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Poster
Mon 1:00 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
Poster
Mon 1:00 Towards Impartial Multi-task Learning
Liyang Liu, Yi Li, Zhanghui Kuang, Jing-Hao Xue, Yimin Chen, Wenming Yang, Qingmin Liao, Wei Zhang
Spotlight
Mon 3:30 Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
Poster
Mon 9:00 Structured Prediction as Translation between Augmented Natural Languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, RISHITA ANUBHAI, Cicero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Poster
Mon 9:00 Planning from Pixels using Inverse Dynamics Models
Keiran Paster, Sheila McIlraith, Jimmy Ba
Poster
Mon 9:00 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Spotlight
Mon 13:40 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Poster
Mon 17:00 One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang
Spotlight
Mon 19:45 Structured Prediction as Translation between Augmented Natural Languages
Giovanni Paolini, Ben Athiwaratkun, Jason Krone, Jie Ma, Alessandro Achille, RISHITA ANUBHAI, Cicero Nogueira dos Santos, Bing Xiang, Stefano Soatto
Spotlight
Mon 21:46 The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
Poster
Tue 1:00 Bayesian Context Aggregation for Neural Processes
Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, Gerhard Neumann
Poster
Tue 1:00 Auxiliary Learning by Implicit Differentiation
Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya
Poster
Tue 1:00 Learning the Pareto Front with Hypernetworks
Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik
Poster
Tue 17:00 Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis
Zhipeng Bao, Yu-Xiong Wang, Martial Hebert
Poster
Wed 9:00 HyperGrid Transformers: Towards A Single Model for Multiple Tasks
Yi Tay, Zhe Zhao, Dara Bahri, Donald Metzler, DA-CHENG Juan
Poster
Wed 9:00 Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning
Valerie Chen, Abhinav Gupta, Kenny Marino
Poster
Wed 17:00 In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang
Poster
Thu 1:00 Impact of Representation Learning in Linear Bandits
Jiaqi Yang, Wei Hu, Jason Lee, Simon Du
Poster
Thu 9:00 Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models
Zirui Wang, Yulia Tsvetkov, Orhan Firat, Yuan Cao
Poster
Thu 9:00 Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data
Jonathan Pilault, Amine EL hattami, Chris J Pal
Workshop
Fri 12:05 Weakly Supervised Multi-task Learning for Concept-based Explainability
Vladimir Balayan
Workshop
Fri 12:20 Weakly Supervised Multi-task Learning for Concept-based Explainability - Q&A
Workshop
Multi-Task Reinforcement Learning with Context-based Representations
Shagun Sodhani, Amy Zhang, Joelle Pineau
Workshop
CoMPS: Continual Meta Policy Search
Glen Berseth, Zhiwei Zhang, Chelsea Finn, Sergey Levine
Workshop
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention
Abhishek Gupta, Justin Yu, Vikash Kumar, Tony Zhao, Kelvin Xu, Aaron Rovinsky, Thomas Devlin, Sergey Levine
Workshop
Differentially Private Multi-Task Learning
Shengyuan Hu, Steven Wu, Virginia Smith