Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional Shifts
Fuente:
arXiv
Saved in:
| Main Authors: | Najafi, Amir, Sani, Samin Mahdizadeh, Farnia, Farzan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
by: Sani, Matina Mahdizadeh, et al.
Published: (2026)
by: Sani, Matina Mahdizadeh, et al.
Published: (2026)
Certified Adversarial Robustness via Partition-based Randomized Smoothing
by: Goli, Hossein, et al.
Published: (2024)
by: Goli, Hossein, et al.
Published: (2024)
On the Distributed Evaluation of Generative Models
by: Wang, Zixiao, et al.
Published: (2023)
by: Wang, Zixiao, et al.
Published: (2023)
DAK-UCB: Diversity-Aware Prompt Routing for LLMs and Generative Models
by: Jafari, Donya, et al.
Published: (2026)
by: Jafari, Donya, et al.
Published: (2026)
The Maximum von Neumann Entropy Principle: Theory and Applications in Machine Learning
by: Wu, Youqi, et al.
Published: (2026)
by: Wu, Youqi, et al.
Published: (2026)
Robust Learnability of Sample-Compressible Distributions under Noisy or Adversarial Perturbations
by: Boushehrian, Arefe, et al.
Published: (2025)
by: Boushehrian, Arefe, et al.
Published: (2025)
On the Hardness of Sampling from Mixture Distributions via Langevin Dynamics
by: Cheng, Xiwei, et al.
Published: (2024)
by: Cheng, Xiwei, et al.
Published: (2024)
A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models
by: Hu, Xiaoyan, et al.
Published: (2024)
by: Hu, Xiaoyan, et al.
Published: (2024)
pFedFair: Towards Optimal Group Fairness-Accuracy Trade-off in Heterogeneous Federated Learning
by: Lei, Haoyu, et al.
Published: (2025)
by: Lei, Haoyu, et al.
Published: (2025)
Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees
by: Ospanov, Azim, et al.
Published: (2024)
by: Ospanov, Azim, et al.
Published: (2024)
PAK-UCB Contextual Bandit: An Online Learning Approach to Prompt-Aware Selection of Generative Models and LLMs
by: Hu, Xiaoyan, et al.
Published: (2024)
by: Hu, Xiaoyan, et al.
Published: (2024)
An Interpretable Evaluation of Entropy-based Novelty of Generative Models
by: Zhang, Jingwei, et al.
Published: (2024)
by: Zhang, Jingwei, et al.
Published: (2024)
Sparse Domain Transfer via Elastic Net Regularization
by: Zhang, Jingwei, et al.
Published: (2024)
by: Zhang, Jingwei, et al.
Published: (2024)
Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability
by: Ye, Zhuorui, et al.
Published: (2024)
by: Ye, Zhuorui, et al.
Published: (2024)
An Information Theoretic Approach to Interaction-Grounded Learning
by: Hu, Xiaoyan, et al.
Published: (2024)
by: Hu, Xiaoyan, et al.
Published: (2024)
Federated Ensemble Learning with Progressive Model Personalization
by: Emrani, Ala, et al.
Published: (2026)
by: Emrani, Ala, et al.
Published: (2026)
Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms
by: Rezaei, Parham, et al.
Published: (2024)
by: Rezaei, Parham, et al.
Published: (2024)
Stability and Generalization in Free Adversarial Training
by: Cheng, Xiwei, et al.
Published: (2024)
by: Cheng, Xiwei, et al.
Published: (2024)
When Kernels Multiply, Clusters Unify: Fusing Embeddings with the Kronecker Product
by: Wu, Youqi, et al.
Published: (2025)
by: Wu, Youqi, et al.
Published: (2025)
On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms
by: Lei, Haoyu, et al.
Published: (2024)
by: Lei, Haoyu, et al.
Published: (2024)
MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations
by: Wang, Zixiao, et al.
Published: (2024)
by: Wang, Zixiao, et al.
Published: (2024)
PromptWise: Online Learning for Cost-Aware Prompt Assignment in Generative Models
by: Hu, Xiaoyan, et al.
Published: (2025)
by: Hu, Xiaoyan, et al.
Published: (2025)
PromptSplit: Revealing Prompt-Level Disagreement in Generative Models
by: Lotfian, Mehdi, et al.
Published: (2026)
by: Lotfian, Mehdi, et al.
Published: (2026)
When Exploration Comes for Free with Mixture-Greedy: Do we need UCB in Diversity-Aware Multi-Armed Bandits?
by: Nia, Bahar Dibaei, et al.
Published: (2026)
by: Nia, Bahar Dibaei, et al.
Published: (2026)
Exposing Diversity Bias in Deep Generative Models: Statistical Origins and Correction of Diversity Error
by: Farnia, Farzan, et al.
Published: (2026)
by: Farnia, Farzan, et al.
Published: (2026)
Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations
by: Oskouie, Haniyeh Ehsani, et al.
Published: (2022)
by: Oskouie, Haniyeh Ehsani, et al.
Published: (2022)
On the Fragility of AI-Based Channel Decoders under Small Channel Perturbations
by: Lei, Haoyu, et al.
Published: (2026)
by: Lei, Haoyu, et al.
Published: (2026)
Towards a Scalable Reference-Free Evaluation of Generative Models
by: Ospanov, Azim, et al.
Published: (2024)
by: Ospanov, Azim, et al.
Published: (2024)
Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method
by: Sani, Matina Mahdizadeh, et al.
Published: (2024)
by: Sani, Matina Mahdizadeh, et al.
Published: (2024)
Conditional Vendi Score: An Information-Theoretic Approach to Diversity Evaluation of Prompt-based Generative Models
by: Jalali, Mohammad, et al.
Published: (2024)
by: Jalali, Mohammad, et al.
Published: (2024)
A Robust Certified Machine Unlearning Method Under Distribution Shift
by: Guo, Jinduo, et al.
Published: (2026)
by: Guo, Jinduo, et al.
Published: (2026)
Federated Learning with Profile Mapping under Distribution Shifts and Drifts
by: Li, Mohan, et al.
Published: (2026)
by: Li, Mohan, et al.
Published: (2026)
SPARKE: Scalable Prompt-Aware Diversity and Novelty Guidance in Diffusion Models via RKE Score
by: Jalali, Mohammad, et al.
Published: (2025)
by: Jalali, Mohammad, et al.
Published: (2025)
Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach
by: Zhang, Jingwei, et al.
Published: (2024)
by: Zhang, Jingwei, et al.
Published: (2024)
Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing
by: Chen, Cheng, et al.
Published: (2021)
by: Chen, Cheng, et al.
Published: (2021)
Syndrome-Flow Consistency Model Achieves One-step Denoising Error Correction Codes
by: Lei, Haoyu, et al.
Published: (2025)
by: Lei, Haoyu, et al.
Published: (2025)
Towards an Explainable Comparison and Alignment of Feature Embeddings
by: Jalali, Mohammad, et al.
Published: (2025)
by: Jalali, Mohammad, et al.
Published: (2025)
Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits
by: Guo, Yihong, et al.
Published: (2024)
by: Guo, Yihong, et al.
Published: (2024)
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees
by: Chandrasekaran, Gautam, et al.
Published: (2025)
by: Chandrasekaran, Gautam, et al.
Published: (2025)
Robust Machine Learning for Regulatory Sequence Modeling under Biological and Technical Distribution Shifts
by: Yang, Yiyao
Published: (2026)
by: Yang, Yiyao
Published: (2026)
Similar Items
-
Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
by: Sani, Matina Mahdizadeh, et al.
Published: (2026) -
Certified Adversarial Robustness via Partition-based Randomized Smoothing
by: Goli, Hossein, et al.
Published: (2024) -
On the Distributed Evaluation of Generative Models
by: Wang, Zixiao, et al.
Published: (2023) -
DAK-UCB: Diversity-Aware Prompt Routing for LLMs and Generative Models
by: Jafari, Donya, et al.
Published: (2026) -
The Maximum von Neumann Entropy Principle: Theory and Applications in Machine Learning
by: Wu, Youqi, et al.
Published: (2026)