Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning

NeurIPS 2021 Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning Youngkyu Hong, Eunho Yang  Datasets for training machine learning models tend to be biased unless the data is collected with complete care. In such a biased dataset, models are susceptible to...

Task-Adaptive Neural Network Retrieval with Meta-Contrastive Learning

NeurIPS 2021 Task-Adaptive Neural Network Retrieval with Meta-Contrastive Learning Wonyong Jeong, Hayeon Lee,Gun Park, Eunyoung Hyung, Jinheon Baek andSung Ju Hwang  Most conventional Neural Architecture Search (NAS) approaches are limited in that they only generate architectures...

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning

IJCAI 2021 RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning Hankook Lee, Sungsoo Ahn, Seung-Woo Seo, You Young Song, Eunho Yang, Sung Ju Hwang and Jinwoo Shin  Retrosynthesis, of which the goal is to find a set of reactants for synthesizing a target p...

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets

ICLR 2021 Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets Hayeon Lee, Eunyoung Hyung and Sung Ju Hwang  Despite the success of recent Neural Architecture Search (NAS) methods on various tasks which have shown to output networks that largely outperfo...

Mutually-Constrained Monotonic Multihead Attention for Online ASR

ICASSP 2021 Mutually-Constrained Monotonic Multihead Attention for Online ASR  Jaeyun Song, Hajin Shim, Eunho Yang   Despite the feature of real-time decoding, Monotonic Multihead Attention (MMA) shows comparable performance to the state-of-the-art offline methods ...

Multi-domain Knowledge Distillation via Uncertainty-Matching for End-to-End ASR Models

INTERSPEECH 2021 Multi-domain Knowledge Distillation via Uncertainty-Matching for End-to-End ASR Models Ho-Gyeong Kim, Min-Joong Lee, Hoshik Lee, Tae Gyoon Kang, Jihyun Lee, Eunho Yang and Sung Ju Hwang  Knowledge Distillation basically matches predictive distributions of st...

Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding

NeurIPS 2021 Mini-Batch Consistent Slot Set Encoder for Scalable Set Encoding Bruno Andreis, Jeffrey Willette, Juho Lee and Sung Ju Hwang  Most existing set encoding algorithms operate under the assumption that all the elements of the set are accessible during training and infere...

Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation

ICML 2021 Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang and Sung Ju Hwang  With rapid progress in neural text-to-speech (TTS) models, personalized speech generation is now in high demand for many applications. For pract...

Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning

ICLR 2021 Meta-GMVAE: Mixture of Gaussian VAE for Unsupervised Meta-Learning Dong Bok Lee, Dongchan Min, Seanie Lee and Sung Ju Hwang  Unsupervised learning aims to learn meaningful representations from unlabeled data which can captures its intrinsic structure, that can be transf...

Learning to Sample with Local and Global Contexts in Experience Replay Buffers

ICLR 2021 Learning to Sample with Local and Global Contexts in Experience Replay Buffers Youngmin Oh, Kimin Lee, Jinwoo Shin, Eunho Yang, Sung Ju Hwang  Experience replay, which enables the agents to remember and reuse experience from the past, has played a significant role in th...