ALL
CONFERENCE
JOURNAL
ETC
AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler
Changhun Kim*, Taewon Kim*, Seungyeon Woo, June Yong Yang, Eunho Yang (*: equal contribution)
NeurIPS Workshop on Table Representation Learning (NeurIPSW-TRL),
2024
[paper]
EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries
Sunjun Kweon, Jiyoun Kim, Heeyoung Kwak, Dongchul Cha, Hangyul Yoon, Kwanghyun Kim, Jeewon Yang, Seunghyun Won, Edward Choi
Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track,
2024
[paper]
[code]
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective
Yeonsung Jung*, Jaeyun Song*, June Yong Yang, Jin-Hwa Kim, Sung-Yub Kim, Eunho Yang (*: equal contribution)
Conference on Neural Information Processing Systems (NeurIPS),
2024
PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning
Gyeongman Kim, Doohyuk Jang and Eunho Yang
Findings of the Conference on Empirical Methods in Natural Language Processing (EMNLP Findings),
2024
[paper]
[code]
Time Series Classification with Large Language Models via Linguistic Scaffolding
Hyeongwon Jang*, June Yong Yang*, Jaeryong Hwang, Eunho Yang (*: equal contribution)
IEEE Access,
2024
[paper]
CloudFixer: Test-Time Adaptation for 3D Point Clouds via Diffusion-Guided Geometric Transformation
Hajin Shim*, Changhun Kim* and Eunho Yang (*: equal contribution)
European Conference on Computer Vision (ECCV),
2024
[paper]
[code]
TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
Sanghyun Jo*, Soohyun Ryu*, Sungyub Kim, Eunho Yang and Kyungsu Kim (*: equal contribution)
European Conference on Computer Vision (ECCV),
2024
[paper]
PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency
Yeonsung Jung, Heecheol Yun, Joonhyung Park, Jin-Hwa Kim and Eunho Yang
International Conference on Machine Learning (ICML),
2024
[paper]
Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
JungEun Kim*, Hangyul Yoon*, Geondo Park, Kyungsu Kim and Eunho Yang (*: equal contribution)
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
2024
[paper]
[code]
Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication
June Yong Yang*, Geondo Park*, Joowon Kim, Hyeongwon Jang and Eunho Yang (*: equal contribution)
International Conference on Learning Representations (ICLR),
2024
[paper]
TEDDY: Trimming Edges with Degree-based Discrimination strategY
Hyunjin Seo*, Jihun Yun* and Eunho Yang (*: equal contribution)
International Conference on Learning Representations (ICLR),
2024
[paper]
[code]
SeamsTalk: Seamless Talking Face Generation via Flow-Guided Inpainting
Yeongho Jeong, Gyeongman Kim, Doohyuk Jang, Jaeryong Hwang and Eunho Yang
IEEE Access,
2024
[paper]
ProxyDet: Synthesizing Proxy Novel Classes via Classwise Mixup for Open Vocabulary Object Detection
Joonhyun Jeong, Geondo Park, Jayeon Yoo, Hyungsik Jung and Heesu Kim
AAAI Conference on Artificial Intelligence (AAAI),
2024
[paper]
[code]
GEX: A flexible method for approximating influence via Geometric Ensemble
Sung-Yub Kim, Kyungsu Kim and Eunho Yang
Conference on Neural Information Processing Systems (NeurIPS),
2023
[paper]
[code]
Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds
Jihun Yun and Eunho Yang
Conference on Neural Information Processing Systems (NeurIPS),
2023
[paper]
PC-Adapter: Topology-Aware Adapter for Efficient Domain Adaption on Point Clouds with Rectified Pseudo-label
Joonhyung Park, Hyunjin Seo and Eunho Yang
IEEE/CVF International Conference on Computer Vision (ICCV),
2023
[paper]
SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy Minimization
Changhun Kim, Joonhyung Park, Hajin Shim and Eunho Yang
Conference of the International Speech Communication Association (INTERSPEECH),
2023
(Oral Presentation, 348/2293=15.18%)
[paper]
[code]
ZET-Speech: Zero-shot adaptive Emotion-controllable Text-to-Speech Synthesis with Diffusion and Style-based Models
Minki Kang*, Wooseok Han*, Sung Ju Hwang and Eunho Yang (*: equal contribution)
Conference of the International Speech Communication Association (INTERSPEECH),
2023
[paper]
Fighting Fire with Fire: Contrastive Debiasing without Bias-free Data via Generative Bias-transformation
Yeonsung Jung, Hajin Shim, June Yong Yang and Eunho Yang
International Conference on Machine Learning (ICML),
2023
[paper]
RGE: A Repulsive Graph Rectification for Node Classification via Influence
Jaeyun Song*, Sung-Yub Kim* and Eunho Yang (*: equal contribution)
International Conference on Machine Learning (ICML),
2023
[paper]
Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding
Gyeongman Kim, Hajin Shim, Hyunsu Kim, Yunjey Choi, Junho Kim and Eunho Yang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
2023
[paper]
[code]
[project]
BiasAdv: Bias-Adversarial Augmentation for Model Debiasing
Jongin Lim, Youngdong Kim, Byungjai Kim, Chanho Ahn, Jinwoo Shin, Eunho Yang and Seungju Han
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
2023
[paper]
Deep Self-Supervised Diversity Promoting Learning on Hierarchical Hyperspheres for Regularization
Youngsung Kim, Yoonsuk Hyun, Jae-Joon Han, Eunho Yang, Sung Ju Hwang and Jinwoo Shin
IEEE Access,
2023
[paper]
Towards the Practical Utility of Federated Learning in the Medical Domain
Seongjun Yang, Hyeonji Hwang, Daeyoung Kim, Radhika Dua, Jong-Yeup Kim, Eunho Yang and Edward Choi
Conference on Health, Inference, and Learning (CHIL),
2023
[paper]
WeavSpeech: Data Augmentation Strategy for Automatic Speech Recognition via Semantic-Aware Weaving
Kyusung Seo, Joonhyung Park, Jaeyun Song and Eunho Yang
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2023
[paper]
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
Sung-Yub Kim, Sihwan Park, Kyungsu Kim and Eunho Yang
International Conference on Learning Representations (ICLR),
2023
(Spotlight Presentation, notable-top-25%)
[paper]
[code]
Learning Input-agnostic Manipulation Directions in StyleGAN with Text Guidance
Yoonjeon Kim, Hyunsu Kim, Junho Kim, Yunjey Choi and Eunho Yang
International Conference on Learning Representations (ICLR),
2023
[paper]
[code]
Machine-Learning Model for the Prediction of Hypoxaemia during Endoscopic Retrograde Cholangiopancreatography under Monitored Anaesthesia Care
Huapyong Kang, Bora Lee, Jung Hyun Jo, Hee Seung Lee, Jeong Youp Park, Seungmin Bang, Seung Woo Park, Si Young Song, Joonhyung Park, Hajin Shim, Jung Hyun Lee, Eunho Yang, Eun Hwa Kim, Kwang Joon Kim, Min-Soo Kim and Moon Jae Chung
Yonsei Medical Journal (YMJ),
2023
[paper]
TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification
Jaeyun Song*, Joonhyung Park* and Eunho Yang (*: equal contribution)
International Conference on Machine Learning (ICML),
2022
[paper]
[code]
Set Based Stochastic Subsampling
Bruno Andreis, Seanie Lee, A. Tuan Nguyen, Juho Lee, Eunho Yang and Sung Ju Hwang
International Conference on Machine Learning (ICML),
2022
[paper]
Does it Really Generalize Well on Unseen Data? Systematic Evaluation of Relational Triple Extraction Methods
Juhyuk Lee*, Min-Joong Lee*, June Yong Yang* and Eunho Yang (*: equal contribution)
Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL),
2022
[paper]
Model-augmented Prioritized Experience Replay
Youngmin Oh, Jinwoo Shin, Eunho Yang and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2022
[paper]
Online Hyperparameter Meta-Learning with Hypergradient Distillation
Hae Beom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy Hospedales and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2022
[paper]
Online Coreset Selection for Rehearsal-based Continual Learning
Jaehong Yoon, Divyam Madaan, Eunho Yang and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2022
[paper]
GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification
Joonhyung Park*, Jaeyun Song* and Eunho Yang (*: equal contribution)
International Conference on Learning Representations (ICLR),
2022
[paper]
[code]
AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning
Jihun Yun, Aurelie C. Lozano and Eunho Yang
International Conference on Artificial Intelligence and Statistics (AISTATS),
2022
[paper]
A Simple Framework for Robust Out-of-Distribution Detection
Youngbum Hur, Eunho Yang and Sung Ju Hwang
IEEE Access,
2022
[paper]
Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing
Joonhyung Park, June Yong Yang, Jinwoo Shin, Sung Ju Hwang and Eunho Yang
AAAI Conference on Artificial Intelligence (AAAI),
2022
(Oral Presentation, 380/9020=4.21%)
[paper]
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation
Joonhyung Park*, Hajin Shim* and Eunho Yang (*: equal contribution)
AAAI Conference on Artificial Intelligence (AAAI),
2022
[paper]
[code]
Learning Polymorphic Neural ODEs with Time-Evolving Mixture
Tehrim Yoon, Sumin Shin and Eunho Yang
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),
2022
[paper]
Learning How Long to Wait: Adaptively-Constrained Monotonic Multihead Attention for Streaming ASR
Jaeyun Song, Hajin Shim and Eunho Yang
IEEE Automatic Speech Recognition and Understanding Workshop (ASRU),
2021
[paper]
Unbiased Classification through Bias-Contrastive and Bias-Balanced Learning
Youngkyu Hong and Eunho Yang
Conference on Neural Information Processing Systems (NeurIPS),
2021
[paper]
[code]
Adaptive Proximal Gradient Methods for Structured Neural Networks
Jihun Yun, Aurelie C. Lozano and Eunho Yang
Conference on Neural Information Processing Systems (NeurIPS),
2021
[paper]
Compressed Sensing via Measurement-Conditional Generative Models
Kyung-Su Kim, Jung Hyun Lee and Eunho Yang
IEEE Access,
2021
[paper]
Distilling Linguistic Context for Language Model Compression
Geondo Park, Gyeongman Kim and Eunho Yang
Conference on Empirical Methods in Natural Language Processing (EMNLP),
2021
[paper]
[code]
Cluster-Promoting Quantization with Bit-Drop for Minimizing Network Quantization Loss
Jung Hyun Lee*, Jihun Yun*, Sung Ju Hwang and Eunho Yang (*: equal contribution)
IEEE/CVF International Conference on Computer Vision (ICCV),
2021
[paper]
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
International Joint Conference on Artificial Intelligence (IJCAI),
2021
[paper]
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
Conference of the International Speech Communication Association (INTERSPEECH),
2021
[paper]
Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
Dongchan Min, Dong Bok Lee, Eunho Yang and Sung Ju Hwang
International Conference on Machine Learning (ICML),
2021
[paper]
[code]
Federated Continual Learning with Weighted Inter-client Transfer
Jaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang and Sung Ju Hwang
International Conference on Machine Learning (ICML),
2021
[paper]
[code]
Mutually-Constrained Monotonic Multihead Attention for Online ASR
Jaeyun Song, Hajin Shim and Eunho Yang
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
2021
[paper]
FedMix: Approximation of Mixup under Mean Augmented Federated Learning
Tehrim Yoon, Sumin Shin, Sung Ju Hwang and Eunho Yang
International Conference on Learning Representations (ICLR),
2021
[paper]
Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning
Wonyong Jeong, Jaehong Yoon, Eunho Yang and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2021
[paper]
[code]
Learning to Sample with Local and Global Contexts in Experience Replay Buffer
Youngmin Oh, Kimin Lee, Jinwoo Shin, Eunho Yang and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2021
[paper]
GTA: Graph Truncated Attention for Retrosynthesis
Seung-Woo Seo, You Young Song, June Yong Yang, Seohui Bae, Hankook Lee, Jinwoo Shin, Sung Ju Hwang and Eunho Yang
AAAI Conference on Artificial Intelligence (AAAI),
2021
[paper]
[code]
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning
A. Tuan Nguyen, Hyewon Jeong, Eunho Yang and Sung Ju Hwang
AAAI Conference on Artificial Intelligence (AAAI),
2021
[paper]
[code]
Time-Reversal Symmetric ODE Network
In Huh, Eunho Yang, Sung Ju Hwang and Jinwoo Shin
Conference on Neural Information Processing Systems (NeurIPS),
2020
[paper]
[code]
Bootstrapping Neural Processes
Juho Lee, Yoonho Lee, Jungtaek Kim, Eunho Yang, Sung Ju Hwang and Yee Whye Teh
Conference on Neural Information Processing Systems (NeurIPS),
2020
[paper]
[code]
Few-shot Visual Reasoning with Meta-Analogical Contrastive Learning
Youngsung Kim, Jinwoo Shin, Eunho Yang and Sung Ju Hwang
Conference on Neural Information Processing Systems (NeurIPS),
2020
[paper]
Attribution Preservation in Network Compression for Reliable Network Interpretation
Geondo Park*, June Yong Yang*, Sung Ju Hwang and Eunho Yang (*: equal contribution)
Conference on Neural Information Processing Systems (NeurIPS),
2020
[paper]
[code]
Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning
Jaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang and Jinwoo Shin
Conference on Neural Information Processing Systems (NeurIPS),
2020
[paper]
[code]
Neural Complexity Measures
Yoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang and Seungjin Choi
Conference on Neural Information Processing Systems (NeurIPS),
2020
[paper]
A General Family of Stochastic Proximal Gradient Methods for Deep Learning
Jihun Yun, Aurelie C. Lozano and Eunho Yang
arXiv preprint arXiv:2007.07484,
2020
[paper]
Cost-effective Interactive Attention Learning with Neural Attention Process
Jay Heo, Junhyeon Park, Hyewon Jeong, Kwang Joon Kim, Juho Lee, Eunho Yang and Sung Ju Hwang
International Conference on Machine Learning (ICML),
2020
[paper]
[code]
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
Jaehong Yoon, Saehoon Kim, Eunho Yang and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2020
[paper]
Meta Dropout: Learning to Perturb Latent Features for Generalization
Hae Beom Lee, Taewook Nam, Eunho Yang and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2020
[paper]
[code]
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks
Hae Beom Lee*, Hayeon Lee*, Donghyun Na*, Saehoon Kim, Minseop Park, Eunho Yang and Sung Ju Hwang (*: equal contribution)
International Conference on Learning Representations (ICLR),
2020
(Oral Presentation, 48/2594=1.85%)
[paper]
[code]
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks
Joonyoung Yi, Juhyuk Lee, Kwang Joon Kim, Sung Ju Hwang and Eunho Yang
International Conference on Learning Representations (ICLR),
2020
[paper]
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare
Ingyo Chung, Saehoon Kim, Juho Lee, Kwang Joon Kim, Sung Ju Hwang and Eunho Yang
AAAI Conference on Artificial Intelligence (AAAI),
2020
[paper]
[code]
Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization
Jung Hyun Lee, Jihun Yun, Sung Ju Hwang and Eunho Yang
arXiv preprint arXiv:1911.12990,
2019
[paper]
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck
Sung-Yub Kim, Yongsu Baek, Sung Ju Hwang and Eunho Yang
arXiv preprint arXiv:1906.03118,
2019
[paper]
Stochastic Gradient Methods with Block Diagonal Matrix Adaptation
Jihun Yun, Aurelie C. Lozano and Eunho Yang
arXiv preprint arXiv:1905.10757,
2019
[paper]
Spectral Approximate Inference
Sejun Park, Eunho Yang, Se-Young Yun and Jinwoo Shin
International Conference on Machine Learning (ICML),
2019
[paper]
Trimming the L1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
Jihun Yun, Peng Zheng, Eunho Yang, Aurelie C. Lozano and Aleksandr Aravkin
International Conference on Machine Learning (ICML),
2019
(Oral Presentation, 159/3424=4.64%)
[paper]
[code]
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu, Juho Lee, Minseop Park, Saehoon Kim, Eunho Yang, Sung Ju Hwang and Yi Yang
International Conference on Learning Representations (ICLR),
2019
[paper]
[code]
A General Family of Trimmed Estimators for Robust High-dimensional Data Analysis
Eunho Yang, Aurelie C. Lozano and Aleksandr Aravkin
Electronic Journal of Statistics (EJS),
2018
[paper]
Joint Active Feature Acquisition and Classification with Variable-Size Set Encoding
Hajin Shim, Sung Ju Hwang and Eunho Yang
Conference on Neural Information Processing Systems (NeurIPS),
2018
[paper]
[code]
Uncertainty-Aware Attention for Reliable Interpretation and Prediction
Jay Heo, Hae Beom Lee, Saehoon Kim, Juho Lee, Kwang Joon Kim, Eunho Yang and Sung Ju Hwang
Conference on Neural Information Processing Systems (NeurIPS),
2018
[paper]
[code]
DropMax: Adaptive Variational Softmax
Hae Beom Lee, Juho Lee, Saehoon Kim, Eunho Yang and Sung Ju Hwang
Conference on Neural Information Processing Systems (NeurIPS),
2018
[paper]
[code]
Deep Asymmetric Multi-task Feature Learning
Hae Beom Lee, Eunho Yang and Sung Ju Hwang
International Conference on Machine Learning (ICML),
2018
[paper]
Adaptive Network Sparsification via Dependent Variational Beta-Bernoulli Dropout
Juho Lee, Saehoon Kim, Jaehong Yoon, Hae Beom Lee, Eunho Yang and Sung Ju Hwang
arXiv preprint arXiv:1805.10896,
2018
[paper]
M-estimation with the Trimmed l1 Penalty
Jihun Yun, Peng Zheng, Eunho Yang, Aurelie C. Lozano and Aleksandr Aravkin
arXiv preprint arXiv:1805.07495,
2018
[paper]
Lifelong Learning with Dynamically Expandable Networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee and Sung Ju Hwang
International Conference on Learning Representations (ICLR),
2018
[paper]
Multitask Learning using Task Clustering with Applications to Predictive Modeling and GWAS of Plant Varieties
Ming Yu, Addie M. Thompson, Karthikeyan Natesan Ramamurthy, Eunho Yang and Aurelie C. Lozano
arXiv preprint arXiv:1710.01788,
2017
[paper]
Learning Task Structure via Sparsity Grouped Multitask Learning
Meghana Kshirsagar, Eunho Yang and Aurelie C. Lozano
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD),
2017
[paper]
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang and Aurelie C. Lozano
International Conference on Machine Learning (ICML),
2017
[paper]
Ordinal Graphical Models: A Tale of Two Approaches
Arun Sai Suggala, Eunho Yang and Pradeep Ravikumar
International Conference on Machine Learning (ICML),
2017
[paper]
A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution
David I. Inouye, Eunho Yang, Genevera I. Allen and Pradeep Ravikumar
Wiley Interdisciplinary Reviews (WIREs): Computational Statistics,
2017
[paper]
Automated Sorghum Phenotyping and Trait Development Platform
Mitch Tuinstra, Cliff Weil, Addie Thompson, Chris Boomsma, Melba Crawford, Ayman Habib, Edward Delp, Keith Cherkauer, Larry Biehl, Naoki Abe, Meghana Kshirsagar, Aurelie C. Lozano, Karthikeyan Natesan Ramamurthy, Peder Olsen, and Eunho Yang
KDD Workshop on Data Science for Food, Energy and Water (KDDW-DSFEW),
2016
Iteratively Regrouped Lasso: Learning Group Structure in Genome Wide Association Studies in Crops
Meghana Kshirsagar, Aurelie C. Lozano and Eunho Yang
KDD Workshop on Data Science for Food, Energy and Water (KDDW-DSFEW),
2016
XMRF: an R package to fit Markov Networks to high-throughput genetics data
Ying-Wooi Wan, Genevera I. Allen, Yulia Baker, Eunho Yang, Pradeep Ravikumar, Matthew Anderson and Zhandong Liu
BMC Systems Biology,
2016
[paper]
Asymmetric Multi-task Learning Based on Task Relatedness and Loss
Giwoong Lee, Eunho Yang and Sung Ju Hwang
International Conference on Machine Learning (ICML),
2016
[paper]
Minimum Distance Lasso for Robust High-dimensional Regression
Aurelie C. Lozano, Nicolai Meinshausen and Eunho Yang
Electronic Journal of Statistics (EJS),
2016
[paper]
Graphical Models via Univariate Exponential Family Distributions
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen and Zhandong Liu
Journal of Machine Learning Research (JMLR),
2015
[paper]
Closed-form Estimators for High-dimensional Generalized Linear Models
Eunho Yang, Aurelie C. Lozano and Pradeep Ravikumar
Conference on Neural Information Processing Systems (NIPS),
2015
(Spotlight Presentation, 82/1838=4.5%)
[paper]
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso
Eunho Yang and Aurelie C. Lozano
Conference on Neural Information Processing Systems (NIPS),
2015
[paper]
Elementary Estimators for Graphical Models
Eunho Yang, Aurelie C. Lozano and Pradeep Ravikumar
Conference on Neural Information Processing Systems (NIPS),
2014
[paper]
Elementary Estimators for High-Dimensional Linear Regression
Eunho Yang, Aurelie C. Lozano and Pradeep Ravikumar
International Conference on Machine Learning (ICML),
2014
[paper]
Elementary Estimators for Sparse Covariance Matrices and Other Structured Moments
Eunho Yang, Aurelie C. Lozano and Pradeep Ravikumar
International Conference on Machine Learning (ICML),
2014
[paper]
Mixed Graphical Models via Exponential Families
Eunho Yang, Yulia Baker, Pradeep Ravikumar, Genevera Allen and Zhandong Liu
International Conference on Artificial Intelligence and Statistics (AISTATS),
2014
(Oral Presentation, 22/335=6.6%)
[paper]
Conditional Random Fields via Univariate Exponential Families
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen and Zhandong Liu
Conference on Neural Information Processing Systems (NIPS),
2013
[paper]
Dirty Statistical Models
Eunho Yang and Pradeep Ravikumar
Conference on Neural Information Processing Systems (NIPS),
2013
[paper]
On Poisson Graphical Models
Eunho Yang, Pradeep Ravikumar, Genevera I. Allen and Zhandong Liu
Conference on Neural Information Processing Systems (NIPS),
2013
[paper]
On Robust Estimation of High Dimensional Generalized Linear Models
Eunho Yang, Ambuj Tewari and Pradeep Ravikumar
International Joint Conference on Artificial Intelligence (IJCAI),
2013
[paper]
Graphical Models via Generalized Linear Models
Eunho Yang, Genevera Allen, Zhandong Liu and Pradeep Ravikumar
Conference on Neural Information Processing Systems (NIPS),
2012
(Oral Presentation, 20/1467=1.4%)
[paper]
Perturbation based Large Margin Approach for Ranking
Eunho Yang, Ambuj Tewari and Pradeep Ravikumar
International Conference on Artificial Intelligence and Statistics (AISTATS),
2012
[paper]
On the Use of Variational Inference for Learning Discrete Graphical Models
Eunho Yang and Pradeep Ravikumar
International Conference on Machine Learning (ICML),
2011
[paper]
On NDCG Consistency of Listwise Ranking Methods
Pradeep Ravikumar, Ambuj Tewari and Eunho Yang
International Conference on Artificial Intelligence and Statistics (AISTATS),
2011
[paper]
A New Class of Ranking Functions for DCG-Like Evaluation Metrics using Conditional Probability Models
Eunho Yang, Pradeep Ravikumar and Matthew Lease
Technical Report AI14-02 (AI report), Department of Computer Science, University of Texas at Austin,
2010
[paper]
