layout: post
title: “Bibliography Classified by Conferences”
date:
categories: Bibliography
author: T Lesort
tag: Bibliography
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Outline
- International-Conference-on-Learning-Representations-ICLR
- Conference-on-Computer-Vision-and-Pattern-Recognition-CVPR
- International-Conference-on-Computer-Vision-ICCV
- European-Conference-on-Computer-Vision-ECCV
- Neural-Information-Processing-Systems-NeuriPS
- International-Conference-on-Machine-Learning-ICML
- International-Joint-Conference-on-Artificial-Intelligence-IJCAI
- International-Joint-Conference-on-Neural-Networks-IJCNN
- International-Conference-on-Artificial-Neural-Networks-ICANN
International Conference on Learning Representations (ICLR)
- Uncertainty-guided Continual Learning with Bayesian Neural Networks, (2020) [paper] [bib] by Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell and Marcus Rohrbach
- Continual Learning with Bayesian Neural Networks for Non-Stationary Data, (2020) [paper] [bib] by Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt and Stephan Günnemann
- Continual learning with hypernetworks, (2020) [paper] [bib] by Johannes von Oswald, Christian Henning, João Sacramento and Benjamin F. Grewe
- Scalable and Order-robust Continual Learning with Additive Parameter Decomposition, (2020) [paper] [bib] by Jaehong Yoon, Saehoon Kim, Eunho Yang and Sung Ju Hwang
- Continual Learning with Adaptive Weights (CLAW), (2020) [paper] [bib] by Tameem Adel, Han Zhao and Richard E. Turner
- A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning, (2020) [paper] [bib] by Soochan Lee, Junsoo Ha, Dongsu Zhang and Gunhee Kim
- Compositional Language Continual Learning, (2020) [paper] [bib] by Yuanpeng Li, Liang Zhao, Kenneth Church and Mohamed Elhoseiny
- BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning, (2020) [paper] [bib] by Yeming Wen, Dustin Tran and Jimmy Ba
- SNOW: Subscribing to Knowledge via Channel Pooling for Transfer & Lifelong Learning of Convolutional Neural Networks, (2020) [paper] [bib] by Chungkuk Yoo, Bumsoo Kang and Minsik Cho
- LAMAL: LAnguage Modeling Is All You Need for Lifelong Language Learning, (2020) [paper] [bib] by Fan-Keng Sun, Cheng-Hao Ho and Hung-Yi Lee
- Progressive Memory Banks for Incremental Domain Adaptation, (2020) [paper] [bib] by Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart and Xin Jiang
- Efficient Lifelong Learning with A-GEM, (2019) [paper] [bib] by Chaudhry, Arslan, Ranzato, Marc’Aurelio, Rohrbach, Marcus and Elhoseiny, Mohamed
- Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL, (2019) [paper] [bib] by Anusha Nagabandi, Chelsea Finn and Sergey Levine
- An Empirical Study of Example Forgetting during Deep Neural Network Learning, (2019) [paper] [bib] by Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes, Adam Trischler, Yoshua Bengio and Geoffrey J. Gordon
- Functional Regularisation for Continual Learning with Gaussian Processes, (2019) [paper] [bib] by Titsias, Michalis K, Schwarz, Jonathan, Matthews, Alexander G de G, Pascanu, Razvan and Teh, Yee Whye
- A comprehensive, application-oriented study of catastrophic forgetting in {DNN}s, (2019) [paper] [bib] by B. Pfulb and A. Gepperth
- Selfless Sequential Learning, (2019) [paper] [bib] by Rahaf Aljundi, Marcus Rohrbach and Tinne Tuytelaars
- Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation, (2018) [paper] [bib] by Xu He and Herbert Jaeger
- Variational Continual Learning, (2018) [paper] [bib] by Cuong V. Nguyen, Yingzhen Li, Thang D. Bui and Richard E. Turner
- FearNet: Brain-Inspired Model for Incremental Learning, (2018) [paper] [bib] by Ronald Kemker and Christopher Kanan
Conference on Computer Vision and Pattern Recognition (CVPR)
- Few-Shot Class-Incremental Learning, (2020) [bib] by Tao, Xiaoyu, Hong, Xiaopeng, Chang, Xinyuan, Dong, Songlin, Wei, Xing and Gong, Yihong
- Incremental Few-Shot Object Detection, (2020) [bib] by Perez-Rua, Juan-Manuel, Zhu, Xiatian, Hospedales, Timothy M and Xiang, Tao
- Conditional Channel Gated Networks for Task-Aware Continual Learning, (2020) [bib] by Abati, Davide, Tomczak, Jakub, Blankevoort, Tijmen, Calderara, Simone, Cucchiara, Rita and Bejnordi, Babak Ehteshami
- Incremental Learning in Online Scenario, (2020) [bib] by He, Jiangpeng, Mao, Runyu, Shao, Zeman and Zhu, Fengqing
- iTAML: An Incremental Task-Agnostic Meta-learning Approach, (2020) [bib] by Rajasegaran, Jathushan, Khan, Salman, Hayat, Munawar, Khan, Fahad Shahbaz and Shah, Mubarak
- ADINet: Attribute Driven Incremental Network for Retinal Image Classification, (2020) [bib] by Meng, Qier and Shin’ichi, Satoh
- Semantic drift compensation for class-incremental learning, (2020) [bib] by Yu, Lu, Twardowski, Bartlomiej, Liu, Xialei, Herranz, Luis, Wang, Kai, Cheng, Yongmei, Jui, Shangling and Weijer, Joost van de
- Maintaining Discrimination and Fairness in Class Incremental Learning, (2020) [bib] by Zhao, Bowen, Xiao, Xi, Gan, Guojun, Zhang, Bin and Xia, Shu-Tao
- Mnemonics Training: Multi-Class Incremental Learning without Forgetting, (2020) [bib] by Liu, Yaoyao, Su, Yuting, Liu, An-An, Schiele, Bernt and Sun, Qianru
- Learning to remember: A synaptic plasticity driven framework for continual learning, (2019) [paper] [bib] by Ostapenko, Oleksiy, Puscas, Mihai, Klein, Tassilo, Jahnichen, Patrick and Nabi, Moin
- Learning to remember: A synaptic plasticity driven framework for continual learning, (2019) [bib] by Ostapenko, Oleksiy, Puscas, Mihai, Klein, Tassilo, Jahnichen, Patrick and Nabi, Moin
- Large scale incremental learning, (2019) [paper] [bib] by Wu, Yue, Chen, Yinpeng, Wang, Lijuan, Ye, Yuancheng, Liu, Zicheng, Guo, Yandong and Fu, Yun
- Learning a Unified Classifier Incrementally via Rebalancing, (2019) [bib] by Hou, Saihui, Pan, Xinyu, Loy, Chen Change, Wang, Zilei and Lin, Dahua
- Learning Without Memorizing, (2019) [bib] by Dhar, Prithviraj, Singh, Rajat Vikram, Peng, Kuan-Chuan, Wu, Ziyan and Chellappa, Rama
- Packnet: Adding multiple tasks to a single network by iterative pruning, (2018) [bib] by Mallya, Arun and Lazebnik, Svetlana
- New Metrics and Experimental Paradigms for Continual Learning, (2018) [bib] by T. L. Hayes, R. Kemker, N. D. Cahill and C. Kanan
- icarl: Incremental classifier and representation learning, (2017) [paper] [bib] by Rebuffi, Sylvestre-Alvise, Kolesnikov, Alexander, Sperl, Georg and Lampert, Christoph H
- Growing a brain: Fine-tuning by increasing model capacity, (2017) [bib] by Wang, Yu-Xiong, Ramanan, Deva and Hebert, Martial
- Expert gate: Lifelong learning with a network of experts, (2017) [bib] by Aljundi, Rahaf, Chakravarty, Punarjay and Tuytelaars, Tinne
- On-the-fly adaptation of regression forests for online camera relocalisation, (2017) [bib] by Cavallari, Tommaso, Golodetz, Stuart, Lord, Nicholas A, Valentin, Julien, Di Stefano, Luigi and Torr, Philip HS
International Conference on Computer Vision (ICCV)
- Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild, (2019) [paper] [bib] by Lee, Kibok, Lee, Kimin, Shin, Jinwoo and Lee, Honglak
European Conference on Computer Vision (ECCV)
- Adversarial Continual Learning, (2020) [paper] [bib] by Ebrahimi, Sayna, Meier, Franziska, Calandra, Roberto, Darrell, Trevor and Rohrbach, Marcus
- Imbalanced Continual Learning with Partitioning Reservoir Sampling, (2020) [paper] [bib] by Kim, Chris Dongjoo, Jeong, Jinseo and Kim, Gunhee
- Online Continual Learning under Extreme Memory Constraints, (2020) [paper] [bib] by Fini, Enrico, Lathuili{`e}re, St{'e}phane, Sangineto, Enver, Nabi, Moin and Ricci, Elisa
- LIRA: Lifelong Image Restoration from Unknown Blended Distortions, (2020) [paper] [bib] by Liu, Jianzhao, Lin, Jianxin, Li, Xin, Zhou, Wei, Liu, Sen and Chen, Zhibo
- Learning latent representations across multiple data domains using Lifelong VAEGAN, (2020) [paper] [bib] by Ye, Fei and Bors, Adrian G
- Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation, (2020) [paper] [bib] by Zhai, Mengyao, Chen, Lei, He, Jiawei, Nawhal, Megha, Tung, Frederick and Mori, Greg
- More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning, (2020) [paper] [bib] by Liu, Yu, Parisot, Sarah, Slabaugh, Gregory, Jia, Xu, Leonardis, Ales and Tuytelaars, Tinne
- Incremental Few-Shot Meta-Learning via Indirect Discriminant Alignment, (2020) [paper] [bib] by Liu, Qing, Majumder, Orchid, Achille, Alessandro, Ravichandran, Avinash, Bhotika, Rahul and Soatto, Stefano
- Class-Incremental Domain Adaptation, (2020) [paper] [bib] by Kundu, Jogendra Nath, Venkatesh, Rahul Mysore, Venkat, Naveen, Revanur, Ambareesh and Babu, R Venkatesh
- Memory-Efficient Incremental Learning Through Feature Adaptation, (2020) [paper] [bib] by Iscen, Ahmet, Zhang, Jeffrey, Lazebnik, Svetlana and Schmid, Cordelia
- PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning, (2020) [paper] [bib] by Douillard, Arthur, Cord, Matthieu, Ollion, Charles, Robert, Thomas and Valle, Eduardo
- Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference, (2020) [paper] [bib] by Kanakis, Menelaos, Bruggemann, David, Saha, Suman, Georgoulis, Stamatios, Obukhov, Anton and Van Gool, Luc
- {REMIND Your Neural Network to Prevent Catastrophic Forgetting}, (2020) [paper] [bib] by {Hayes}, Tyler L., {Kafle}, Kushal, {Shrestha}, Robik and {Acharya}, Manoj and {Kanan}, Christopher
- Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence, (2018) [paper] [bib] by Chaudhry, Arslan, Dokania, Puneet K, Ajanthan, Thalaiyasingam and Torr, Philip HS
- Lifelong learning via progressive distillation and retrospection, (2018) [paper] [bib] by Hou, Saihui, Pan, Xinyu, Change Loy, Chen, Wang, Zilei and Lin, Dahua
- End-to-end incremental learning, (2018) [paper] [bib] by Castro, Francisco M, Marin-Jimenez, Manuel J, Guil, Nicolas, Schmid, Cordelia and Alahari, Karteek
- Piggyback: Adapting a single network to multiple tasks by learning to mask weights, (2018) [bib] by Mallya, Arun, Davis, Dillon and Lazebnik, Svetlana
- DeeSIL: Deep-Shallow Incremental Learning., (2018) [bib] by Belouadah, Eden and Popescu, Adrian
Neural Information Processing Systems (NeuriPS)
- Compacting, Picking and Growing for Unforgetting Continual Learning, (2019) [paper] [bib] by Hung, Ching-Yi, Tu, Cheng-Hao, Wu, Cheng-En, Chen, Chien-Hung, Chan, Yi-Ming and Chen, Chu-Song
- Uncertainty-based Continual Learning with Adaptive Regularization, (2019) [paper] [bib] by Ahn, Hongjoon, Cha, Sungmin, Lee, Donggyu and Moon, Taesup
- Gradient based sample selection for online continual learning, (2019) [paper] [bib] by Aljundi, Rahaf, Lin, Min, Goujaud, Baptiste and Bengio, Yoshua
- Online Continual Learning with Maximal Interfered Retrieval, (2019) [paper] [bib] by Aljundi, Rahaf, Caccia, Lucas, Belilovsky, Eugene, Caccia, Massimo, Lin, Min, Charlin, Laurent and Tuytelaars, Tinne
- Meta-Learning Representations for Continual Learning, (2019) [paper] [bib] by Javed, Khurram and White, Martha
- Reconciling meta-learning and continual learning with online mixtures of tasks, (2019) [paper] [bib] by Jerfel, Ghassen, Grant, Erin, Griffiths, Tom and Heller, Katherine A
- Experience replay for continual learning, (2019) [paper] [bib] by Rolnick, David, Ahuja, Arun, Schwarz, Jonathan, Lillicrap, Timothy and Wayne, Gregory
- Incremental few-shot learning with attention attractor networks, (2019) [bib] by Ren, Mengye, Liao, Renjie, Fetaya, Ethan and Zemel, Richard
- Memory Replay GANs: Learning to Generate New Categories without Forgetting, (2018) [paper] [bib] by Wu, Chenshen, Herranz, Luis, Liu, Xialei, wang, yaxing, van de Weijer, Joost and Raducanu, Bogdan
- Online structured laplace approximations for overcoming catastrophic forgetting, (2018) [bib] by Ritter, Hippolyt, Botev, Aleksandar and Barber, David
- Gradient Episodic Memory for Continual Learning, (2017) [paper] [bib] by Lopez-Paz, David and Ranzato, Marc-Aurelio
- Continual learning with deep generative replay, (2017) [paper] [bib] by Shin, Hanul, Lee, Jung Kwon, Kim, Jaehong and Kim, Jiwon
- Overcoming catastrophic forgetting by incremental moment matching, (2017) [bib] by Lee, Sang-Woo, Kim, Jin-Hwa, Jun, Jaehyun, Ha, Jung-Woo and Zhang, Byoung-Tak
- Lifelong learning with non-iid tasks, (2015) [bib] by Pentina, Anastasia and Lampert, Christoph H
- Toward a formal framework for continual learning, (2005) [bib] by Ring, Mark B
International Conference on Machine Learning (ICML)
- Online Meta-Learning, (2019) [paper] [bib] by Finn, Chelsea, Rajeswaran, Aravind, Kakade, Sham and Levine, Sergey
- Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer, (2019) [bib] by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David *
- Progress \& compress: A scalable framework for continual learning, (2018) [paper] [bib] by Schwarz, Jonathan, Luketina, Jelena, Czarnecki, Wojciech M, Grabska-Barwinska, Agnieszka, Teh, Yee Whye, Pascanu, Razvan and Hadsell, Raia
- Continual Learning Through Synaptic Intelligence, (2017) [paper] [bib] by *Zenke, Friedeman, Poole, Ben and Ganguli, Surya *
- Model-agnostic meta-learning for fast adaptation of deep networks, (2017) [bib] by Finn, Chelsea, Abbeel, Pieter and Levine, Sergey
- A {PAC}-Bayesian bound for lifelong learning, (2014) [bib] by Pentina, Anastasia and Lampert, Christoph
- {ELLA}: An Efficient Lifelong Learning Algorithm, (2013) [paper] [bib] by Paul Ruvolo and Eric Eaton
International Joint Conference on Artificial Intelligence (IJCAI)
- Closed-loop Memory GAN for Continual Learning, (2019) [paper] [bib] by Rios, Amanda and Itti, Laurent
- Dual-memory Deep Learning Architectures for Lifelong Learning of Everyday Human Behaviors, (2016) [paper] [bib] by Lee, Sang-Woo, Lee, Chung-Yeon, Kwak, Dong-Hyun, Kim, Jiwon, Kim, Jeonghee and Zhang, Byoung-Tak
International Joint Conference on Neural Networks (IJCNN)
- Generative Models from the perspective of Continual Learning, (2019) [paper] [bib] by Lesort, Timoth{'e}e, Caselles-Dupr{'e}, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David
- A cognitive developmental robotics architecture for lifelong learning by evolution in real robots, (2010) [bib] by Bellas, Francisco, Fai{~n}a, Andr{'e}s, Varela, Gervasio and Duro, Richard J