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Gradients as Features for Deep Representation Learning

Gradients as Features for Deep Representation Learning

12 April 2020
Fangzhou Mu
Yingyu Liang
Yin Li
    OOD
ArXivPDFHTML

Papers citing "Gradients as Features for Deep Representation Learning"

15 / 15 papers shown
Title
Solving Token Gradient Conflict in Mixture-of-Experts for Large Vision-Language Model
Solving Token Gradient Conflict in Mixture-of-Experts for Large Vision-Language Model
Longrong Yang
Dong Shen
Chaoxiang Cai
Fan Yang
Size Li
Di Zhang
Xi Li
MoE
56
2
0
28 Jun 2024
Fine-tuning with Very Large Dropout
Fine-tuning with Very Large Dropout
Jianyu Zhang
Léon Bottou
46
1
0
01 Mar 2024
Differentially Private Image Classification by Learning Priors from
  Random Processes
Differentially Private Image Classification by Learning Priors from Random Processes
Xinyu Tang
Ashwinee Panda
Vikash Sehwag
Prateek Mittal
23
20
0
08 Jun 2023
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained
  Models
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
Guillermo Ortiz-Jiménez
Alessandro Favero
P. Frossard
MoMe
51
112
0
22 May 2023
Head2Toe: Utilizing Intermediate Representations for Better Transfer
  Learning
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning
Utku Evci
Vincent Dumoulin
Hugo Larochelle
Michael C. Mozer
30
83
0
10 Jan 2022
Deep Active Learning by Leveraging Training Dynamics
Deep Active Learning by Leveraging Training Dynamics
Haonan Wang
Wei Huang
Ziwei Wu
A. Margenot
Hanghang Tong
Jingrui He
AI4CE
27
33
0
16 Oct 2021
Unsupervised Shape Completion via Deep Prior in the Neural Tangent
  Kernel Perspective
Unsupervised Shape Completion via Deep Prior in the Neural Tangent Kernel Perspective
Lei Chu
Hao Pan
Wenping Wang
3DPC
34
11
0
19 Apr 2021
Fast Adaptation with Linearized Neural Networks
Fast Adaptation with Linearized Neural Networks
Wesley J. Maddox
Shuai Tang
Pablo G. Moreno
A. Wilson
Andreas C. Damianou
32
32
0
02 Mar 2021
A linearized framework and a new benchmark for model selection for
  fine-tuning
A linearized framework and a new benchmark for model selection for fine-tuning
Aditya Deshpande
Alessandro Achille
Avinash Ravichandran
Hao Li
L. Zancato
Charless C. Fowlkes
Rahul Bhotika
Stefano Soatto
Pietro Perona
ALM
118
46
0
29 Jan 2021
Estimating informativeness of samples with Smooth Unique Information
Estimating informativeness of samples with Smooth Unique Information
Hrayr Harutyunyan
Alessandro Achille
Giovanni Paolini
Orchid Majumder
Avinash Ravichandran
Rahul Bhotika
Stefano Soatto
27
24
0
17 Jan 2021
Mixed-Privacy Forgetting in Deep Networks
Mixed-Privacy Forgetting in Deep Networks
Aditya Golatkar
Alessandro Achille
Avinash Ravichandran
M. Polito
Stefano Soatto
CLL
MU
130
160
0
24 Dec 2020
LQF: Linear Quadratic Fine-Tuning
LQF: Linear Quadratic Fine-Tuning
Alessandro Achille
Aditya Golatkar
Avinash Ravichandran
M. Polito
Stefano Soatto
29
27
0
21 Dec 2020
Faster Non-Convex Federated Learning via Global and Local Momentum
Faster Non-Convex Federated Learning via Global and Local Momentum
Rudrajit Das
Anish Acharya
Abolfazl Hashemi
Sujay Sanghavi
Inderjit S. Dhillon
Ufuk Topcu
FedML
40
82
0
07 Dec 2020
Predicting Training Time Without Training
Predicting Training Time Without Training
L. Zancato
Alessandro Achille
Avinash Ravichandran
Rahul Bhotika
Stefano Soatto
26
24
0
28 Aug 2020
Backpropagated Gradient Representations for Anomaly Detection
Backpropagated Gradient Representations for Anomaly Detection
Gukyeong Kwon
Mohit Prabhushankar
Dogancan Temel
Ghassan AlRegib
30
71
0
18 Jul 2020
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