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Papers
How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning?
AAAI 2025
How many samples are needed to train a deep neural network?
ICLR 2025
Infinite Width Limits of Self Supervised Neural Networks
AISTATS 2025
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
COLT 2025
Learning from Label Proportions and Covariate-shifted Instances
UAI 2025
Learning with Exact Invariances in Polynomial Time
ICML 2025
Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning
ICLR 2025
On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes
JMLR 2025
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
JMLR 2025
On the Sample Complexity of Next-Token Prediction
AISTATS 2025
Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions
JMLR 2025
Overtuning in Hyperparameter Optimization
AutoML 2025
PAC-Bayes Analysis for Recalibration in Classification
ICML 2025
Parabolic Continual Learning
AISTATS 2025
Rethinking Benign Overfitting in Two-Layer Neural Networks
ICML 2025
Sample Complexity of Linear Regression Models for Opinion Formation in Networks
AAAI 2025
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes
CVPR 2025
Stability and Generalization for Stochastic (Compositional) Optimizations
IJCAI 2025
Statistical Guarantees for Unpaired Image-to-Image Cross-Domain Analysis using GANs
AISTATS 2025
Supercharging Graph Transformers with Advective Diffusion
ICML 2025
The Size of Teachers as a Measure of Data Complexity: PAC-Bayes Excess Risk Bounds and Scaling Laws
AISTATS 2025
Toward Understanding In-context vs. In-weight Learning
ICLR 2025
Training Data Provenance Verification: Did Your Model Use Synthetic Data from My Generative Model for Training?
CVPR 2025
Understanding the Stability-based Generalization of Personalized Federated Learning
ICLR 2025
Universality of Kernel Random Matrices and Kernel Regression in the Quadratic Regime
JMLR 2025