Eunho Yang

Orcid: 0000-0003-2188-0169

According to our database1, Eunho Yang authored at least 124 papers between 2006 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective.
CoRR, 2024

REBIND: Enhancing ground-state molecular conformation via force-based graph rewiring.
CoRR, 2024

Augmentation-Driven Metric for Balancing Preservation and Modification in Text-Guided Image Editing.
CoRR, 2024

Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning.
CoRR, 2024

LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding.
CoRR, 2024

LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices.
CoRR, 2024

AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler.
CoRR, 2024

Unleashing the Potential of Text-attributed Graphs: Automatic Relation Decomposition via Large Language Models.
CoRR, 2024

No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization.
CoRR, 2024

SeamsTalk: Seamless Talking Face Generation via Flow-Guided Inpainting.
IEEE Access, 2024

Time Series Classification With Large Language Models via Linguistic Scaffolding.
IEEE Access, 2024

PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

TEDDY: Trimming Edges with Degree-based Discrimination Strategy.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

CloudFixer: Test-Time Adaptation for 3D Point Clouds via Diffusion-Guided Geometric Transformation.
Proceedings of the Computer Vision - ECCV 2024, 2024

TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias.
Proceedings of the Computer Vision - ECCV 2024, 2024

Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Learning Polymorphic Neural ODEs With Time-Evolving Mixture.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Face-StyleSpeech: Improved Face-to-Voice latent mapping for Natural Zero-shot Speech Synthesis from a Face Image.
CoRR, 2023

BackTrack: Robust template update via Backward Tracking of candidate template.
CoRR, 2023

Deep Self-Supervised Diversity Promoting Learning on Hierarchical Hyperspheres for Regularization.
IEEE Access, 2023

Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GEX: A flexible method for approximating influence via Geometric Ensemble.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy Minimization.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

ZET-Speech: Zero-shot adaptive Emotion-controllable Text-to-Speech Synthesis with Diffusion and Style-based Models.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

RGE: A Repulsive Graph Rectification for Node Classification via Influence.
Proceedings of the International Conference on Machine Learning, 2023

Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation.
Proceedings of the International Conference on Machine Learning, 2023

Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

PC-Adapter: Topology-Aware Adapter for Efficient Domain Adaption on Point Clouds with Rectified Pseudo-label.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Weavspeech: Data Augmentation Strategy For Automatic Speech Recognition Via Semantic-Aware Weaving.
Proceedings of the IEEE International Conference on Acoustics, 2023

Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

BiasAdv: Bias-Adversarial Augmentation for Model Debiasing.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Towards the Practical Utility of Federated Learning in the Medical Domain.
Proceedings of the Conference on Health, Inference, and Learning, 2023

2022
A Simple Framework for Robust Out-of-Distribution Detection.
IEEE Access, 2022

Does it Really Generalize Well on Unseen Data? Systematic Evaluation of Relational Triple Extraction Methods.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification.
Proceedings of the International Conference on Machine Learning, 2022

Set Based Stochastic Subsampling.
Proceedings of the International Conference on Machine Learning, 2022

Online Coreset Selection for Rehearsal-based Continual Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Model-augmented Prioritized Experience Replay.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Online Hyperparameter Meta-Learning with Hypergradient Distillation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Model-Augmented Q-learning.
CoRR, 2021

Compressed Sensing via Measurement-Conditional Generative Models.
IEEE Access, 2021

Adaptive Proximal Gradient Methods for Structured Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multi-Domain Knowledge Distillation via Uncertainty-Matching for End-to-End ASR Models.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Federated Continual Learning with Weighted Inter-client Transfer.
Proceedings of the 38th International Conference on Machine Learning, 2021

Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation.
Proceedings of the 38th International Conference on Machine Learning, 2021

FedMix: Approximation of Mixup under Mean Augmented Federated Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Learning to Sample with Local and Global Contexts in Experience Replay Buffer.
Proceedings of the 9th International Conference on Learning Representations, 2021

Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Mutually-Constrained Monotonic Multihead Attention for Online ASR.
Proceedings of the IEEE International Conference on Acoustics, 2021

Distilling Linguistic Context for Language Model Compression.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning How Long to Wait: Adaptively-Constrained Monotonic Multihead Attention for Streaming ASR.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021

GTA: Graph Truncated Attention for Retrosynthesis.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
A General Family of Stochastic Proximal Gradient Methods for Deep Learning.
CoRR, 2020

Stochastic Subset Selection.
CoRR, 2020

Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning.
CoRR, 2020

Federated Semi-Supervised Learning with Inter-Client Consistency.
CoRR, 2020

Federated Continual Learning with Adaptive Parameter Communication.
CoRR, 2020

Attribution Preservation in Network Compression for Reliable Network Interpretation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Bootstrapping neural processes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Neural Complexity Measures.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Time-Reversal Symmetric ODE Network.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cost-Effective Interactive Attention Learning with Neural Attention Processes.
Proceedings of the 37th International Conference on Machine Learning, 2020

Scalable and Order-robust Continual Learning with Additive Parameter Decomposition.
Proceedings of the 8th International Conference on Learning Representations, 2020

Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Meta Dropout: Learning to Perturb Latent Features for Generalization.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks.
Proceedings of the 8th International Conference on Learning Representations, 2020

Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck.
CoRR, 2019

Sparsity Normalization: Stabilizing the Expected Outputs of Deep Networks.
CoRR, 2019

Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks.
CoRR, 2019

Meta Dropout: Learning to Perturb Features for Generalization.
CoRR, 2019

Stochastic Gradient Methods with Block Diagonal Matrix Adaptation.
CoRR, 2019

ORACLE: Order Robust Adaptive Continual LEarning.
CoRR, 2019

Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Spectral Approximate Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Mixed Effect Composite RNN-GP: A Personalized and Reliable Prediction Model for Healthcare.
CoRR, 2018

Adaptive Network Sparsification via Dependent Variational Beta-Bernoulli Dropout.
CoRR, 2018

Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

DropMax: Adaptive Variational Softmax.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Uncertainty-Aware Attention for Reliable Interpretation and Prediction.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Asymmetric Multi-task Feature Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Lifelong Learning with Dynamically Expandable Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
DropMax: Adaptive Stochastic Softmax.
CoRR, 2017

Why Pay More When You Can Pay Less: A Joint Learning Framework for Active Feature Acquisition and Classification.
CoRR, 2017

Sequential Local Learning for Latent Graphical Models.
CoRR, 2017

Learning Task Clusters via Sparsity Grouped Multitask Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity.
Proceedings of the 34th International Conference on Machine Learning, 2017

Ordinal Graphical Models: A Tale of Two Approaches.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
XMRF: an R package to fit Markov Networks to high-throughput genetics data.
BMC Syst. Biol., 2016

Asymmetric Multi-task Learning based on Task Relatedness and Confidence.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Graphical models via univariate exponential family distributions.
J. Mach. Learn. Res., 2015

Closed-form Estimators for High-dimensional Generalized Linear Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Elementary Estimators for Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Elementary Estimators for Sparse Covariance Matrices and other Structured Moments.
Proceedings of the 31th International Conference on Machine Learning, 2014

Elementary Estimators for High-Dimensional Linear Regression.
Proceedings of the 31th International Conference on Machine Learning, 2014

Mixed Graphical Models via Exponential Families.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
On Poisson Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Conditional Random Fields via Univariate Exponential Families.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Dirty Statistical Models.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On Robust Estimation of High Dimensional Generalized Linear Models.
Proceedings of the IJCAI 2013, 2013

2012
Perturbation based Large Margin Approach for Ranking.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Graphical Models via Generalized Linear Models.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
On NDCG Consistency of Listwise Ranking Methods.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

On the Use of Variational Inference for Learning Discrete Graphical Model.
Proceedings of the 28th International Conference on Machine Learning, 2011

2009
Tele-conference using advanced tool on future IP.
Proceedings of the 2009 International Conference on Information Networking, 2009

Selfish retransmission protocol in an IR-UWB system.
Proceedings of the 2009 International Conference on Information Networking, 2009

2008
On selfish behavior using asymmetric carrier sensing in IEEE 802.11 wireless networks.
Proceedings of the LCN 2008, 2008

The Bandwidth Feasibility Test Method for Ubiquitous Teleconference on Future Internet.
Proceedings of the IEEE International Symposium on Parallel and Distributed Processing with Applications, 2008

2006
EIMD: A New Congestion Control for Fast Long-Distance Networks.
Proceedings of the Information Networking, 2006


  Loading...