
Eunho Yang
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2020 – today
- 2020
- [c43]Ingyo Chung, Saehoon Kim, Juho Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang:
Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare. AAAI 2020: 3649-3657 - [c42]Haebeom Lee, Hayeon Lee, Donghyun Na, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang:
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks. ICLR 2020 - [c41]Haebeom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang:
Meta Dropout: Learning to Perturb Latent Features for Generalization. ICLR 2020 - [c40]Joonyoung Yi, Juhyuk Lee, Kwang Joon Kim, Sung Ju Hwang, Eunho Yang:
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks. ICLR 2020 - [c39]Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang:
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition. ICLR 2020 - [c38]Jay Heo, Junhyeon Park, Hyewon Jeong, Kwang Joon Kim, Juho Lee, Eunho Yang, Sung Ju Hwang:
Cost-Effective Interactive Attention Learning with Neural Attention Processes. ICML 2020: 4228-4238 - [c37]In Huh, Eunho Yang, Sung Ju Hwang, Jinwoo Shin:
Time-Reversal Symmetric ODE Network. NeurIPS 2020 - [c36]Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang, Jinwoo Shin:
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning. NeurIPS 2020 - [c35]Youngsung Kim, Jinwoo Shin, Eunho Yang, Sung Ju Hwang:
Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning. NeurIPS 2020 - [c34]Yoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang, Seungjin Choi:
Neural Complexity Measures. NeurIPS 2020 - [c33]Juho Lee, Yoonho Lee, Jungtaek Kim, Eunho Yang, Sung Ju Hwang, Yee Whye Teh:
Bootstrapping neural processes. NeurIPS 2020 - [c32]Geondo Park, June Yong Yang, Sung Ju Hwang, Eunho Yang:
Attribution Preservation in Network Compression for Reliable Network Interpretation. NeurIPS 2020 - [i32]Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang:
Federated Continual Learning with Adaptive Parameter Communication. CoRR abs/2003.03196 (2020) - [i31]Jay Heo, Junhyeon Park, Hyewon Jeong, Kwang Joon Kim, Juho Lee, Eunho Yang, Sung Ju Hwang:
Cost-effective Interactive Attention Learning with Neural Attention Processes. CoRR abs/2006.05419 (2020) - [i30]Wonyong Jeong, Jaehong Yoon, Eunho Yang, Sung Ju Hwang:
Federated Semi-Supervised Learning with Inter-Client Consistency. CoRR abs/2006.12097 (2020) - [i29]Minyoung Song, Jaehong Yoon, Eunho Yang, Sung Ju Hwang:
Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning. CoRR abs/2006.12139 (2020) - [i28]Tuan A. Nguyen, Hyewon Jeong, Eunho Yang, Sung Ju Hwang:
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning. CoRR abs/2006.12777 (2020) - [i27]Tuan A. Nguyen, Bruno Andreis, Juho Lee, Eunho Yang, Sung Ju Hwang:
Stochastic Subset Selection. CoRR abs/2006.14222 (2020) - [i26]Kyung-Su Kim, Jung Hyun Lee, Eunho Yang:
Compressed Sensing via Measurement-Conditional Generative Models. CoRR abs/2007.00873 (2020) - [i25]Kyung-Su Kim, Aurélie C. Lozano, Eunho Yang:
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks. CoRR abs/2007.00884 (2020) - [i24]Youngmin Oh, Kimin Lee, Jinwoo Shin, Eunho Yang, Sung Ju Hwang:
Learning to Sample with Local and Global Contexts in Experience Replay Buffer. CoRR abs/2007.07358 (2020) - [i23]Jihun Yun, Aurelie C. Lozano, Eunho Yang:
A General Family of Stochastic Proximal Gradient Methods for Deep Learning. CoRR abs/2007.07484 (2020) - [i22]Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang, Jinwoo Shin:
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning. CoRR abs/2007.08844 (2020) - [i21]In Huh, Eunho Yang, Sung Ju Hwang, Jinwoo Shin:
Time-Reversal Symmetric ODE Network. CoRR abs/2007.11362 (2020) - [i20]Youngsung Kim, Jinwoo Shin, Eunho Yang, Sung Ju Hwang:
Few-shot Visual Reasoning with Meta-analogical Contrastive Learning. CoRR abs/2007.12020 (2020) - [i19]Yoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang, Seungjin Choi:
Neural Complexity Measures. CoRR abs/2008.02953 (2020) - [i18]Juho Lee, Yoonho Lee, Jungtaek Kim, Eunho Yang, Sung Ju Hwang, Yee Whye Teh:
Bootstrapping Neural Processes. CoRR abs/2008.02956 (2020) - [i17]Geondo Park, June Yong Yang, Sung Ju Hwang, Eunho Yang:
Attribution Preservation in Network Compression for Reliable Network Interpretation. CoRR abs/2010.15054 (2020)
2010 – 2019
- 2019
- [c31]Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Eunho Yang, Sung Ju Hwang, Yi Yang:
Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning. ICLR (Poster) 2019 - [c30]Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin:
Spectral Approximate Inference. ICML 2019: 5052-5061 - [c29]Jihun Yun, Peng Zheng, Eunho Yang, Aurelie C. Lozano, Aleksandr Y. Aravkin:
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. ICML 2019: 7242-7251 - [i16]Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang:
ORACLE: Order Robust Adaptive Continual LEarning. CoRR abs/1902.09432 (2019) - [i15]Sejun Park, Eunho Yang, Se-Young Yun, Jinwoo Shin:
Spectral Approximate Inference. CoRR abs/1905.05348 (2019) - [i14]Jihun Yun, Aurelie C. Lozano, Eunho Yang:
Stochastic Gradient Methods with Block Diagonal Matrix Adaptation. CoRR abs/1905.10757 (2019) - [i13]Haebeom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang:
Meta Dropout: Learning to Perturb Features for Generalization. CoRR abs/1905.12914 (2019) - [i12]Donghyun Na, Haebeom Lee, Saehoon Kim, Minseop Park, Eunho Yang, Sung Ju Hwang:
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks. CoRR abs/1905.12917 (2019) - [i11]Joonyoung Yi, Juhyuk Lee, Sung Ju Hwang, Eunho Yang:
Sparsity Normalization: Stabilizing the Expected Outputs of Deep Networks. CoRR abs/1906.00150 (2019) - [i10]Sungyub Kim, Yongsu Baek, Sung Ju Hwang, Eunho Yang:
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck. CoRR abs/1906.03118 (2019) - [i9]Jihun Yun, Jung Hyun Lee, Sung Ju Hwang, Eunho Yang:
Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization. CoRR abs/1911.12990 (2019) - 2018
- [c28]Jaehong Yoon, Eunho Yang, Jeongtae Lee, Sung Ju Hwang:
Lifelong Learning with Dynamically Expandable Networks. ICLR (Poster) 2018 - [c27]Haebeom Lee, Eunho Yang, Sung Ju Hwang:
Deep Asymmetric Multi-task Feature Learning. ICML 2018: 2962-2970 - [c26]Jay Heo, Haebeom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang:
Uncertainty-Aware Attention for Reliable Interpretation and Prediction. NeurIPS 2018: 917-926 - [c25]Haebeom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang:
DropMax: Adaptive Variational Softmax. NeurIPS 2018: 927-937 - [c24]Hajin Shim, Sung Ju Hwang, Eunho Yang:
Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding. NeurIPS 2018: 1375-1385 - [i8]Jay Heo, Haebeom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang, Sung Ju Hwang:
Uncertainty-Aware Attention for Reliable Interpretation and Prediction. CoRR abs/1805.09653 (2018) - [i7]Juho Lee, Saehoon Kim, Jaehong Yoon, Haebeom Lee, Eunho Yang, Sung Ju Hwang:
Adaptive Network Sparsification via Dependent Variational Beta-Bernoulli Dropout. CoRR abs/1805.10896 (2018) - [i6]Ingyo Chung, Saehoon Kim, Juho Lee, Sung Ju Hwang, Eunho Yang:
Mixed Effect Composite RNN-GP: A Personalized and Reliable Prediction Model for Healthcare. CoRR abs/1806.01551 (2018) - 2017
- [c23]Arun Sai Suggala, Eunho Yang, Pradeep Ravikumar:
Ordinal Graphical Models: A Tale of Two Approaches. ICML 2017: 3260-3269 - [c22]Eunho Yang, Aurélie C. Lozano:
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity. ICML 2017: 3911-3920 - [c21]Meghana Kshirsagar, Eunho Yang, Aurélie C. Lozano:
Learning Task Clusters via Sparsity Grouped Multitask Learning. ECML/PKDD (2) 2017: 673-689 - [i5]Sejun Park, Eunho Yang, Jinwoo Shin:
Sequential Local Learning for Latent Graphical Models. CoRR abs/1703.04082 (2017) - [i4]Haebeom Lee, Eunho Yang, Sung Ju Hwang:
Deep Asymmetric Multi-task Feature Learning. CoRR abs/1708.00260 (2017) - [i3]Jeongtae Lee, Jaehong Yoon, Eunho Yang, Sung Ju Hwang:
Lifelong Learning with Dynamically Expandable Networks. CoRR abs/1708.01547 (2017) - [i2]Hajin Shim, Sung Ju Hwang, Eunho Yang:
Why Pay More When You Can Pay Less: A Joint Learning Framework for Active Feature Acquisition and Classification. CoRR abs/1709.05964 (2017) - [i1]Haebeom Lee, Juho Lee, Eunho Yang, Sung Ju Hwang:
DropMax: Adaptive Stochastic Softmax. CoRR abs/1712.07834 (2017) - 2016
- [j2]Ying-Wooi Wan, Genevera I. Allen, Yulia Baker, Eunho Yang, Pradeep Ravikumar, Matthew Anderson
, Zhandong Liu
:
XMRF: an R package to fit Markov Networks to high-throughput genetics data. BMC Syst. Biol. 10(S-3): 69 (2016) - [c20]Giwoong Lee, Eunho Yang, Sung Ju Hwang:
Asymmetric Multi-task Learning based on Task Relatedness and Confidence. ICML 2016: 230-238 - 2015
- [j1]Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu:
Graphical models via univariate exponential family distributions. J. Mach. Learn. Res. 16: 3813-3847 (2015) - [c19]Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar:
Closed-form Estimators for High-dimensional Generalized Linear Models. NIPS 2015: 586-594 - [c18]Eunho Yang, Aurelie C. Lozano:
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso. NIPS 2015: 2602-2610 - 2014
- [c17]Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu:
Mixed Graphical Models via Exponential Families. AISTATS 2014: 1042-1050 - [c16]Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar:
Elementary Estimators for High-Dimensional Linear Regression. ICML 2014: 388-396 - [c15]Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar:
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments. ICML 2014: 397-405 - [c14]Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar:
Elementary Estimators for Graphical Models. NIPS 2014: 2159-2167 - 2013
- [c13]Eunho Yang, Ambuj Tewari, Pradeep Ravikumar:
On Robust Estimation of High Dimensional Generalized Linear Models. IJCAI 2013: 1834-1840 - [c12]Eunho Yang, Pradeep Ravikumar:
Dirty Statistical Models. NIPS 2013: 611-619 - [c11]Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu:
Conditional Random Fields via Univariate Exponential Families. NIPS 2013: 683-691 - [c10]Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu:
On Poisson Graphical Models. NIPS 2013: 1718-1726 - 2012
- [c9]Eunho Yang, Pradeep Ravikumar, Genevera I. Allen, Zhandong Liu:
Graphical Models via Generalized Linear Models. NIPS 2012: 1367-1375 - [c8]Eunho Yang, Ambuj Tewari, Pradeep Ravikumar:
Perturbation based Large Margin Approach for Ranking. AISTATS 2012: 1358-1366 - 2011
- [c7]Eunho Yang, Pradeep Ravikumar:
On the Use of Variational Inference for Learning Discrete Graphical Model. ICML 2011: 1009-1016 - [c6]Pradeep Ravikumar, Ambuj Tewari, Eunho Yang:
On NDCG Consistency of Listwise Ranking Methods. AISTATS 2011: 618-626
2000 – 2009
- 2009
- [c5]Jimyung Kang, Eunho Yang, Youngjin Park, Soonwoo Lee, Yonghwa Kim, Kwanho Kim:
Selfish retransmission protocol in an IR-UWB system. ICOIN 2009: 1-5 - [c4]Sunglim Lee, Koji Okamura, Eunho Yang:
Tele-conference using advanced tool on future IP. ICOIN 2009: 1-3 - 2008
- [c3]Sunglim Lee, Koji Okamura, Eunho Yang:
The Bandwidth Feasibility Test Method for Ubiquitous Teleconference on Future Internet. ISPA 2008: 790-794 - [c2]Eunho Yang, Jaehyuk Choi, Sunglim Lee:
On selfish behavior using asymmetric carrier sensing in IEEE 802.11 wireless networks. LCN 2008: 527-529 - 2006
- [c1]Eunho Yang, Seong-il Hahm, Seongho Cho, Chong-kwon Kim, Pillwoo Lee:
EIMD: A New Congestion Control for Fast Long-Distance Networks. ICOIN 2006: 379-388
Coauthor Index

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