Paper Authors Tags Video
Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer Seungwon Lee, Sima Behpour, Eric Eaton Lifelong Learning, Continual Learning https://www.youtube.com/watch?v=zAwwr8BqAS0
Evaluating Logical Generalization in Graph Neural Networks Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton Graph Representation Learning, Lifelong Learning, Logic https://www.youtube.com/watch?v=TKEjaA4m4jg&feature=youtu.be
Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation Ryan Julian, Benjamin Swanson, Gaurav S. Sukhatme, Sergey Levine, Chelsea Finn, Karol Hausman Fine-tuning, Continual Learning, Deep Rl, Vision, Robotics, Manipulation, Lifelong Learning https://youtu.be/dj8oCgZbnwU
Wandering Within a World: Online Contextualized Few-Shot Learning Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel Few-shot Learning, Continual Learning, Lifelong Learning https://youtu.be/pLcJwWumt2I
Taming the Herd: Multi-Modal Meta-Learning with a Population of Agents Robert Müller, Jack Parker-holder, Aldo Pacchiano Meta-learning https://youtu.be/36yP-NNlB1o
Lifelong Learning of Factored Policies via Policy Gradients Jorge A Mendez, Eric Eaton Lifelong Learning, Policy Gradient Learning, Factored Policies https://www.youtube.com/watch?v=aZoRM48pVFw
Learning Intrinsically Motivated Options to Stimulate Policy Exploration Louis Bagot, Kevin Mets, Steven Latré Reinforcement Learning, Intrinsic Motivation, Curiosity, Hierarchical Reinforcement Learning, Options, Exploration Option https://youtu.be/hY5FzrXCyIk
Hierarchical Expert Networks for Meta-Learning Heinke Hihn, Daniel A. Braun Meta-learning, Regression, Classification, Reinforcement Learning, Information Theory https://youtu.be/B0wHa4NNejg
La-MAML: Look-ahead Meta Learning for Continual Learning Gunshi Gupta, Karmesh Yadav, Liam Paull Continual Learning, Meta Learning, Online Learning https://youtu.be/HzewyVu8LaY
Covariate Distribution aware Meta-learning Amrith Setlur, Saket Dingliwal, Barnabas Poczos Meta-learning, Few-shot Learning, Graphical Model, Bayesian https://youtu.be/oBrcTESEu1Y
Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual Learning Sandeep Madireddy, Angel Yanguas-gil, Prasanna Balaprakash Online Learning, Continual Learning, Neuromorphic Architectures, Transfer Metalearning, Mixed-integer Optimization https://youtu.be/Rif6CjnG7Mw
Tackling Non-forgetting and Forward Transfer with a Unified Lifelong Learning Approach Xinyu Yun, Tanner A Bohn, Charles X. Ling Lifelong Learning, Catestrohphic Forgetting, Forward Transfer, Backward Transfer https://www.youtube.com/watch?v=nI4N7s9l_bk
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov Multitask Rl, Inverse Rl, Hindsight Relabeling
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine Reinforcement Learning, Transfer Learning, Domain Adaptation
Importance Weighting with a Adversarial Network for Large-Scale Sleep Staging Samaneh Nasiri, Gari D. Clifford Adversarial Neural Network, Domain Adaptation, Intra And Inter-patient Variability, Eeg, Sleep Staging https://www.youtube.com/watch?v=5kxqkNKpl1g
Unsupervised Progressive Learning and the STAM Architecture James Smith, Seth Baer, Cameron Taylor, Constantine Continual Learning, Unsupervised Learning, Online Learning, Clustering https://youtu.be/CAL0C8zUOxk
Active Online Domain Adaptation Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang Online Learning, Active Learning, Bandit Algorithms https://youtu.be/vrvoX59Q7ck
Bridging Worlds in Reinforcement Learning with Model-Advantage Nirbhay Modhe, Harish K Kamath, Dhruv Batra, Ashwin Kalyan Model, Advantage, Reinforcement, Learning, Reinforcement Learning, Model-based, Imitation, Generalization, Fqi, Value, Iteration https://youtu.be/a7MopjK58gc
Towards an Unsupervised Method for Model Selection in Few-Shot Learning Simon Guiroy, Vikas Verma, Christopher Pal Meta-Learning, Few-Shot Learning, Early Stopping, Deep Learning https://www.youtube.com/watch?v=RAOhJTB4Clw
Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent Mehdi Abbana Bennani, Masashi Sugiyama Continual Learning, Deep Learning Theory, Deep Learning, Transfer Learning, Statistical Learning, Curriculum Learning https://youtu.be/_P1OXpjDf6Y
Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn Meta-learning, Reinforcement Learning, Exploration https://youtu.be/EiIC0Rkz8-s
Federated Continual Learning with Weighted Inter-client Transfer Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang Continual Learning, Federated Learning, Deep Learning https://youtu.be/6SU0PGCZqxs
Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition and Selective Transfer Aswin Raghavan, Jesse Hostetler, Indranil Sur, Abrar Rahman, Ajay Divakaran Lifelong Learning, Reinforcement Learning, Continual Learning, Machine Learning, Starcraft https://youtu.be/IsO2Yz4z43Q
Skill Discovery for Exploration and Planning using Deep Skill Graphs Akhil Bagaria, Jason Crowley, Jing Wei Nicholas Lim, George Konidaris Deep Reinforcement Learning, Hierarchical Reinforcement Learning, Planning, Exploration https://youtu.be/KLjonDBiKx0
Off-Policy Adversarial Inverse Reinforcement Learning Samin Yeasar Arnob Reinforcement Learning, Transfer Learning, Inverse Reinforcement Learning https://youtu.be/PK3byu61JKI
Chaotic Continual Learning Touraj Laleh, Mojtaba Faramarzi, Irina Rish, Sarath Chandar Continual Learning, Catastrophic Forgetting https://youtu.be/-NcJA8nDw54
Attention Option-Critic Raviteja Chunduru, Doina Precup Reinforcement Learning, Hierarchical Reinforcement Learning, Temporal Abstraction, Options, Attention https://youtu.be/m3VbVy9--gI
CPR: Classifier-Projection Regularization for Continual Learning Sungmin Cha, Hsiang Hsu, Flavio Du Pin Calmon, And Taesup Moon Continual Learning, Wide Local Minima, Catastrophic Forgetting https://youtu.be/aMuuvmcXIS8
Logical Composition in Lifelong Reinforcement Learning Geraud Nangue Tasse, Steven James, Benjamin Rosman Reinforcement Learning, Lifelong Learning, Multi Task Learning, Transfer Learning, Zero Shot Composition https://youtu.be/OtA3HYl5bVg
Deep Reinforcement Learning amidst Lifelong Non-Stationarity Annie Xie, James Harrison, Chelsea Finn Non-stationarity, Reinforcement Learning https://youtu.be/FyKPO7LV06I
Meta-Learning for Recalibration of EMG-Based Upper Limb Prostheses Krsto Proroković, Michael Wand, Jürgen Schmidhuber Meta-learning, Emg
RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning Riccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost Van De Weijer Continual Learning, Image Captioning, Lstms, Catastrophic Forgetting https://youtu.be/r7NELrvSbDk
Combining Variational Continual Learning with FiLM Layers Noel Loo, Siddharth Swaroop, Richard E Turner https://www.youtube.com/watch?v=9R5DsATuLIU&feature=youtu.be
Pseudo-Rehearsal for Continual Learning with Normalizing Flows Jary Pomponi, Simone Scardapane, Aurelio Uncini Machine Learning, Continuous Learning, Normalizing Flow, Catastrophic Forgetting https://youtu.be/vAOc7ZmaiII
MemeSem:A Multi-modal Framework for Sentimental Analysis of Meme via Transfer Learning Raj Ratn Pranesh, Ambesh Shekhar Multimodal, Social Computing, Sentiment Analysis, Transfer Learning, Natural Language Processing, Deep Learning https://youtu.be/E05Z4_gvBIk
A Brief Look at Generalization in Visual Meta-Reinforcement Learning Safa Alver, Doina Precup Meta-reinforcement Learning, Generalization In Reinforcement Learning https://youtu.be/wjCv7yPpssQ
ELSIM: End-to-end learning of reusable skills through intrinsic motivation Arthur Aubret, Laetitia Matignon, Salima Hassas Intrinsic Motivation, Curriculum Learning, Developmental Learning, Reinforcement Learning https://youtu.be/TkKQCFKDk1o
Task Agnostic Continual Learning via Meta Learning Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu Continual Learning, Meta Learning, Gan, Multi-agent Game https://youtu.be/nmKlx3lI14g
Continual Learning from the Perspective of Compression Xu He, Min Lin Continual Learning, Compression, Mdl https://youtu.be/jl2aRNpZWn0
Continual Deep Learning by Functional Regularisation of Memorable Past Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard Turner, Mohammad Emtiyaz Khan Continual Learning, Lifelong Learning, Deep Learning, Functional Regularisation https://youtu.be/1bFGWUfkKpE
Off-Policy Meta-Reinforcement Learning Based on Feature Embedding Spaces Takahisa Imagawa, Takuya Hiraoka, Yoshimasa Tsuruoka Reinforcement Learning, Meta-learning, Amortized Inference, Transfer Learning https://youtu.be/BA3Ygsnt7v0
Exchangeable Models in Meta Reinforcement Learning Iryna Korshunova, Jonas Degrave, Joni Dambre, Arthur Gretton, Ferenc Huszar Meta-rl, Task Inference, Exchangeability https://youtu.be/tvNSp_zGoi4
Effective Diversity in Population Based Reinforcement Learning Jack Parker-holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts https://www.youtube.com/watch?v=2k26xxPw3CA&feature=youtu.be
A Policy Gradient Method for Task-Agnostic Exploration Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli Unsupervised Reinforcement Learning, Intrinsic Motivation, Task-agnostic Exploration https://youtu.be/rOutDTj1MuA
Optimizing for the Future in Non-Stationary MDPs Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas Non-stationary Mdps, Reinforcement Learning, Lifelong Learning https://icml.cc/virtual/2020/poster/6316
Curriculum Learning with Diversity for Supervised Computer Vision Tasks Petru Soviany Curriculum Learning, Self-paced Learning, Object Detection, Instance Segmentation https://youtu.be/le06MIJdpPw
Generalizing Curricula for Reinforcement Learning Sanmit Narvekar, Peter Stone Curriculum Learning, Transfer Learning, Reinforcement Learning https://youtu.be/MpSEMVzfA0Y
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees Jonas Rothfuss, Vincent Fortuin, Andreas Krause Meta-learning, Multi-task Learning https://youtu.be/CfDQT96kJ3w
Continual Learning of Object Instances Kishan Parshotam, Mert Kilickaya Continual Learning, Object Instances, Metric Learning, Re-identification, Data Privacy https://youtu.be/F6uIGzCwFCk
Gradient Based Memory Editing for Task-Free Continual Learning Xisen Jin, Junyi Du, Xiang Ren Continual Learning, Task-free Continual Learning, Memory Editing https://youtu.be/aoSMcD_drTg
Storing Encoded Episodes as Concepts for Continual Learning Ali Ayub, Alan R. Wagner Continual Learning, Cognitively-inspired Learning, Class-incremental Learning, Catastrophic Forgetting https://youtu.be/oZPx_ZSJVJU
Hierarchical reinforcment learning for efficent exploration and transfer Lorenzo Steccanella, Simone Totaro, Damien Allonsius, Anders Jonsson Reinforcment Learning, Hierarchical Reinforcment Learning, Transfer Learning, Sparse Reward Domains https://www.youtube.com/watch?v=MJlW8bJy-BA&feature=youtu.be
Meta-Learning GNN Initializations for Low-Resource Molecular Property Prediction Cuong Q. Nguyen, Constantine Kreatsoulas, Kim M. Branson Meta-learning, Few-shot Learning, Graph Neural Networks, Qsar