Greg Ver Steeg
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
57
Venues
20
Active years
2011–2025
Best venue rank
A*
Where they publish
Papers
57 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICASSP | Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application. | Elan Markowitz, Ziyan Jiang, Fan Yang, Xing Fan, Zheng Chen, Greg Ver Steeg, Aram Galstyan |
| 2024 | ACL | Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks. | Haz Sameen Shahgir, Xianghao Kong, Greg Ver Steeg, Yue Dong |
| 2024 | AISTATS | Policy Learning for Localized Interventions from Observational Data. | Myrl G. Marmarelis, Fred Morstatter, Aram Galstyan, Greg Ver Steeg |
| 2024 | CVPR | Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding. | Alessandro Achille, Greg Ver Steeg, Tian Yu Liu, Matthew Trager, Carson Klingenberg, Stefano Soatto |
| 2024 | CVPR | Comparative Analysis of Generalization and Harmonization Methods for 3D Brain fMRI Images: A Case Study on OpenBHB Dataset. | Soroosh Safari Loaliyan, Greg Ver Steeg |
| 2024 | EACL | Prompt Perturbation Consistency Learning for Robust Language Models. | Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan |
| 2024 | ICLR | Interpretable Diffusion via Information Decomposition. | Xianghao Kong, Ollie Liu, Han Li, Dani Yogatama, Greg Ver Steeg |
| 2024 | RecSys | Biased User History Synthesis for Personalized Long-Tail Item Recommendation. | Keshav Balasubramanian, Abdulla Alshabanah, Elan Markowitz, Greg Ver Steeg, Murali Annavaram |
| 2023 | ACL | Measuring and Mitigating Local Instability in Deep Neural Networks. | Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan |
| 2023 | ACL | Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. | Umang Gupta, Aram Galstyan, Greg Ver Steeg |
| 2023 | ACL | Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. | Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg |
| 2023 | ICLR | Information-Theoretic Diffusion. | Xianghao Kong, Rob Brekelmans, Greg Ver Steeg |
| 2023 | MICCAI | Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain. | Elizabeth Haddad, Myrl G. Marmarelis, Talia M. Nir, Aram Galstyan, Greg Ver Steeg, Neda Jahanshad |
| 2023 | UAI | Partial identification of dose responses with hidden confounders. | Myrl G. Marmarelis, Elizabeth Haddad, Andrew Jesson, Neda Jahanshad, Aram Galstyan, Greg Ver Steeg |
| 2022 | ACL | Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. | Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan |
| 2022 | CVPR | Failure Modes of Domain Generalization Algorithms. | Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan |
| 2022 | ICLR | Improving Mutual Information Estimation with Annealed and Energy-Based Bounds. | Rob Brekelmans, Sicong Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Baker Grosse, Alireza Makhzani |
| 2022 | ITW | Formal limitations of sample-wise information-theoretic generalization bounds. | Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan |
| 2022 | MICCAI | Towards Sparsified Federated Neuroimaging Models via Weight Pruning. | Dimitris Stripelis, Umang Gupta, Nikhil J. Dhinagar, Greg Ver Steeg, Paul M. Thompson, Jos Luis Ambite |
| 2022 | NAACL | Temporal Generalization for Spoken Language Understanding. | Judith Gaspers, Anoop Kumar, Greg Ver Steeg, Aram Galstyan |
| 2022 | NAACL | StATIK: Structure and Text for Inductive Knowledge Graph Completion. | Elan Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Murali Annavaram, Aram Galstyan, Greg Ver Steeg |
| 2021 | AAAI | Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation. | Umang Gupta, Aaron M. Ferber, Bistra Dilkina, Greg Ver Steeg |
| 2021 | ACML | Layer-Wise Neural Network Compression via Layer Fusion. | James O'Neill, Greg Ver Steeg, Aram Galstyan |
| 2021 | AISTATS | Influence Decompositions For Neural Network Attribution. | Kyle Reing, Greg Ver Steeg, Aram Galstyan |
| 2021 | ICLR | Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. | Elan Sopher Markowitz, Keshav Balasubramanian, Mehrnoosh Mirtaheri, Sami Abu-El-Haija, Bryan Perozzi, Greg Ver Steeg, Aram Galstyan |
| 2021 | UAI | q-Paths: Generalizing the geometric annealing path using power means. | Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood |
| 2020 | AAAI | Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. | Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan |
| 2020 | AAAI | Invariant Representations through Adversarial Forgetting. | Ayush Jaiswal, Daniel Moyer, Greg Ver Steeg, Wael AbdAlmageed, Premkumar Natarajan |
| 2020 | ICML | All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. | Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan |
| 2020 | ICML | Improving generalization by controlling label-noise information in neural network weights. | Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan |
| 2019 | AAAI | Kernelized Hashcode Representations for Relation Extraction. | Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao |
| 2019 | AISTATS | Auto-Encoding Total Correlation Explanation. | Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan |
| 2019 | EMNLP | Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. | Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi |
| 2019 | ICML | MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. | Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan |
| 2018 | IJCAI | Dialogue Modeling Via Hash Functions. | Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan |
| 2018 | UAI | A Forest Mixture Bound for Block-Free Parallel Inference. | Neal Lawton, Greg Ver Steeg, Aram Galstyan |
| 2017 | ICDE | Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks (Extended Abstract). | Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, Aram Galstyan |
| 2017 | IJCAI | Unsupervised Learning via Total Correlation Explanation. | Greg Ver Steeg |
| 2017 | IJCAI | Sifting Common Information from Many Variables. | Greg Ver Steeg, Shuyang Gao, Kyle Reing, Aram Galstyan |
| 2017 | WWW | The Spread of Physical Activity Through Social Networks. | David Stck, Haraldur Tmas Hallgrmsson, Greg Ver Steeg, Alessandro Epasto, Luca Foschini |
| 2016 | ICML | The Information Sieve. | Greg Ver Steeg, Aram Galstyan |
| 2016 | WWW | Latent Space Model for Multi-Modal Social Data. | Yoon-Sik Cho, Greg Ver Steeg, Emilio Ferrara, Aram Galstyan |
| 2015 | AISTATS | Efficient Estimation of Mutual Information for Strongly Dependent Variables. | Shuyang Gao, Greg Ver Steeg, Aram Galstyan |
| 2015 | AISTATS | Maximally Informative Hierarchical Representations of High-Dimensional Data. | Greg Ver Steeg, Aram Galstyan |
| 2015 | MICCAI | Information-Theoretic Clustering of Neuroimaging Metrics Related to Cognitive Decline in the Elderly. | Madelaine Daianu, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M. Nir, Xiaoran Yan, Gautam Prasad, Kristina Lerman, Aram Galstyan, Paul M. Thompson |
| 2015 | WWW | Disentangling the Lexicons of Disaster Response in Twitter. | Nathan O. Hodas, Greg Ver Steeg, Joshua J. Harrison, Satish Chikkagoudar, Eric Bell, Courtney D. Corley |
| 2015 | UAI | Estimating Mutual Information by Local Gaussian Approximation. | Shuyang Gao, Greg Ver Steeg, Aram Galstyan |
| 2014 | AAAI | Where and Why Users "Check In". | Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan |
| 2014 | ICML | Demystifying Information-Theoretic Clustering. | Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo |
| 2013 | AISTATS | Statistical Tests for Contagion in Observational Social Network Studies. | Greg Ver Steeg, Aram Galstyan |
| 2013 | WSDM | Information-theoretic measures of influence based on content dynamics. | Greg Ver Steeg, Aram Galstyan |
| 2012 | WWW | Information transfer in social media. | Greg Ver Steeg, Aram Galstyan |
| 2011 | AAAI | Co-Evolution of Selection and Influence in Social Networks. | Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan |
| 2011 | ICWSM | Social Mechanics: An Empirically Grounded Science of Social Media. | Kristina Lerman, Aram Galstyan, Greg Ver Steeg, Tad Hogg |
| 2011 | ICWSM | What Stops Social Epidemics? | Greg Ver Steeg, Rumi Ghosh, Kristina Lerman |
| 2011 | UAI | A Sequence of Relaxation Constraining Hidden Variable Models. | Greg Ver Steeg, Aram Galstyan |
| 2011 | UAI | Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs (Abstract). | Greg Ver Steeg, Aram Galstyan, Armen E. Allahverdyan |