Farzan Farnia

According to our database, Farzan Farnia authored at least 67 papers between 2013 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

VirtualHAR: Virtual Sensing Device and Correlation-Based Learning Approach for Multiwearable Sensing Device-Based Human Activity Recognition.

Nafees Ahmad, Ho-fung Leung, Farzan Farnia

IEEE Internet Things J., July, 2025

SPARKE: Scalable Prompt-Aware Diversity Guidance in Diffusion Models via RKE Score.

Mohammad Jalali, Haoyu Lei, Amin Gohari, Farzan Farnia

CoRR, June, 2025

Fusing Cross-modal and Uni-modal Representations: A Kronecker Product Approach.

Youqi Wu, Jingwei Zhang, Farzan Farnia

CoRR, June, 2025

Towards an Explainable Comparison and Alignment of Feature Embeddings.

Mohammad Jalali, Bahar Dibaei Nia, Farzan Farnia

CoRR, June, 2025

Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models.

Shizhan Gong, Yankai Jiang, Qi Dou, Farzan Farnia

CoRR, June, 2025

PromptWise: Online Learning for Cost-Aware Prompt Assignment in Generative Models.

Xiaoyan Hu, Lauren Pick, Ho-fung Leung, Farzan Farnia

CoRR, May, 2025

APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning.

Azim Ospanov, Farzan Farnia, Roozbeh Yousefzadeh

CoRR, May, 2025

DiffPattern-Flex: Efficient Layout Pattern Generation via Discrete Diffusion.

Zixiao Wang, Wenqian Zhao, Yunheng Shen, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu

CoRR, May, 2025

pFedFair: Towards Optimal Group Fairness-Accuracy Trade-off in Heterogeneous Federated Learning.

Haoyu Lei, Shizhan Gong, Qi Dou, Farzan Farnia

CoRR, March, 2025

Boosting Generalization in Diffusion-Based Neural Combinatorial Solver via Energy-guided Sampling.

Haoyu Lei, Kaiwen Zhou, Yinchuan Li, Zhitang Chen, Farzan Farnia

CoRR, February, 2025

Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees.

Azim Ospanov, Farzan Farnia

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms.

Parham Rezaei, Farzan Farnia, Cheuk Ting Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Boosting the visual interpretability of CLIP via adversarial fine-tuning.

Shizhan Gong, Haoyu Lei, Qi Dou, Farzan Farnia

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach.

Jingwei Zhang, Mohammad Jalali, Cheuk Ting Li, Farzan Farnia

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability.

Zhuorui Ye, Farzan Farnia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models.

Xiaoyan Hu, Ho-fung Leung, Farzan Farnia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Stability and Generalization in Free Adversarial Training.

Xiwei Cheng, Kexin Fu, Farzan Farnia

Trans. Mach. Learn. Res., 2024

Dissecting CLIP: Decomposition with a Schur Complement-based Approach.

Azim Ospanov, Mohammad Jalali, Farzan Farnia

CoRR, 2024

Be More Diverse than the Most Diverse: Online Selection of Diverse Mixtures of Generative Models.

Parham Rezaei, Farzan Farnia, Cheuk Ting Li

CoRR, 2024

On the Trade-Off between Stability and Fidelity of Gaussian-Smoothed Saliency Maps.

Zhuorui Ye, Farzan Farnia

CoRR, 2024

Conditional Vendi Score: An Information-Theoretic Approach to Diversity Evaluation of Prompt-based Generative Models.

Mohammad Jalali, Azim Ospanov, Amin Gohari, Farzan Farnia

CoRR, 2024

On the Statistical Complexity of Estimating VENDI Scores from Empirical Data.

Azim Ospanov, Farzan Farnia

CoRR, 2024

Robust Model Evaluation over Large-scale Federated Networks.

Amir Najafi, Samin Mahdizadeh Sani, Farzan Farnia

CoRR, 2024

An Online Learning Approach to Prompt-based Selection of Generative Models.

Xiaoyan Hu, Ho-fung Leung, Farzan Farnia

CoRR, 2024

Certified Adversarial Robustness via Partition-based Randomized Smoothing.

Hossein Goli, Farzan Farnia

CoRR, 2024

An Optimism-based Approach to Online Evaluation of Generative Models.

Xiaoyan Hu, Ho-fung Leung, Farzan Farnia

CoRR, 2024

MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations.

Zixiao Wang, Jingwei Zhang, Wenqian Zhao, Farzan Farnia, Bei Yu

CoRR, 2024

On the Mode-Seeking Properties of Langevin Dynamics.

Xiwei Cheng, Kexin Fu, Farzan Farnia

CoRR, 2024

Towards a Scalable Identification of Novel Modes in Generative Models.

Jingwei Zhang, Mohammad Jalali, Cheuk Ting Li, Farzan Farnia

CoRR, 2024

On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms.

Haoyu Lei, Amin Gohari, Farzan Farnia

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Towards a Scalable Reference-Free Evaluation of Generative Models.

Azim Ospanov, Jingwei Zhang, Mohammad Jalali, Xuenan Cao, Andrej Bogdanov, Farzan Farnia

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

An Interpretable Evaluation of Entropy-based Novelty of Generative Models.

Jingwei Zhang, Cheuk Ting Li, Farzan Farnia

Proceedings of the Forty-first International Conference on Machine Learning, 2024

An Information Theoretic Approach to Interaction-Grounded Learning.

Xiaoyan Hu, Farzan Farnia, Ho-fung Leung

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Provably Efficient CVaR RL in Low-rank MDPs.

Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ChatPattern: Layout Pattern Customization via Natural Language.

Zixiao Wang, Yunheng Shen, Xufeng Yao, Wenqian Zhao, Yang Bai, Farzan Farnia, Bei Yu

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

Structured Gradient-Based Interpretations via Norm-Regularized Adversarial Training.

Shizhan Gong, Qi Dou, Farzan Farnia

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

A Super-pixel-based Approach to the Stable Interpretation of Neural Networks.

Shizhan Gong, Jingwei Zhang, Qi Dou, Farzan Farnia

Proceedings of the 35th British Machine Vision Conference, 2024

On Convergence in Wasserstein Distance and f-divergence Minimization Problems.

Cheuk Ting Li, Jingwei Zhang, Farzan Farnia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Sparse Domain Transfer via Elastic Net Regularization.

Jingwei Zhang, Farzan Farnia

Proceedings of the Computer Vision - ACCV 2024, 2024

2023

GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models.

Farzan Farnia, William W. Wang, Subhro Das, Ali Jadbabaie

SIAM J. Math. Data Sci., March, 2023

On the Evaluation of Generative Models in Distributed Learning Tasks.

Zixiao Wang, Farzan Farnia, Zhenghao Lin, Yunheng Shen, Bei Yu

CoRR, 2023

On the Role of Generalization in Transferability of Adversarial Examples.

Yilin Wang, Farzan Farnia

Proceedings of the Uncertainty in Artificial Intelligence, 2023

An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions.

Mohammad Jalali, Cheuk Ting Li, Farzan Farnia

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope.

Jingwei Zhang, Farzan Farnia

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations.

Haniyeh Ehsani Oskouie, Farzan Farnia

Proceedings of the IEEE International Conference on Acoustics, 2023

DiffPattern: Layout Pattern Generation via Discrete Diffusion.

Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Mode-Seeking Divergences: Theory and Applications to GANs.

Cheuk Ting Li, Farzan Farnia

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

An Optimal Transport Approach to Personalized Federated Learning.

Farzan Farnia, Amirhossein Reisizadeh, Ramtin Pedarsani, Ali Jadbabaie

IEEE J. Sel. Areas Inf. Theory, 2022

Universal Adversarial Directions.

Ching Lam Choi, Farzan Farnia

CoRR, 2022

On Convergence of Gradient Descent Ascent: A Tight Local Analysis.

Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie

Proceedings of the International Conference on Machine Learning, 2022

2021

Group-Structured Adversarial Training.

Farzan Farnia, Amirali Aghazadeh, James Zou, David Tse

CoRR, 2021

Train simultaneously, generalize better: Stability of gradient-based minimax learners.

Farzan Farnia, Asuman E. Ozdaglar

Proceedings of the 38th International Conference on Machine Learning, 2021

A Wasserstein Minimax Framework for Mixed Linear Regression.

Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman E. Ozdaglar

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Understanding GANs in the LQG Setting: Formulation, Generalization and Stability.

Soheil Feizi, Farzan Farnia, Tony Ginart, David Tse

IEEE J. Sel. Areas Inf. Theory, 2020

A Fourier-Based Approach to Generalization and Optimization in Deep Learning.

Farzan Farnia, Jesse M. Zhang, David N. C. Tse

IEEE J. Sel. Areas Inf. Theory, 2020

GANs May Have No Nash Equilibria.

Farzan Farnia, Asuman E. Ozdaglar

CoRR, 2020

Robust Federated Learning: The Case of Affine Distribution Shifts.

Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Do GANs always have Nash equilibria?

Farzan Farnia, Asuman E. Ozdaglar

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Generalizable Adversarial Training via Spectral Normalization.

Farzan Farnia, Jesse M. Zhang, David Tse

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

A Convex Duality Framework for GANs.

Farzan Farnia, David Tse

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

A Minimax Approach to Supervised Learning.

Farzan Farnia, David Tse

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

On Feedback in Gaussian Multihop Networks.

Bobbie Chern, Farzan Farnia, Ayfer Özgür

IEEE Trans. Inf. Theory, 2015

Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication.

Yishun Dong, Farzan Farnia, Ayfer Özgür

IEEE J. Sel. Areas Commun., 2015

Discrete Rényi Classifiers.

Meisam Razaviyayn, Farzan Farnia, David Tse

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Minimum HGR correlation principle: From marginals to joint distribution.

Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse

Proceedings of the IEEE International Symposium on Information Theory, 2015

2014

On feedback in Gaussian multi-hop networks.

Farzan Farnia, Ayfer Özgür

Proceedings of the 2014 Information Theory and Applications Workshop, 2014

2013

Asymptotic behavior of network capacity under spatial network coding.

Farzan Farnia, S. Jamaloddin Golestani

Proceedings of the 2013 IEEE Wireless Communications and Networking Conference (WCNC), 2013