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MODL: Multilearner Online Deep Learning
v1v2 (latest)

MODL: Multilearner Online Deep Learning

28 May 2024
Antonios Valkanas
Boris N. Oreshkin
Mark Coates
ArXiv (abs)PDFHTML

Papers citing "MODL: Multilearner Online Deep Learning"

26 / 26 papers shown
Title
Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes
Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes
Daniel Waxman
Fernando Llorente
Petar M. Djurić
211
0
0
21 May 2025
DSAM: A Deep Learning Framework for Analyzing Temporal and Spatial
  Dynamics in Brain Networks
DSAM: A Deep Learning Framework for Analyzing Temporal and Spatial Dynamics in Brain Networks
Bishal Thapaliya
Robyn L. Miller
Jiayu Chen
Yu-Ping Wang
Esra Akbas
...
Bhaskar Ray
Pranav Suresh
Santosh Ghimire
Vince D. Calhoun
Jingyu Liu
136
20
0
19 May 2024
Personalized Negative Reservoir for Incremental Learning in Recommender Systems
Personalized Negative Reservoir for Incremental Learning in Recommender Systems
Antonios Valkanas
Yuening Wang
Yingxue Zhang
Mark Coates
CLL
248
2
0
06 Mar 2024
Online Cascade Learning for Efficient Inference over Streams
Online Cascade Learning for Efficient Inference over Streams
Lunyiu Nie
Zhimin Ding
Erdong Hu
Christopher M. Jermaine
Swarat Chaudhuri
301
15
0
07 Feb 2024
Brain Networks and Intelligence: A Graph Neural Network Based Approach
  to Resting State fMRI Data
Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data
Bishal Thapaliya
Esra Akbas
Jiayu Chen
Ram Sapkota
Bhaskar Ray
Pranav Suresh
Vince D. Calhoun
Jingyu Liu
279
32
0
06 Nov 2023
Simulation-based stacking
Simulation-based stackingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Yuling Yao
Bruno Régaldo-Saint Blancard
Justin Domke
256
6
0
25 Oct 2023
Generative models improve fairness of medical classifiers under
  distribution shifts
Generative models improve fairness of medical classifiers under distribution shiftsNature Network Boston (NNB), 2023
Ira Ktena
Olivia Wiles
Isabela Albuquerque
Sylvestre-Alvise Rebuffi
Ryutaro Tanno
...
Danielle Belgrave
Pushmeet Kohli
Alan Karthikesalingam
A. Cemgil
Sven Gowal
OODMedIm
373
144
0
18 Apr 2023
Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary
  Dropouts
Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts
Rohit Agarwal
D. K. Gupta
Alexander Horsch
Dilip K. Prasad
198
5
0
09 Mar 2023
ORFit: One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares
ORFit: One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-SquaresIEEE Conference on Decision and Control (CDC), 2022
Youngjae Min
Kwangjun Ahn
Navid Azizan
308
23
0
28 Jul 2022
On-the-Fly Test-time Adaptation for Medical Image Segmentation
On-the-Fly Test-time Adaptation for Medical Image SegmentationInternational Conference on Medical Imaging with Deep Learning (MIDL), 2022
Jeya Maria Jose Valanarasu
Pengfei Guo
VS Vibashan
Vishal M. Patel
OOD
108
41
0
10 Mar 2022
Deep learning enhanced Rydberg multifrequency microwave recognition
Deep learning enhanced Rydberg multifrequency microwave recognitionNature Communications (Nat Commun), 2022
Zongkai Liu
Li-Hua Zhang
Bang Liu
Zhengli Zhang
Guangtao Guo
D. Ding
B. Shi
113
64
0
28 Feb 2022
Burn After Reading: Online Adaptation for Cross-domain Streaming Data
Burn After Reading: Online Adaptation for Cross-domain Streaming Data
Luyu Yang
M. Gao
Zeyuan Chen
Ran Xu
Abhinav Shrivastava
Chetan Ramaiah
111
4
0
08 Dec 2021
Efficient Methods for Online Multiclass Logistic Regression
Efficient Methods for Online Multiclass Logistic Regression
Naman Agarwal
Satyen Kale
Julian Zimmert
179
12
0
06 Oct 2021
Repulsive Deep Ensembles are Bayesian
Repulsive Deep Ensembles are BayesianNeural Information Processing Systems (NeurIPS), 2021
Francesco DÁngelo
Vincent Fortuin
UQCVBDL
434
116
0
22 Jun 2021
ProtoRes: Proto-Residual Network for Pose Authoring via Learned Inverse
  Kinematics
ProtoRes: Proto-Residual Network for Pose Authoring via Learned Inverse KinematicsInternational Conference on Learning Representations (ICLR), 2021
Boris N. Oreshkin
Florent Bocquelet
Félix G. Harvey
Bay Raitt
Dominic Laflamme
3DH
294
18
0
03 Jun 2021
Self-Supervised Deep Visual Odometry with Online Adaptation
Self-Supervised Deep Visual Odometry with Online Adaptation
Shunkai Li
Xin Wang
Yingdian Cao
Fei Xue
Zike Yan
H. Zha
TTA
163
77
0
13 May 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
Bayesian Deep Learning and a Probabilistic Perspective of GeneralizationNeural Information Processing Systems (NeurIPS), 2020
A. Wilson
Pavel Izmailov
UQCVBDLOOD
615
734
0
20 Feb 2020
Stochastic Online Optimization using Kalman Recursion
Stochastic Online Optimization using Kalman RecursionJournal of machine learning research (JMLR), 2020
Joseph de Vilmarest
Olivier Wintenberger
182
9
0
10 Feb 2020
Physics-Guided Deep Neural Networks for Power Flow Analysis
Physics-Guided Deep Neural Networks for Power Flow AnalysisIEEE Transactions on Power Systems (IEEE Trans. Power Syst.), 2020
Xinyue Hu
Haoji Hu
Saurabh Verma
Zhi-Li Zhang
432
157
0
31 Jan 2020
Diversity regularization in deep ensembles
Diversity regularization in deep ensembles
Changjian Shui
A. Mozafari
Jonathan Marek
Ihsen Hedhli
Christian Gagné
UQCV
112
15
0
22 Feb 2018
Online Deep Learning: Learning Deep Neural Networks on the Fly
Online Deep Learning: Learning Deep Neural Networks on the Fly
Doyen Sahoo
Quang Pham
Jing Lu
Guosheng Lin
OnRLAI4CE
186
338
0
10 Nov 2017
Using stacking to average Bayesian predictive distributions
Using stacking to average Bayesian predictive distributions
Yuling Yao
Aki Vehtari
Daniel P. Simpson
Andrew Gelman
452
388
0
06 Apr 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCVBDL
1.4K
6,718
0
05 Dec 2016
Overcoming catastrophic forgetting in neural networks
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
...
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
CLL
1.1K
8,777
1
02 Dec 2016
A Bayes interpretation of stacking for M-complete and M-open settings
A Bayes interpretation of stacking for M-complete and M-open settings
Tri Le
B. Clarke
223
43
0
16 Feb 2016
Structured Prediction Cascades
Structured Prediction CascadesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2010
David J. Weiss
Benjamin Sapp
B. Taskar
161
126
0
06 Aug 2012
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