ICML2022放榜了，很久没写博客了，今天摸鱼把ICML2022的接收列表翻了一遍，挑了一些自己感兴趣的下次读, 先放论文列表，有兴趣的自取。

Oral

Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning
Bounding Training Data Reconstruction in Private (Deep) Learning
Measuring Representational Robustness of Neural Networks Through Shared Invariances
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias
Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models

Spotlights

Does the Data Induce Capacity Control in Deep Learning?
Accelerating Shapley Explanation via Contributive Cooperator Selection
Prototype Based Classification from Hierarchy to Fairness
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments
Fair Representation Learning through Implicit Path Alignment
Feature selection using e-values
Mitigating Neural Network Overconfidence with Logit Normalization
Active Multi-Task Representation Learning
Dataset Condensation with Contrastive Signals
Extracting Latent State Representations with Linear Dynamics from Rich Observations
How to Fill the Optimal Set? Population Gradient Descent with Harmless Diversity
Fair and Fast k-Center Clustering for Data Summarization
Channel Importance Matters in Few-Shot Image Classification
Label-Free Explainability for Unsupervised Models
A psychological theory of explainability
From data to functa: Your data point is a function and you should treat it like one
Understanding Robust Overfitting of Adversarial Training and Beyond
Learning Stable Classifiers by Transferring Unstable Features
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings
XAI for Transformers: Better Explanations through Conservative Propagation
Role-based Multiplex Network Embedding
Meaningfully debugging model mistakes using conceptual counterfactual explanations
Forgetting-free Continual Learning with Winning Subnetworks
Wide Neural Networks Forget Less Catastrophically
Measuring dissimilarity with diffeomorphism invariance
Efficient Learning of CNNs using Patch Based Features
Multi-scale Feature Learning Dynamics: Insights for Double Descent

Accepted papers

Achieving Fairness at No Utility Cost via Data Reweighing
Confidence Score for Source-Free Unsupervised Domain Adaptation
Probabilistic Bilevel Coreset Selection
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information
On the Effects of Artificial Data Modification
Provable Domain Generalization via Invariant-Feature Subspace Recovery
More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize
Information-Intensive Dataset Condensation
Datamodels: Understanding Predictions with Data and Data with Predictions
Benefits of Deep and Wide Convolutional Residual Networks: Function Approximation under Smoothness Constraint
What Can Linear Interpolation of Neural Network Loss Landscapes Tell Us?
Understanding Instance-Level Impact of Fairness Constraints
Disentangling Disease-related Representation from Obscure for Disease Prediction
A new similarity measure for covariate shift with applications to nonparametric regression
Representation Topology Divergence: A Method for Comparing Neural Network Representations

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ICML2022有意思的文章

Oral

Spotlights

Accepted papers

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