Greg Ver Steeg
48 papers · 2013–2024 · 15 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (15) π§ Keyword Pioneer π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (12) π Academic Marathon (11)
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Academic Marathon
(11)
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Cross-Pollinator
(14)
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Renaissance Researcher
(7)
π€
Dynamic Duo
(38)
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Deep Specialist
(14)
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Keyword Champion
(10)
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Grand Slam
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Trend Setter
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Century Club
(48)
ποΈ
Keyword Collector
(197)
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Unstoppable
(12)
β‘
Prolific Year
(7)
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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
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