Decoupled Training for Long-Tailed Classification With Stochastic Representations

ICLR 2023 Decoupled Training for Long-Tailed Classification With Stochastic Representations  Giung Nam, Sunguk Jang, Juho Lee   Decoupling representation learning and classifier learning has been shown to be effective in classification with long-tailed data. There ...

Skill-based Meta-Reinforcement Learning

ICLR 2022 Skill-based Meta-Reinforcement Learning Taewook Nam, Shao-Hua Sun, Karl Pertsch, Sung Ju Hwang, Joseph J Lim    While deep reinforcement learning methods have shown impressive results in robot learning, their sample inefficiency makes the learning of complex, long-...

Representational Continuity for Unsupervised Continual Learning

ICLR 2022 Representational Continuity for Unsupervised Continual Learning Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang  Continual learning (CL) aims to learn a sequence of tasks without forgetting the previously acquired knowledge. However, recent CL advanc...

Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning

ICLR 2022 Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning Seanie Lee, Hae Beom Lee, Juho Lee, Sung Ju Hwang  Multilingual models jointly pretrained on multiple languages have achieved remarkable performance on various multilingual downstream tasks. Mor...

Rethinking the Representational Continuity: Towards Unsupervised Continual Learning

ICLR 2022 Rethinking the Representational Continuity: Towards Unsupervised Continual Learning Divyam Madaan, Jaehong Yoon, Yuanchun Li, Yunxin Liu, Sung Ju Hwang  Continual learning (CL) aims to learn a sequence of tasks without forgetting the previously acquired knowledge. ...

Online Hyperparameter Meta-Learning with Hypergradient Distillation

ICLR 2022 Online Hyperparameter Meta-Learning with Hypergradient Distillation Hae Beom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy Hospedales, Sung Ju Hwang    Many gradient-based meta-learning methods assume a set of parameters that do not participate in inner-optim...

Online Coreset Selection for Rehearsal-based Continual Learning

ICLR 2022 Online Coreset Selection for Rehearsal-based Continual Learning Jaehong Yoon, Divyam Madaan, Eunho Yang, Sung Ju Hwang  A dataset is a shred of crucial evidence to describe a task. However, each data point in the dataset does not have the same potential, as some of...

Model-augmented Prioritized Experience Replay

ICLR 2022 Model-augmented Prioritized Experience Replay Youngmin Oh, Jinwoo Shin, Eunho Yang, Sung Ju Hwang    Experience replay is an essential component in off-policy model-free reinforcement learning (MfRL). Due to its effectiveness, various methods for calculating priori...

Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty

ICLR 2022 Meta Learning Low Rank Covariance Factors for Energy Based Deterministic Uncertainty Jeffrey Ryan Willette, Hae Beom Lee, Juho Lee, Sung Ju Hwang  Numerous recent works utilize bi-Lipschitz regularization of neural network layers to preserve relative distances between d...

GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification

ICLR 2022 GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification Joonhyung Park*, Jaeyun Song*, Eunho Yang (*: equal contribution)  In many real-world node classification scenarios, nodes are highly class-imbalanced, where graph neural networks (G...