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CAdam: Confidence-Based Optimization for Online Learning
v1v2 (latest)

CAdam: Confidence-Based Optimization for Online Learning

29 November 2024
Shaowen Wang
Anan Liu
Jian Xiao
Huan Liu
Yuekui Yang
Cong Xu
Qianqian Pu
Suncong Zheng
Wei-Qiang Zhang
Di Wang
Jie Jiang
Jian Li
Author Contacts:
wangsw23@mails.tsinghua.edu.cnlijian83@mail.tsinghua.edu.cn
ArXiv (abs)PDFHTML

Papers citing "CAdam: Confidence-Based Optimization for Online Learning"

31 / 31 papers shown
Title
Cautious Optimizers: Improving Training with One Line of Code
Cautious Optimizers: Improving Training with One Line of Code
Kaizhao Liang
Lizhang Chen
B. Liu
Qiang Liu
ODL
195
9
0
25 Nov 2024
On the Convergence of Adam under Non-uniform Smoothness: Separability
  from SGDM and Beyond
On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond
Bohan Wang
Huishuai Zhang
Qi Meng
Ruoyu Sun
Zhi-Ming Ma
Wei Chen
66
11
0
22 Mar 2024
Closing the Gap Between the Upper Bound and the Lower Bound of Adam's
  Iteration Complexity
Closing the Gap Between the Upper Bound and the Lower Bound of Adam's Iteration Complexity
Bohan Wang
Jingwen Fu
Huishuai Zhang
Nanning Zheng
Wei Chen
49
19
0
27 Oct 2023
A Gradient-based Approach for Online Robust Deep Neural Network Training
  with Noisy Labels
A Gradient-based Approach for Online Robust Deep Neural Network Training with Noisy Labels
Yifan Yang
Alec Koppel
Zheng Zhang
NoLa
53
3
0
08 Jun 2023
Convergence of Adam Under Relaxed Assumptions
Convergence of Adam Under Relaxed Assumptions
Haochuan Li
Alexander Rakhlin
Ali Jadbabaie
80
65
0
27 Apr 2023
Symbolic Discovery of Optimization Algorithms
Symbolic Discovery of Optimization Algorithms
Xiangning Chen
Chen Liang
Da Huang
Esteban Real
Kaiyuan Wang
...
Xuanyi Dong
Thang Luong
Cho-Jui Hsieh
Yifeng Lu
Quoc V. Le
152
374
0
13 Feb 2023
Adam Can Converge Without Any Modification On Update Rules
Adam Can Converge Without Any Modification On Update Rules
Yushun Zhang
Congliang Chen
Naichen Shi
Ruoyu Sun
Zhimin Luo
51
68
0
20 Aug 2022
Adaptive Online Incremental Learning for Evolving Data Streams
Adaptive Online Incremental Learning for Evolving Data Streams
Siyun Zhang
Jian-wei Liu
Xin Zuo
CLL
51
30
0
05 Jan 2022
Learning Robust Recommender from Noisy Implicit Feedback
Learning Robust Recommender from Noisy Implicit Feedback
Wenjie Wang
Fuli Feng
Xiangnan He
Liqiang Nie
Tat-Seng Chua
NoLa
62
3
0
02 Dec 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
657
41,103
0
22 Oct 2020
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed
  Gradients
AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients
Juntang Zhuang
Tommy M. Tang
Yifan Ding
S. Tatikonda
Nicha Dvornek
X. Papademetris
James S. Duncan
ODL
165
517
0
15 Oct 2020
BARS-CTR: Open Benchmarking for Click-Through Rate Prediction
BARS-CTR: Open Benchmarking for Click-Through Rate Prediction
Jieming Zhu
Jinyang Liu
Shuai Yang
Qi Zhang
Xiuqiang He
71
129
0
12 Sep 2020
Online Robust and Adaptive Learning from Data Streams
Online Robust and Adaptive Learning from Data Streams
Shintaro Fukushima
Atsushi Nitanda
Kenji Yamanishi
59
3
0
23 Jul 2020
Learning under Concept Drift: A Review
Learning under Concept Drift: A Review
Jie Lu
Anjin Liu
Fan Dong
Feng Gu
João Gama
Guangquan Zhang
AI4TS
65
1,282
0
13 Apr 2020
A new regret analysis for Adam-type algorithms
A new regret analysis for Adam-type algorithms
Ahmet Alacaoglu
Yura Malitsky
P. Mertikopoulos
Volkan Cevher
ODL
60
42
0
21 Mar 2020
A Simple Convergence Proof of Adam and Adagrad
A Simple Convergence Proof of Adam and Adagrad
Alexandre Défossez
Léon Bottou
Francis R. Bach
Nicolas Usunier
112
155
0
05 Mar 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
520
42,449
0
03 Dec 2019
On the Variance of the Adaptive Learning Rate and Beyond
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu
Haoming Jiang
Pengcheng He
Weizhu Chen
Xiaodong Liu
Jianfeng Gao
Jiawei Han
ODL
287
1,905
0
08 Aug 2019
On the Convergence of Adam and Beyond
On the Convergence of Adam and Beyond
Sashank J. Reddi
Satyen Kale
Surinder Kumar
99
2,499
0
19 Apr 2019
Robust Loss Functions under Label Noise for Deep Neural Networks
Robust Loss Functions under Label Noise for Deep Neural Networks
Aritra Ghosh
Himanshu Kumar
P. Sastry
NoLaOOD
70
957
0
27 Dec 2017
Deep & Cross Network for Ad Click Predictions
Deep & Cross Network for Ad Click Predictions
Ruoxi Wang
Bin Fu
Gang Fu
Mingliang Wang
104
1,233
0
17 Aug 2017
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
517
19,065
0
20 Jul 2017
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
707
131,652
0
12 Jun 2017
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
Huifeng Guo
Ruiming Tang
Yunming Ye
Zhenguo Li
Xiuqiang He
120
2,650
0
13 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
823
11,909
0
09 Mar 2017
Product-based Neural Networks for User Response Prediction
Product-based Neural Networks for User Response Prediction
Yanru Qu
Han Cai
Kan Ren
Weinan Zhang
Yong Yu
Ying Wen
Jun Wang
86
716
0
01 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
775
36,813
0
25 Aug 2016
Wide & Deep Learning for Recommender Systems
Wide & Deep Learning for Recommender Systems
Heng-Tze Cheng
L. Koc
Jeremiah Harmsen
T. Shaked
Tushar Chandra
...
Zakaria Haque
Lichan Hong
Vihan Jain
Xiaobing Liu
Hemal Shah
HAIVLM
179
3,659
0
24 Jun 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,386
0
04 Sep 2014
ADADELTA: An Adaptive Learning Rate Method
ADADELTA: An Adaptive Learning Rate Method
Matthew D. Zeiler
ODL
155
6,625
0
22 Dec 2012
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