Sang Michael Xie
15 papers · 2018–2024 · 4 conferences · across top CS/AI conferences
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NIPS (4)
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Keywords
transfer learning
(3)
language model
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neural network
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representation learning
(1)
feature learning
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domain generalization
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robust optimization
(1)
semi-supervised regression
(1)
kl divergence
(1)
unsupervised domain adaptation
(1)
adversarial training
(1)
feature disentanglement
(1)
out-of-distribution generalization
(1)
deep kernel learning
(1)
feature space
(1)
gaussian process
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distribution shift
(1)
structured output
(1)
continuous relaxation
(1)
contrastive learning
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Papers
Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations
ICML 2024
Data Selection for Language Models via Importance Resampling
NIPS 2023
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
NIPS 2023
Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models
ICML 2023
Reward Design with Language Models
ICLR 2023
Extending the WILDS Benchmark for Unsupervised Adaptation
ICLR 2022
An Explanation of In-context Learning as Implicit Bayesian Inference
ICLR 2022
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation
ICML 2022
Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization
ICML 2021
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
ICLR 2021
Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning
NIPS 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts
ICML 2021
Understanding and Mitigating the Tradeoff between Robustness and Accuracy
ICML 2020
Reparameterizable Subset Sampling via Continuous Relaxations
IJCAI 2019
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
NIPS 2018