Timezone: »
Accepted papers: https://www.amtl-workshop.org/accepted-papers
TuckER: Tensor Factorization for Knowledge Graph Completion Authors: Ivana Balazevic, Carl Allen, Timothy Hospedales
Learning Cancer Outcomes from Heterogeneous Genomic Data Sources: An Adversarial Multi-task Learning Approach Authors: Safoora Yousefi, Amirreza Shaban, Mohamed Amgad, Lee Cooper
Continual adaptation for efficient machine communication Authors: Robert Hawkins, Minae Kwon, Dorsa Sadigh, Noah Goodman
Every Sample a Task: Pushing the Limits of Heterogeneous Models with Personalized Regression Authors: Ben Lengerich, Bryon Aragam, Eric Xing
Data Enrichment: Multi-task Learning in High Dimension with Theoretical Guarantees Authors: Amir Asiaee, Samet Oymak, Kevin R. Coombes, Arindam Banerjee
A Functional Extension of Multi-Output Learning Authors: Alex Lambert, Romain Brault, Zoltan Szabo, Florence d'Alche-Buc
Interpretable Robust Recommender Systems with Side Information Authors: Wenyu Chen, Zhechao Huang, Jason Cheuk Nam Liang, Zihao Xu
Personalized Student Stress Prediction with Deep Multi-Task Network Authors: Abhinav Shaw, Natcha Simsiri, Iman Dezbani, Madelina Fiterau, Tauhidur Rahaman
SuperTML: Domain Transfer from Computer Vision to Structured Tabular Data through Two-Dimensional Word Embedding Authors: Baohua Sun, Lin Yang, Wenhan Zhang, Michael Lin, Patrick Dong, Charles Young, Jason Dong
Goal-conditioned Imitation Learning Authors: Yiming Ding, Carlos Florensa, Mariano Phielipp, Pieter Abbeel
Tasks Without Borders: A New Approach to Online Multi-Task Learning Authors: Alexander Zimin, Christoph H. Lampert
The Role of Embedding-complexity in Domain-invariant Representations Authors: Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka
Lifelong Learning via Online Leverage Score Sampling Authors: Dan Teng, Sakyasingha Dasgupta
Connections Between Optimization in Machine Learning and Adaptive Control Authors: Joseph E. Gaudio, Travis E. Gibson, Anuradha M. Annaswamy, Michael A. Bolender, Eugene Lavretsky
Meta-Reinforcement Learning for Adaptive Autonomous Driving Authors: Yesmina Jaafra, Jean Luc Laurent, Aline Deruyver, Mohamed Saber Naceur
PAGANDA: An Adaptive Task-Independent Automatic Data Augmentation Authors: Boli Fang, Miao Jiang, Jerry Shen
Improving Relevance Prediction with Transfer Learning in Large-scale Retrieval Systems Authors: Ruoxi Wang, Zhe Zhao, Xinyang Yi, Ji Yang, Derek Zhiyuan Cheng, Lichan Hong, Steve Tjoa, Jieqi Kang, Evan Ettinger, Ed Chi
Federated Optimization for Heterogeneous Networks Authors: Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith
Learning Exploration Policies for Model-Agnostic Meta-Reinforcement Learning Authors: Swaminathan Gurumurthy, Sumit Kumar, Katia Sycara
A Meta Understanding of Meta-Learning Authors: Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark Campbell, Kilian Q. Weinberger
Multi-Task Learning via Task Multi-Clustering Authors: Andy Yan, Xin Wang, Ion Stoica, Joseph Gonzalez, Roy Fox
Prototypical Bregman Networks Authors: Kubra Cilingir, Brian Kulis
Differentiable Hebbian Plasticity for Continual Learning Authors: Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor
Active Multitask Learning with Committees Authors: Jingxi Xu, Da Tang, Tony Jebara
Progressive Memory Banks for Incremental Domain Adaptation Authors: Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang
Sub-policy Adaptation for Hierarchical Reinforcement Learning Authors: Alexander Li, Carlos Florensa, Pieter Abbeel
Learning to learn to communicate Authors: Ryan Lowe, Abhinav Gupta, Jakob Foerster, Douwe Kiela, Joelle Pineau
Author Information
Ivana Balazevic (University of Edinburgh)
Minae Kwon (Stanford University)
Benjamin Lengerich (Carnegie Mellon University)
Amir Asiaee (The Ohio State University)
Alex Lambert (Télécom ParisTech)
Wenyu Chen (MIT)
Yiming Ding (University of California, Berkeley)
Carlos Florensa (UC Berkeley)
Joseph E Gaudio (MIT)
Yesmina Jaafra (Segula Technologies - Icube Laboratory)
Boli Fang (Indiana University)
Ruoxi Wang (Google AI)
Tian Li (CMU)
SWAMINATHAN GURUMURTHY (Carnegie Mellon University)
Andy Yan (University of California, Berkeley)
Kubra Cilingir (Boston University / Amazon)
Vithursan (Vithu) Thangarasa (University of Guelph/ Vector Institute)
I'm currently a Graduate Student Research at the University of Guelph and Vector Institute for Artificial Intelligence working on continual learning algorithms and overcoming catastrophic forgetting for deep neural networks. As a graduate student advised by Dr. Graham W. Taylor, I am working towards an MASc at University of Guelph's Machine Learning Research Group (MLRG) and completed my BEng. in Engineering Systems and Computing, along with six awesome internships at Uber AI, Tesla, Scotiabank, ON Semiconductor, Evertz Microsystems, and Jamdeo.
Alexander Li (UC Berkeley)
Interested in representation learning, unsupervised learning, meta-learning, and hierarchical reinforcement learning.
Ryan Lowe (Mila, McGill University)
More from the Same Authors
-
2023 : Auto-Aligning Multiagent Incentives with Global Objectives »
Minae Kwon · John Agapiou · Edgar Duéñez-Guzmán · Romuald Elie · Georgios Piliouras · Kalesha Bullard · Ian Gemp -
2023 Workshop: Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities »
Zheng Xu · Peter Kairouz · Bo Li · Tian Li · John Nguyen · Jianyu Wang · Shiqiang Wang · Ayfer Ozgur -
2022 Poster: Private Adaptive Optimization with Side information »
Tian Li · Manzil Zaheer · Sashank Jakkam Reddi · Virginia Smith -
2022 Spotlight: Private Adaptive Optimization with Side information »
Tian Li · Manzil Zaheer · Sashank Jakkam Reddi · Virginia Smith -
2021 Poster: Heterogeneity for the Win: One-Shot Federated Clustering »
Don Kurian Dennis · Tian Li · Virginia Smith -
2021 Poster: Ditto: Fair and Robust Federated Learning Through Personalization »
Tian Li · Shengyuan Hu · Ahmad Beirami · Virginia Smith -
2021 Spotlight: Ditto: Fair and Robust Federated Learning Through Personalization »
Tian Li · Shengyuan Hu · Ahmad Beirami · Virginia Smith -
2021 Spotlight: Heterogeneity for the Win: One-Shot Federated Clustering »
Don Kurian Dennis · Tian Li · Virginia Smith -
2021 Poster: Targeted Data Acquisition for Evolving Negotiation Agents »
Minae Kwon · Siddharth Karamcheti · Mariano-Florentino Cuellar · Dorsa Sadigh -
2021 Spotlight: Targeted Data Acquisition for Evolving Negotiation Agents »
Minae Kwon · Siddharth Karamcheti · Mariano-Florentino Cuellar · Dorsa Sadigh -
2020 : Brainstorming & Closing »
Mayoore Jaiswal · Ryan Lowe · Jesse Dodge · Jessica Forde · Rosanne Liu -
2020 : Q&A: Peter Henderson »
Peter Henderson · Mayoore Jaiswal · Ryan Lowe -
2020 Workshop: MLRetrospectives: A Venue for Self-Reflection in ML Research »
Jessica Forde · Jesse Dodge · Mayoore Jaiswal · Rosanne Liu · Ryan Lowe · Rosanne Liu · Joelle Pineau · Yoshua Bengio -
2020 : Welcome »
Ryan Lowe · Jessica Forde -
2020 Poster: Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses »
Pierre Laforgue · Alex Lambert · Luc Brogat-Motte · Florence d'Alche-Buc -
2020 Poster: Deep Divergence Learning »
Kubra Cilingir · Rachel Manzelli · Brian Kulis -
2019 : Contributed Talk: Continual Adaptation for Efficient Machine Communication »
Minae Kwon -
2019 : Contributed Talk: Improving Relevance Prediction with Transfer Learning in Large-scale Retrieval Systems »
Ruoxi Wang -
2019 : Poster Session »
Boli Fang · Ananth Balashankar · Sonam Damani · Emma Beauxis-Aussalet · Nan Wu · Elizabeth Bondi · Marc Rußwurm · David Ruhe · Nripsuta Saxena · Katie Spoon -
2019 Poster: Unifying Orthogonal Monte Carlo Methods »
Krzysztof Choromanski · Mark Rowland · Wenyu Chen · Adrian Weller -
2019 Oral: Unifying Orthogonal Monte Carlo Methods »
Krzysztof Choromanski · Mark Rowland · Wenyu Chen · Adrian Weller -
2018 Poster: Automatic Goal Generation for Reinforcement Learning Agents »
Carlos Florensa · David Held · Xinyang Geng · Pieter Abbeel -
2018 Oral: Automatic Goal Generation for Reinforcement Learning Agents »
Carlos Florensa · David Held · Xinyang Geng · Pieter Abbeel