CoLLAs

Publications

2023

Renhao Huang, Anthony Tompkins, Maurice Pagnucco, Yang Song
Towards Single Source Domain Generalisation in Trajectory Prediction: A Motion Prior based Approach. CoLLAs (2023)
Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen, Sarath Chandar
Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning. CoLLAs (2023)
Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel
Stabilizing Unsupervised Environment Design with a Learned Adversary. CoLLAs (2023)
Hamed Hemati, Andrea Cossu, Antonio Carta, Julio Hurtado, Lorenzo Pellegrini, Davide Bacciu, Vincenzo Lomonaco, Damian Borth
Class-Incremental Learning with Repetition. CoLLAs (2023)
Réda Alami, Mohammed Mahfoud, Eric Moulines
Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes. CoLLAs (2023)
Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor
Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges. CoLLAs (2023)
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
Prospective Learning: Principled Extrapolation to the Future. CoLLAs (2023)
Hamed Hemati, Vincenzo Lomonaco, Davide Bacciu, Damian Borth
Partial Hypernetworks for Continual Learning. CoLLAs (2023)
Banafsheh Rafiee, Sina Ghiassian, Jun Jin, Richard S. Sutton, Jun Luo, Adam White
Auxiliary task discovery through generate-and-test. CoLLAs (2023)
Subhankar Roy, Riccardo Volpi, Gabriela Csurka, Diane Larlus
RaSP: Relation-aware Semantic Prior for Weakly Supervised Incremental Segmentation. CoLLAs (2023)
Hadi Nekoei, Akilesh Badrinaaraayanan, Amit Sinha, Mohammad Amini, Janarthanan Rajendran, Aditya Mahajan, Sarath Chandar
Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning. CoLLAs (2023)
Tom Dupuis, Jaonary Rabarisoa, Quoc-Cuong Pham, David Filliat
VIBR: Learning View-Invariant Value Functions for Robust Visual Control. CoLLAs (2023)
Yuqing Du, Ksenia Konyushkova, Misha Denil, Akhil Raju, Jessica Landon, Felix Hill, Nando de Freitas, Serkan Cabi
Vision-Language Models as Success Detectors. CoLLAs (2023)
Muberra Ozmen, Joseph Cotnareanu, Mark Coates
Substituting Data Annotation with Balanced Neighbourhoods and Collective Loss in Multi-label Text Classification. CoLLAs (2023)
Shenao Zhang, Li Shen, Lei Han, Li Shen
Learning Meta Representations for Agents in Multi-Agent Reinforcement Learning. CoLLAs (2023)
Eleni Nisioti, Elías Masquil, Gautier Hamon, Clément Moulin-Frier
Autotelic Reinforcement Learning in Multi-Agent Environments. CoLLAs (2023)
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash
Improving Performance in Continual Learning Tasks using Bio-Inspired Architectures. CoLLAs (2023)
Alexandre Galashov, Jovana Mitrovic, Dhruva Tirumala, Yee Whye Teh, Timothy Nguyen, Arslan Chaudhry, Razvan Pascanu
Continually learning representations at scale. CoLLAs (2023)
Massimiliano Patacchiola, Mingfei Sun, Katja Hofmann, Richard E. Turner
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy Imitation. CoLLAs (2023)
Sarthak Bhagat, Simon Stepputtis, Joseph Campbell, Katia P. Sycara
Sample-Efficient Learning of Novel Visual Concepts. CoLLAs (2023)
Safa Alver, Doina Precup
Minimal Value-Equivalent Partial Models for Scalable and Robust Planning in Lifelong Reinforcement Learning. CoLLAs (2023)
Christopher McClurg, Ali Ayub, Harsh Tyagi, Sarah Michele Rajtmajer, Alan R. Wagner
Active Class Selection for Few-Shot Class-Incremental Learning. CoLLAs (2023)
Shubham Malaviya, Manish Shukla, Sachin Lodha
Reducing Communication Overhead in Federated Learning for Pre-trained Language Models Using Parameter-Efficient Finetuning. CoLLAs (2023)
Grégoire Petit, Adrian Popescu, Eden Belouadah, David Picard, Bertrand Delezoide
PlaStIL: Plastic and Stable Exemplar-Free Class-Incremental Learning. CoLLAs (2023)
Gwen Legate, Lucas Caccia, Eugene Belilovsky
Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning. CoLLAs (2023)
Hsing-Huan Chung, Joydeep Ghosh
Incremental Unsupervised Domain Adaptation on Evolving Graphs. CoLLAs (2023)
Peter G. Chang, Gerardo Duràn-Martín, Alexander Y. Shestopaloff, Matt Jones, Kevin Patrick Murphy
Low-rank extended Kalman filtering for online learning of neural networks from streaming data. CoLLAs (2023)
Timothée Lesort, Oleksiy Ostapenko, Pau Rodríguez, Diganta Misra, Md Rifat Arefin, Laurent Charlin, Irina Rish
Challenging Common Assumptions about Catastrophic Forgetting and Knowledge Accumulation. CoLLAs (2023)
Saptarshi Nath, Christos Peridis, Eseoghene Ben-Iwhiwhu, Xinran Liu, Shirin Dora, Cong Liu, Soheil Kolouri, Andrea Soltoggio
Sharing Lifelong Reinforcement Learning Knowledge via Modulating Masks. CoLLAs (2023)
Vincent Liu, Han Wang, Ruo Yu Tao, Khurram Javed, Adam White, Martha White
Measuring and Mitigating Interference in Reinforcement Learning. CoLLAs (2023)
Boje Deforce, Bart Baesens, Jan Diels, Estefanía Serral Asensio
MultiMix TFT: A Multi-task Mixed-Frequency Framework with Temporal Fusion Transformers. CoLLAs (2023)
Arip Asadulaev, Vitaly Shutov, Alexander Korotin, Alexander Panfilov, Vladislava Kontsevaya, Andrey Filchenkov
A Minimalist Approach for Domain Adaptation with Optimal Transport. CoLLAs (2023)
Sashank Pisupati, Isabel M. Berwian, Jamie Chiu, Yongjing Ren, Yael Niv
Human inductive biases for aversive continual learning - a hierarchical Bayesian nonparametric model. CoLLAs (2023)
Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Geoffrey Holmes
Self-trained Centroid Classifiers for Semi-supervised Cross-domain Few-shot Learning. CoLLAs (2023)
Lior Friedman, Ron Meir
Adaptive Meta-Learning via data-dependent PAC-Bayes bounds. CoLLAs (2023)
Kushagra Chandak, Bingshan Hu, Nidhi Hegde
Differentially Private Algorithms for Efficient Online Matroid Optimization. CoLLAs (2023)
Vincent Létourneau, Colin Bellinger, Isaac Tamblyn, Maia Fraser
Time and temporal abstraction in continual learning: tradeoffs, analogies and regret in an active measuring setting. CoLLAs (2023)
Thang Doan, Seyed-Iman Mirzadeh, Mehrdad Farajtabar
Continual Learning Beyond a Single Model. CoLLAs (2023)
Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos
The Effectiveness of World Models for Continual Reinforcement Learning. CoLLAs (2023)
Gabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation. CoLLAs (2023)
Cédric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer, Xingdi Yuan, Marc-Alexandre Côté
Augmenting Autotelic Agents with Large Language Models. CoLLAs (2023)
Joseph Campbell, Yue Guo, Fiona Xie, Simon Stepputtis, Katia P. Sycara
Introspective Action Advising for Interpretable Transfer Learning. CoLLAs (2023)
Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado
Loss of Plasticity in Continual Deep Reinforcement Learning. CoLLAs (2023)
Kristopher De Asis, Eric Graves, Richard S. Sutton
Value-aware Importance Weighting for Off-policy Reinforcement Learning. CoLLAs (2023)
Yingjun Du, Jiayi Shen, Xiantong Zhen, Cees G. M. Snoek
EMO: Episodic Memory Optimization for Few-Shot Meta-Learning. CoLLAs (2023)
Albin Soutif-Cormerais, Antonio Carta, Joost van de Weijer
Improving Online Continual Learning Performance and Stability with Temporal Ensembles. CoLLAs (2023)
Randolph Linderman, Jingyang Zhang, Nathan Inkawhich, Hai Helen Li, Yiran Chen
Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification. CoLLAs (2023)
Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian Jiang, Bo Liu, Peter Stone
Model-Based Meta Automatic Curriculum Learning. CoLLAs (2023)
Amber Li, Tom Silver
Embodied Active Learning of Relational State Abstractions for Bilevel Planning. CoLLAs (2023)

volume 232, 2023

Conference on Lifelong Learning Agents, 22-25 August 2023, McGill University, Montréal, Québec, Canada. CoLLAs 232 (2023)