. Brébisson
Pascal Vincent
ArXivPDFHTML

Papers citing "An Exploration of Softmax Alternatives Belonging to the Spherical Loss Family"

19 / 19 papers shown
Title
Building a stable classifier with the inflated argmax
Building a stable classifier with the inflated argmax
Jake A. Soloff
Rina Foygel Barber
Rebecca Willett
144
2
0
22 May 2024
An extended asymmetric sigmoid with Perceptron (SIGTRON) for imbalanced
  linear classification
An extended asymmetric sigmoid with Perceptron (SIGTRON) for imbalanced linear classification
Hyenkyun Woo
20
0
0
26 Dec 2023
A Large Deviations Perspective on Policy Gradient Algorithms
A Large Deviations Perspective on Policy Gradient Algorithms
Wouter Jongeneel
Daniel Kuhn
Mengmeng Li
31
1
0
13 Nov 2023
Classified as unknown: A novel Bayesian neural network
Classified as unknown: A novel Bayesian neural network
Tianbo Yang
Tianshuo Yang
BDL
UQCV
10
0
0
31 Jan 2023
On the Lipschitz Constant of Deep Networks and Double Descent
On the Lipschitz Constant of Deep Networks and Double Descent
Matteo Gamba
Hossein Azizpour
Mårten Björkman
33
7
0
28 Jan 2023
Universal Spam Detection using Transfer Learning of BERT Model
Universal Spam Detection using Transfer Learning of BERT Model
Vijay Srinivas Tida
Sonya Hsu
25
47
0
07 Feb 2022
Sparse-softmax: A Simpler and Faster Alternative Softmax Transformation
Sparse-softmax: A Simpler and Faster Alternative Softmax Transformation
Shaoshi Sun
Zhenyuan Zhang
B. Huang
Pengbin Lei
Jianlin Su
Shengfeng Pan
Jiarun Cao
UQCV
13
7
0
23 Dec 2021
Escaping the Gradient Vanishing: Periodic Alternatives of Softmax in
  Attention Mechanism
Escaping the Gradient Vanishing: Periodic Alternatives of Softmax in Attention Mechanism
Shulun Wang
Bin Liu
Feng Liu
25
16
0
16 Aug 2021
von Mises-Fisher Loss: An Exploration of Embedding Geometries for
  Supervised Learning
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning
Tyler R. Scott
Andrew C. Gallagher
Michael C. Mozer
27
39
0
29 Mar 2021
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at
  Reliable OOD Detection
Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection
Dennis Ulmer
Giovanni Cina
OODD
35
31
0
09 Dec 2020
Exploring Alternatives to Softmax Function
Exploring Alternatives to Softmax Function
K. Banerjee
Vishak C.
R. Gupta
Kartik Vyas
Anushree H.
Biswajit Mishra
11
49
0
23 Nov 2020
Optimal Approximation -- Smoothness Tradeoffs for Soft-Max Functions
Optimal Approximation -- Smoothness Tradeoffs for Soft-Max Functions
Alessandro Epasto
Mohammad Mahdian
Vahab Mirrokni
Manolis Zampetakis
23
15
0
22 Oct 2020
Hyperspectral Classification Based on 3D Asymmetric Inception Network
  with Data Fusion Transfer Learning
Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning
Haokui Zhang
Yu Liu
Bei Fang
Ying Li
Lingqiao Liu
Ian Reid
3DPC
13
9
0
11 Feb 2020
Secure Evaluation of Quantized Neural Networks
Secure Evaluation of Quantized Neural Networks
Anders Dalskov
Daniel E. Escudero
Marcel Keller
17
137
0
28 Oct 2019
Sampled Softmax with Random Fourier Features
Sampled Softmax with Random Fourier Features
A. S. Rawat
Jiecao Chen
Felix X. Yu
A. Suresh
Sanjiv Kumar
39
55
0
24 Jul 2019
Von Mises-Fisher Loss for Training Sequence to Sequence Models with
  Continuous Outputs
Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs
Sachin Kumar
Yulia Tsvetkov
22
70
0
10 Dec 2018
Mad Max: Affine Spline Insights into Deep Learning
Mad Max: Affine Spline Insights into Deep Learning
Randall Balestriero
Richard Baraniuk
AI4CE
31
78
0
17 May 2018
Simultaneous Learning of Trees and Representations for Extreme
  Classification and Density Estimation
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite
A. Choromańska
David Sontag
25
35
0
14 Oct 2016
The Z-loss: a shift and scale invariant classification loss belonging to
  the Spherical Family
The Z-loss: a shift and scale invariant classification loss belonging to the Spherical Family
A. D. Brébisson
Pascal Vincent
17
10
0
29 Apr 2016
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