← Authors

Greg Ver Steeg

48 papers · 2013–2024 · 15 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🌍 Conference Polyglot (15) πŸƒ Academic Marathon (11) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (7) 🀝 Dynamic Duo (38) πŸ”¬ Deep Specialist (14) πŸ† Keyword Champion (10) πŸ† Grand Slam πŸ“ˆ Trend Setter πŸ’Ž Century Club (48) πŸ—ƒοΈ Keyword Collector (197) πŸ”₯ Unstoppable (12) ⚑ Prolific Year (7) πŸš€ Conference Pioneer

Conferences

NIPS (9) AISTATS (6) ACL (5) ICML (5) AAAI (4) ICLR (4) NAACL (3) CVPR (2) EMNLP (2) IJCAI (2) UAI (2) CLEAR (1) EACL (1) IJCNLP (1) MIDL (1)

Top co-authors

Aram Galstyan (38) Shuyang Gao (7) Rob Brekelmans (7) Hrayr Harutyunyan (5) Anoop Kumar (5) Umang Gupta (5) Guillermo Cecchi (4) Xianghao Kong (4) Sahil Garg (4) Daniel Moyer (4)

Keywords

mutual information (10) information theory (7) unsupervised learning (7) representation learning (6) variational inference (4) causal inference (3) relation extraction (3) hashcode representation (3) kernel methods (3) generalization bound (2) semi-supervised learning (2) adversarial learning (2) model compression (2) feature learning (2) variational autoencoder (2) hierarchical representation (2) intent classification (2) knowledge distillation (2) domain generalization (2) adversarial training (2)

Papers

Prompt Perturbation Consistency Learning for Robust Language Models EACL 2024
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding CLEAR 2024
Policy Learning for Localized Interventions from Observational Data AISTATS 2024
Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training NIPS 2024
Interpretable Diffusion via Information Decomposition ICLR 2024
Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks ACL 2024
Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding CVPR 2024
Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models ACL 2023
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning ACL 2023
Measuring and Mitigating Local Instability in Deep Neural Networks ACL 2023
Partial identification of dose responses with hidden confounders UAI 2023
Information-Theoretic Diffusion ICLR 2023
Temporal Generalization for Spoken Language Understanding NAACL 2022
StATIK: Structure and Text for Inductive Knowledge Graph Completion NAACL 2022
Attributing Fair Decisions with Attention Interventions NAACL 2022
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds ICLR 2022
Zero-Shot Cross-Lingual Sequence Tagging as Seq2Seq Generation for Joint Intent Classification and Slot Filling EMNLP 2022
Failure Modes of Domain Generalization Algorithms CVPR 2022
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal ACL 2022
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation AAAI 2021
Implicit SVD for Graph Representation Learning NIPS 2021
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling NIPS 2021
Information-theoretic generalization bounds for black-box learning algorithms NIPS 2021
Influence Decompositions For Neural Network Attribution AISTATS 2021
Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning ICLR 2021
Membership Inference Attacks on Deep Regression Models for Neuroimaging MIDL 2021
q-Paths: Generalizing the geometric annealing path using power means UAI 2021
Invariant Representations through Adversarial Forgetting AAAI 2020
Modeling Dialogues with Hashcode Representations: A Nonparametric Approach AAAI 2020
Improving generalization by controlling label-noise information in neural network weights ICML 2020
All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference ICML 2020
Exact Rate-Distortion in Autoencoders via Echo Noise NIPS 2019
Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction EMNLP 2019
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing ICML 2019
Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction IJCNLP 2019
Fast structure learning with modular regularization NIPS 2019
Auto-Encoding Total Correlation Explanation AISTATS 2019
Kernelized Hashcode Representations for Relation Extraction AAAI 2019
Invariant Representations without Adversarial Training NIPS 2018
Sifting Common Information from Many Variables IJCAI 2017
Unsupervised Learning via Total Correlation Explanation IJCAI 2017
Variational Information Maximization for Feature Selection NIPS 2016
The Information Sieve ICML 2016
Efficient Estimation of Mutual Information for Strongly Dependent Variables AISTATS 2015
Maximally Informative Hierarchical Representations of High-Dimensional Data AISTATS 2015
Discovering Structure in High-Dimensional Data Through Correlation Explanation NIPS 2014
Demystifying Information-Theoretic Clustering ICML 2014
Statistical Tests for Contagion in Observational Social Network Studies AISTATS 2013