Ricardo Henao
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
62
Venues
17
Active years
2006–2026
Best venue rank
A*
Where they publish
Papers
62 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Calibrating Model-Based Evaluation Metrics for Summarization. | Hongye Liu, Dhanajit Brahma, Ricardo Henao |
| 2026 | ACL | Learning to Control Summaries with Score Ranking. | Hongye Liu, Liang Ding, Ricardo Henao |
| 2025 | AAAI | Proactive Pseudo-Intervention: Pre-informed Contrastive Learning For Interpretable Vision Models. | Dong Wang, Yuewei Yang, Liqun Chen, Zhe Gan, Ricardo Henao, Lawrence Carin |
| 2025 | AISTATS | Cross-Modal Imputation and Uncertainty Estimation for Spatial Transcriptomics. | Xiangyu Guo, Ricardo Henao |
| 2025 | EMNLP | Learning Subjective Label Distributions via Sociocultural Descriptors. | Mohammed Fayiz Parappan, Ricardo Henao |
| 2025 | ICML | Learning Survival Distributions with the Asymmetric Laplace Distribution. | Deming Sheng, Ricardo Henao |
| 2025 | ICML | On Understanding Attention-Based In-Context Learning for Categorical Data. | Aaron T. Wang, William Convertino, Xiang Cheng, Ricardo Henao, Lawrence Carin |
| 2025 | NAACL | Learning to Substitute Words with Model-based Score Ranking. | Hongye Liu, Ricardo Henao |
| 2024 | AISTATS | Adaptive Discretization for Event PredicTion (ADEPT). | Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew Engelhard |
| 2024 | ICML | Contrastive Learning for Clinical Outcome Prediction with Partial Data Sources. | Meng Xia, Jonathan Wilson, Benjamin Goldstein, Ricardo Henao |
| 2024 | NAACL | Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning. | Rui Wang, Tong Yu, Ruiyi Zhang, Sungchul Kim, Ryan A. Rossi, Handong Zhao, Junda Wu, Subrata Mitra, Lina Yao, Ricardo Henao |
| 2023 | AAAI | Few-Shot Composition Learning for Image Retrieval with Prompt Tuning. | Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li, Ricardo Henao |
| 2023 | ACL | Federated Domain Adaptation for Named Entity Recognition via Distilling with Heterogeneous Tag Sets. | Rui Wang, Tong Yu, Junda Wu, Handong Zhao, Sungchul Kim, Ruiyi Zhang, Subrata Mitra, Ricardo Henao |
| 2023 | AISTATS | Estimating Total Correlation with Mutual Information Estimators. | Ke Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin |
| 2023 | AISTATS | Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling. | Rui Wang, Pengyu Cheng, Ricardo Henao |
| 2023 | ICML | An Effective Meaningful Way to Evaluate Survival Models. | Shiang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner |
| 2023 | KDD | Neural Insights for Digital Marketing Content Design. | Fanjie Kong, Yuan Li, Houssam Nassif, Tanner Fiez, Ricardo Henao, Shreya Chakrabarti |
| 2023 | WACV | Pushing the Efficiency Limit Using Structured Sparse Convolutions. | Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin |
| 2022 | ACL | Few-Shot Class-Incremental Learning for Named Entity Recognition. | Rui Wang, Tong Yu, Handong Zhao, Sungchul Kim, Subrata Mitra, Ruiyi Zhang, Ricardo Henao |
| 2022 | AISTATS | Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data. | Matthew Engelhard, Ricardo Henao |
| 2022 | CVPR | Efficient Classification of Very Large Images with Tiny Objects. | Fanjie Kong, Ricardo Henao |
| 2022 | EMNLP | Open World Classification with Adaptive Negative Samples. | Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin |
| 2022 | EMNLP | Context-aware Information-theoretic Causal De-biasing for Interactive Sequence Labeling. | Junda Wu, Rui Wang, Tong Yu, Ruiyi Zhang, Handong Zhao, Shuai Li, Ricardo Henao, Ani Nenkova |
| 2022 | ICASSP | Wasserstein Cross-Lingual Alignment For Named Entity Recognition. | Rui Wang, Ricardo Henao |
| 2022 | ICLR | Gradient Importance Learning for Incomplete Observations. | Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic |
| 2022 | UAI | Capturing actionable dynamics with structured latent ordinary differential equations. | Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao |
| 2021 | AAAI | Variational Disentanglement for Rare Event Modeling. | Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao |
| 2021 | AISTATS | Counterfactual Representation Learning with Balancing Weights. | Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin |
| 2021 | CVPR | Wasserstein Contrastive Representation Distillation. | Liqun Chen, Dong Wang, Zhe Gan, Jingjing Liu, Ricardo Henao, Lawrence Carin |
| 2021 | EMNLP | Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition. | Rui Wang, Ricardo Henao |
| 2021 | NAACL | SpanPredict: Extraction of Predictive Document Spans with Neural Attention. | Vivek Subramanian, Matthew Engelhard, Samuel Berchuck, Liqun Chen, Ricardo Henao, Lawrence Carin |
| 2020 | AAAI | Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning. | Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin |
| 2020 | BMVC | Advancing weakly supervised cross-domain alignment with optimal transport. | Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin |
| 2020 | EMNLP | Integrating Task Specific Information into Pretrained Language Models for Low Resource Fine Tuning. | Rui Wang, Shijing Si, Guoyin Wang, Lei Zhang, Lawrence Carin, Ricardo Henao |
| 2020 | ICML | Learning Autoencoders with Relational Regularization. | Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin |
| 2019 | AAAI | Communication-Efficient Stochastic Gradient MCMC for Neural Networks. | Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin |
| 2018 | AAAI | Deconvolutional Latent-Variable Model for Text Sequence Matching. | Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin |
| 2018 | ACL | NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. | Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Ricardo Henao, Lawrence Carin |
| 2018 | ACL | Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. | Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin |
| 2018 | ACL | Joint Embedding of Words and Labels for Text Classification. | Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin |
| 2018 | AMIA | The Duke Health Data Science Internship Program: Integrating the Educational Mission into Real-World Research. | Shelley A. Rusincovitch, Lisa Wruck, Ricardo Henao, Larisa Rodgers, Allison Dunning, Peter Merrill, Hillary Mulder, Robert Overton, Matthew Phelan, Erich Huang, Lawrence Carin, Michael J. Pencina |
| 2018 | EMNLP | Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. | Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin |
| 2018 | ICML | Adversarial Time-to-Event Modeling. | Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao |
| 2018 | ICML | Variational Inference and Model Selection with Generalized Evidence Bounds. | Liqun Chen, Chenyang Tao, Ruiyi Zhang, Ricardo Henao, Lawrence Carin |
| 2018 | ICML | JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. | Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin |
| 2018 | ICML | Chi-square Generative Adversarial Network. | Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin |
| 2017 | AMIA | Guiding Principles for the Duke Connected Care Predictive Modeling Pilot. | Eugenie Komives, Shelley A. Rusincovitch, John Paat, Lawrence Carin, Daniel Costello, Michael Gao, Bradley G. Hammill, Ricardo Henao, Nigel B. Neely, Ursula Rogers, Devdutta Sangvai, Mary Schilder, Erich Huang |
| 2017 | AMIA | Rationale and Design for the Duke Connected Care Predictive Modeling Pilot with a Medicare Shared Savings Program Population. | Shelley A. Rusincovitch, Ricardo Henao, Michael Gao, Lawrence Carin, Ursula Rogers, Nigel B. Neely, Mary Schilder, Daniel Costello, Eugenie Komives, Erich Huang |
| 2017 | EMNLP | Learning Generic Sentence Representations Using Convolutional Neural Networks. | Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin |
| 2017 | ICML | Stochastic Gradient Monomial Gamma Sampler. | Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin |
| 2017 | ICML | Adversarial Feature Matching for Text Generation. | Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin |
| 2016 | AAAI | Learning a Hybrid Architecture for Sequence Regression and Annotation. | Yizhe Zhang, Ricardo Henao, Lawrence Carin, Jianling Zhong, Alexander J. Hartemink |
| 2016 | AISTATS | Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization. | Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin |
| 2016 | ICDM | Triply Stochastic Variational Inference for Non-linear Beta Process Factor Analysis. | Kai Fan, Yizhe Zhang, Ricardo Henao, Katherine A. Heller |
| 2016 | ICDM | Dynamic Poisson Factor Analysis. | Yizhe Zhang, Yue Zhao, Lawrence David, Ricardo Henao, Lawrence Carin |
| 2016 | IJCAI | Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks. | Yizhe Zhang, Ricardo Henao, Chunyuan Li, Lawrence Carin |
| 2015 | AISTATS | Learning Deep Sigmoid Belief Networks with Data Augmentation. | Zhe Gan, Ricardo Henao, David E. Carlson, Lawrence Carin |
| 2015 | ICML | Scalable Deep Poisson Factor Analysis for Topic Modeling. | Zhe Gan, Changyou Chen, Ricardo Henao, David E. Carlson, Lawrence Carin |
| 2015 | ICML | A Multitask Point Process Predictive Model. | Wenzhao Lian, Ricardo Henao, Vinayak A. Rao, Joseph E. Lucas, Lawrence Carin |
| 2015 | ICML | Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood. | Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin |
| 2013 | AMIA | Patient Clustering with Uncoded Text in Electronic Medical Records. | Ricardo Henao, Jared Murray, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas |
| 2006 | ICONIP | Probabilistic Kernel Principal Component Analysis Through Time. | Mauricio A. lvarez, Ricardo Henao |