Alexander D'Amour
12 papers · 2017–2025 · 4 venues · across top CS/AI venues
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Machine Learning
(11)
Artificial Intelligence
(8)
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(7)
Learning Types Β· Machine Learning
(4)
Optimization & Theory
(4)
Deep Learning
(3)
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(2)
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(1)
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Keywords
distribution shift
(5)
causal inference
(4)
domain generalization
(4)
model robustness
(2)
spurious correlation
(2)
transfer learning
(2)
data balancing
(2)
statistical inference
(2)
domain adaptation
(1)
multimodal learning
(1)
active learning
(1)
em algorithm
(1)
high-dimensional inference
(1)
test-time adaptation
(1)
sensitivity analysis
(1)
logistic regression
(1)
variance reduction
(1)
hierarchical model
(1)
out-of-distribution generalization
(1)
coreference resolution
(1)
Papers
Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
JMLR 2025
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
ICLR 2024
Mind the Graph When Balancing Data for Fairness or Robustness
NeurIPS 2024
Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations
NeurIPS 2023
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
NeurIPS 2022
The MultiBERTs: BERT Reproductions for Robustness Analysis
ICLR 2022
Underspecification Presents Challenges for Credibility in Modern Machine Learning
JMLR 2022
Counterfactual Invariance to Spurious Correlations in Text Classification
NeurIPS 2021
On Robustness and Transferability of Convolutional Neural Networks
CVPR 2021
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression
NeurIPS 2021
Detecting Extrapolation with Local Ensembles
ICLR 2020
Reducing Reparameterization Gradient Variance
NeurIPS 2017