← Authors

Farzan Farnia

33 papers · 2015–2026 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (38) 🧭 Keyword Pioneer πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) ❓ The Questioner (2) πŸ—ƒοΈ Keyword Collector (79) πŸ”₯ Unstoppable (8) ⚑ Prolific Year (7) πŸ’Ž Century Club (32)

Conferences

ICML (11) NIPS (6) AISTATS (4) ICLR (4) UAI (3) CVPR (2) ICCV (2) AAAI (1)

Top co-authors

Cheuk Ting Li (6) Jingwei Zhang (5) Mohammad Jalali (5) Xiaoyan Hu (4) David Tse (4) Ho-fung Leung (4) Haoyu LEI (3) Qi Dou (3) Shizhan Gong (3) Azim Ospanov (3)

Keywords

generative adversarial network (6) minimax optimization (6) wasserstein distance (5) generative model (4) neural network interpretability (2) federated learning (2) neural network (2) random fourier feature (2) generalization bound (2) adversarial training (2) jensen-shannon divergence (2) gradient descent (2) group sparsity (1) binary classification (1) text-to-image generation (1) divergence minimization (1) distribution shift (1) supervised learning (1) mixed linear regression (1) algorithmic stability (1)

Papers

Boosting Cross-problem Generalization in Diffusion-Based Neural Combinatorial Solver via Inference Time Adaptation AAAI 2026
Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms ICLR 2025
A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models AISTATS 2025
Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability AISTATS 2025
Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach CVPR 2025
Scendi Score: Prompt-Aware Diversity Evaluation via Schur Complement of CLIP Embeddings ICCV 2025
Boosting the visual interpretability of CLIP via adversarial fine-tuning ICLR 2025
Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models ICML 2025
PAK-UCB Contextual Bandit: An Online Learning Approach to Prompt-Aware Selection of Generative Models and LLMs ICML 2025
Towards an Explainable Comparison and Alignment of Feature Embeddings ICML 2025
Multilayer Matrix Factorization via Dimension-Reducing Diffusion Variational Inference ICML 2025
Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional Shifts ICML 2025
Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees UAI 2025
Towards a Scalable Reference-Free Evaluation of Generative Models NIPS 2024
An Interpretable Evaluation of Entropy-based Novelty of Generative Models ICML 2024
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training CVPR 2024
On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms UAI 2024
An Information Theoretic Approach to Interaction-Grounded Learning ICML 2024
Provably Efficient CVaR RL in Low-rank MDPs ICLR 2024
On Convergence in Wasserstein Distance and f-divergence Minimization Problems AISTATS 2024
Mode-Seeking Divergences: Theory and Applications to GANs AISTATS 2023
On the Role of Generalization in Transferability of Adversarial Examples UAI 2023
MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope ICCV 2023
An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions NIPS 2023
On Convergence of Gradient Descent Ascent: A Tight Local Analysis ICML 2022
A Wasserstein Minimax Framework for Mixed Linear Regression ICML 2021
Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021
Robust Federated Learning: The Case of Affine Distribution Shifts NIPS 2020
Do GANs always have Nash equilibria? ICML 2020
Generalizable Adversarial Training via Spectral Normalization ICLR 2019
A Convex Duality Framework for GANs NIPS 2018
A Minimax Approach to Supervised Learning NIPS 2016
Discrete RΓ©nyi Classifiers NIPS 2015