CoLLAs 2022

64 papers

A Dataset Perspective on Offline Reinforcement Learning Kajetan Schweighofer, Marius-constantin Dinu, Andreas Radler, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-nemling, Hamid Eghbal-zadeh, Sepp Hochreiter
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A Multi-Head Model for Continual Learning via Out-of-Distribution Replay Gyuhak Kim, Bing Liu, Zixuan Ke
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A Rule-Based Shield: Accumulating Safety Rules from Catastrophic Action Effects Shahaf S. Shperberg, Bo Liu, Alessandro Allievi, Peter Stone
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A Theory for Knowledge Transfer in Continual Learning Diana Benavides-Prado, Patricia Riddle
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Adapting Pre-Trained Language Models to Low-Resource Text Simplification: The Path Matters Cristina Garbacea, Qiaozhu Mei
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Benchmarking Learning Efficiency in Deep Reservoir Computing Hugo Cisneros, Tomas Mikolov, Josef Sivic
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CLActive: Episodic Memories for Rapid Active Learning Sri Aurobindo Munagala, Sidhant Subramanian, Shyamgopal Karthik, Ameya Prabhu, Anoop Namboodiri
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CompoSuite: A Compositional Reinforcement Learning Benchmark Jorge A. Mendez, Marcel Hussing, Meghna Gummadi, Eric Eaton
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Consistency Is the Key to Further Mitigating Catastrophic Forgetting in Continual Learning Prashant Shivaram Bhat, Bahram Zonooz, Elahe Arani
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Continual Learning and Private Unlearning Bo Liu, Qiang Liu, Peter Stone
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Continual Learning of Dynamical Systems with Competitive Federated Reservoir Computing Leonard Bereska, Efstratios Gavves
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Continual Learning Through Hamilton Equations Alessandro Betti, Lapo Faggi, Marco Gori, Matteo Tiezzi, Simone Marullo, Enrico Meloni, Stefano Melacci
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Continual Learning with Foundation Models: An Empirical Study of Latent Replay Oleksiy Ostapenko, Timothee Lesort, Pau Rodriguez, Md Rifat Arefin, Arthur Douillard, Irina Rish, Laurent Charlin
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Continual Novelty Detection Rahaf Aljundi, Daniel Olmeda Reino, Nikolay Chumerin, Richard E. Turner
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Continual Unsupervised Learning for Optical Flow Estimation with Deep Networks Simone Marullo, Matteo Tiezzi, Alessandro Betti, Lapo Faggi, Enrico Meloni, Stefano Melacci
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CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning Agents Sam Powers, Eliot Xing, Eric Kolve, Roozbeh Mottaghi, Abhinav Gupta
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Curbing Task Interference Using Representation Similarity-Guided Multi-Task Feature Sharing Naresh Kumar Gurulingan, Elahe Arani, Bahram Zonooz
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Differencing Based Self-Supervised Pretraining for Scene Change Detection Vijaya Raghavan T. Ramkumar, Elahe Arani, Bahram Zonooz
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Disentanglement and Generalization Under Correlation Shifts Christina M. Funke, Paul Vicol, Kuan-chieh Wang, Matthias Kuemmerer, Richard Zemel, Matthias Bethge
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EFL: Elastic Federated Learning on Non-IID Data Zichen Ma, Yu Lu, Wenye Li, Shuguang Cui
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Energy-Based Models for Continual Learning Shuang Li, Yilun Du, Gido Ven, Igor Mordatch
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Few-Shot Learning by Dimensionality Reduction in Gradient Space Martin Gauch, Maximilian Beck, Thomas Adler, Dmytro Kotsur, Stefan Fiel, Hamid Eghbal-zadeh, Johannes Brandstetter, Johannes Kofler, Markus Holzleitner, Werner Zellinger, Daniel Klotz, Sepp Hochreiter, Sebastian Lehner
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Forgetting and Imbalance in Robot Lifelong Learning with Off-Policy Data Wenxuan Zhou, Steven Bohez, Jan Humplik, Nicolas Heess, Abbas Abdolmaleki, Dushyant Rao, Markus Wulfmeier, Tuomas Haarnoja
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Heat-RL: Online Model Selection for Streaming Time-Series Anomaly Detection Yujing Wang, Luoxin Xiong, Mingliang Zhang, Hui Xue, Qi Chen, Yaming Yang, Yunhai Tong, Congrui Huang, Bixiong Xu
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Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning Michael Matthews, Mikayel Samvelyan, Jack Parker-holder, Edward Grefenstette, Tim Rocktäschel
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How Do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert Dick
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How Does the Task Landscape Affect MAML Performance? Liam Collins, Aryan Mokhtari, Sanjay Shakkottai
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Improved Policy Optimization for Online Imitation Learning Jonathan Wilder Lavington, Sharan Vaswani, Mark Schmidt
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Improving Meta-Learning Generalization with Activation-Based Early-Stopping Simon Guiroy, Christopher Pal, Goncalo Mordido, Sarath Chandar
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InBiaseD: Inductive Bias Distillation to Improve Generalization and Robustness Through Shape-Awareness Shruthi Gowda, Bahram Zonooz, Elahe Arani
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Increasing Model Generalizability for Unsupervised Visual Domain Adaptation Mohammad Rostami
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Inexperienced RL Agents Can’t Get It Right: Lower Bounds on Regret at Finite Sample Complexity Maia Fraser, Vincent Létourneau
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Inherent Limitations of Multi-Task Fair Representations Tosca Lechner, Shai Ben-David
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Learning Object-Centered Autotelic Behaviors with Graph Neural Networks Ahmed Akakzia, Olivier Sigaud
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Learning Skills Diverse in Value-Relevant Features Matthew J. A. Smith, Jelena Luketina, Kristian Hartikainen, Maximilian Igl, Shimon Whiteson
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Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning Phung Lai, Han Hu, Hai Phan, Ruoming Jin, My Thai, An Chen
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Lifelong Robotic Reinforcement Learning by Retaining Experiences Annie Xie, Chelsea Finn
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Meta-Gradients in Non-Stationary Environments Jelena Luketina, Sebastian Flennerhag, Yannick Schroecker, David Abel, Tom Zahavy, Satinder Singh
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MO2: Model-Based Offline Options Sasha Salter, Markus Wulfmeier, Dhruva Tirumala, Nicolas Heess, Martin Riedmiller, Raia Hadsell, Dushyant Rao
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Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2 Zachary Alan Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael Piacentino, Ajay Divakaran, Roberto Corizzo, Kamil Faber, Nathalie Japkowicz, Michael Baron, James Smith, Sahana Pramod Joshi, Zsolt Kira, Cameron Ethan Taylor, Mustafa Burak Gurbuz, Constantine Dovrolis, Tyler L. Hayes, Christopher Kanan, Jhair Gallardo
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Neural Distillation as a State Representation Bottleneck in Reinforcement Learning Valentin Guillet, Dennis George Wilson, Emmanuel Rachelson
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On Anytime Learning at Macroscale Lucas Caccia, Jing Xu, Myle Ott, Marcaurelio Ranzato, Ludovic Denoyer
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On the Limitations of Continual Learning for Malware Classification Mohammad Saidur Rahman, Scott Coull, Matthew Wright
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Online Continual Learning for Embedded Devices Tyler L. Hayes, Christopher Kanan
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Open Set Recognition via Augmentation-Based Similarity Learning Sepideh Esmaeilpour, Lei Shu, Bing Liu
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Optimal Transport Meets Noisy Label Robust Loss and MixUp Regularization for Domain Adaptation Kilian Fatras, Hiroki Naganuma, Ioannis Mitliagkas
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Overcoming Challenges in Leveraging GANs for Few-Shot Data Augmentation Christopher Beckham, Issam H. Laradji, Pau Rodriguez, David Vazquez, Derek Nowrouzezahrai, Christopher Pal
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Practical Tradeoffs Between Memory, Compute, and Performance in Learned Optimizers Luke Metz, C. Daniel Freeman, James Harrison, Niru Maheswaranathan, Jascha Sohl-dickstein
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Predictive Learning Enables Neural Networks to Learn Complex Working Memory Tasks Thijs Lambik Plas, Sanjay G. Manohar, Tim P. Vogels
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Probing Transfer in Deep Reinforcement Learning Without Task Engineering Andrei Alex Rusu, Sebastian Flennerhag, Dushyant Rao, Razvan Pascanu, Raia Hadsell
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Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-constantin Dinu, Vihang Prakash Patil, Angela Bitto-nemling, Hamid Eghbal-zadeh, Sepp Hochreiter
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Self-Activating Neural Ensembles for Continual Reinforcement Learning Sam Powers, Eliot Xing, Abhinav Gupta
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SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries Meghna Gummadi, David Kent, Jorge A. Mendez, Eric Eaton
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Sim-to-Real Transfer of Visual Grounding for Human-Aided Ambiguity Resolution Georgios Tziafas, Lambert Schomaker, Hamidreza Kasaei
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Simulation-Acquired Latent Action Spaces for Dynamics Generalization Nicholas Corrado, Yuxiao Qu, Josiah P. Hanna
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Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations Ali Abbasi, Parsa Nooralinejad, Vladimir Braverman, Hamed Pirsiavash, Soheil Kolouri
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Streaming Inference for Infinite Non-Stationary Clustering Rylan Schaeffer, Gabrielle Kaili-may Liu, Yilun Du, Scott Linderman, Ila R. Fiete
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SYNERgy Between SYNaptic Consolidation and Experience Replay for General Continual Learning Fahad Sarfraz, Elahe Arani, Bahram Zonooz
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TAG: Task-Based Accumulated Gradients for Lifelong Learning Pranshu Malviya, Balaraman Ravindran, Sarath Chandar
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Task Agnostic Representation Consolidation: A Self-Supervised Based Continual Learning Approach Prashant Shivaram Bhat, Bahram Zonooz, Elahe Arani
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Test Sample Accuracy Scales with Training Sample Density in Neural Networks Xu Ji, Razvan Pascanu, R. Devon Hjelm, Balaji Lakshminarayanan, Andrea Vedaldi
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Trustworthiness Evaluation and Trust-Aware Design of CNN Architectures Mingxi Cheng, Tingyang Sun, Shahin Nazarian, Paul Bogdan
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What Should I Know? Using Meta-Gradient Descent for Predictive Feature Discovery in a Single Stream of Experience Alex Kearney, Anna Koop, Johannes Günther, Patrick M. Pilarski
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Zipfian Environments for Reinforcement Learning Stephanie C.Y. Chan, Andrew Kyle Lampinen, Pierre Harvey Richemond, Felix Hill
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