Asymptotic behavior of network capacity under spatial network coding. - Farzan Farnia; S. Jamaloddin Golestani (WCNC, 2013)

On feedback in Gaussian multi-hop networks. - Farzan Farnia; Ayfer Özgür (ITA, 2014)

Minimum HGR correlation principle: From marginals to joint distribution. - Farzan Farnia; Meisam Razaviyayn; Sreeram Kannan; David Tse (ISIT, 2015)

Discrete Rényi Classifiers. - Meisam Razaviyayn; Farzan Farnia; David Tse (NIPS, 2015)

Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication. - Yishun Dong; Farzan Farnia; Ayfer Özgür (IEEE J. Sel. Areas Commun., 2015)

On Feedback in Gaussian Multihop Networks. - Bobbie Chern; Farzan Farnia; Ayfer Özgür (IEEE Trans. Inf. Theory, 2015)

A Minimax Approach to Supervised Learning. - Farzan Farnia; David Tse (NIPS, 2016)

A Convex Duality Framework for GANs. - Farzan Farnia; David Tse (NeurIPS, 2018)

Generalizable Adversarial Training via Spectral Normalization. - Farzan Farnia; Jesse M. Zhang; David Tse (ICLR (Poster), 2019)

Do GANs always have Nash equilibria? - Farzan Farnia; Asuman E. Ozdaglar (ICML, 2020)

Robust Federated Learning: The Case of Affine Distribution Shifts. - Amirhossein Reisizadeh; Farzan Farnia; Ramtin Pedarsani; Ali Jadbabaie (NeurIPS, 2020)

GANs May Have No Nash Equilibria. - Farzan Farnia; Asuman E. Ozdaglar (CoRR, 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)

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 Wasserstein Minimax Framework for Mixed Linear Regression. - Theo Diamandis; Yonina C. Eldar; Alireza Fallah 001; Farzan Farnia; Asuman E. Ozdaglar (ICML, 2021)

Train simultaneously, generalize better: Stability of gradient-based minimax learners. - Farzan Farnia; Asuman E. Ozdaglar (ICML, 2021)

Group-Structured Adversarial Training. - Farzan Farnia; Amirali Aghazadeh; James Zou 001; David Tse (CoRR, 2021)

On Convergence of Gradient Descent Ascent: A Tight Local Analysis. - Haochuan Li; Farzan Farnia; Subhro Das; Ali Jadbabaie (ICML, 2022)

Universal Adversarial Directions. - Ching Lam Choi; Farzan Farnia (CoRR, 2022)

An Optimal Transport Approach to Personalized Federated Learning. - Farzan Farnia; Amirhossein Reisizadeh; Ramtin Pedarsani; Ali Jadbabaie (IEEE J. Sel. Areas Inf. Theory, 2022)

Mode-Seeking Divergences: Theory and Applications to GANs. - Cheuk Ting Li; Farzan Farnia (AISTATS, 2023)

DiffPattern: Layout Pattern Generation via Discrete Diffusion. - Zixiao Wang 001; Yunheng Shen; Wenqian Zhao 002; Yang Bai; Guojin Chen; Farzan Farnia; Bei Yu 001 (DAC, 2023)

Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations. - Haniyeh Ehsani Oskouie; Farzan Farnia (ICASSP, 2023)

MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope. - Jingwei Zhang; Farzan Farnia (ICCV, 2023)

An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions. - Mohammad Jalali; Cheuk Ting Li; Farzan Farnia (NeurIPS, 2023)

On the Role of Generalization in Transferability of Adversarial Examples. - Yilin Wang; Farzan Farnia (UAI, 2023)

On the Evaluation of Generative Models in Distributed Learning Tasks. - Zixiao Wang 001; Farzan Farnia; Zhenghao Lin; Yunheng Shen; Bei Yu 001 (CoRR, 2023)

GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models. - Farzan Farnia; William W. Wang; Subhro Das; Ali Jadbabaie (SIAM J. Math. Data Sci., 2023)

Sparse Domain Transfer via Elastic Net Regularization. - Jingwei Zhang; Farzan Farnia (ACCV (5), 2024)

On Convergence in Wasserstein Distance and f-divergence Minimization Problems. - Cheuk Ting Li; Jingwei Zhang; Farzan Farnia (AISTATS, 2024)

A Super-pixel-based Approach to the Stable Interpretation of Neural Networks. - Shizhan Gong; Jingwei Zhang; Qi Dou 001; Farzan Farnia (BMVC, 2024)

Structured Gradient-Based Interpretations via Norm-Regularized Adversarial Training. - Shizhan Gong; Qi Dou 001; Farzan Farnia (CVPR, 2024)

ChatPattern: Layout Pattern Customization via Natural Language. - Zixiao Wang 001; Yunheng Shen; Xufeng Yao; Wenqian Zhao 002; Yang Bai; Farzan Farnia; Bei Yu 001 (DAC, 2024)

Provably Efficient CVaR RL in Low-rank MDPs. - Yulai Zhao 002; Wenhao Zhan; Xiaoyan Hu 003; Ho-fung Leung; Farzan Farnia; Wen Sun 002; Jason D. Lee (ICLR, 2024)

An Information Theoretic Approach to Interaction-Grounded Learning. - Xiaoyan Hu 003; Farzan Farnia; Ho-fung Leung (ICML, 2024)

An Interpretable Evaluation of Entropy-based Novelty of Generative Models. - Jingwei Zhang; Cheuk Ting Li; Farzan Farnia (ICML, 2024)

Towards a Scalable Reference-Free Evaluation of Generative Models. - Azim Ospanov; Jingwei Zhang; Mohammad Jalali; Xuenan Cao; Andrej Bogdanov; Farzan Farnia (NeurIPS, 2024)

On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms. - Haoyu Lei; Amin Gohari; Farzan Farnia (UAI, 2024)

Towards a Scalable Identification of Novel Modes in Generative Models. - Jingwei Zhang; Mohammad Jalali; Cheuk Ting Li; Farzan Farnia (CoRR, 2024)

On the Mode-Seeking Properties of Langevin Dynamics. - Xiwei Cheng; Kexin Fu; Farzan Farnia (CoRR, 2024)

MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations. - Zixiao Wang 001; Jingwei Zhang; Wenqian Zhao 002; Farzan Farnia; Bei Yu 001 (CoRR, 2024)

An Optimism-based Approach to Online Evaluation of Generative Models. - Xiaoyan Hu 003; Ho-fung Leung; Farzan Farnia (CoRR, 2024)

Certified Adversarial Robustness via Partition-based Randomized Smoothing. - Hossein Goli; Farzan Farnia (CoRR, 2024)

An Online Learning Approach to Prompt-based Selection of Generative Models. - Xiaoyan Hu 003; Ho-fung Leung; Farzan Farnia (CoRR, 2024)

Robust Model Evaluation over Large-scale Federated Networks. - Amir Najafi 002; Samin Mahdizadeh Sani; Farzan Farnia (CoRR, 2024)

On the Statistical Complexity of Estimating VENDI Scores from Empirical Data. - Azim Ospanov; 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 Trade-Off between Stability and Fidelity of Gaussian-Smoothed Saliency Maps. - Zhuorui Ye; 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)

Dissecting CLIP: Decomposition with a Schur Complement-based Approach. - Azim Ospanov; Mohammad Jalali; Farzan Farnia (CoRR, 2024)

Stability and Generalization in Free Adversarial Training. - Xiwei Cheng; Kexin Fu; Farzan Farnia (Trans. Mach. Learn. Res., 2024)

A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models. - Xiaoyan Hu 003; Ho-fung Leung; Farzan Farnia (AISTATS, 2025)

Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability. - Zhuorui Ye; Farzan Farnia (AISTATS, 2025)

Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach. - Jingwei Zhang; Mohammad Jalali; Cheuk Ting Li; Farzan Farnia (CVPR, 2025)

Boosting the visual interpretability of CLIP via adversarial fine-tuning. - Shizhan Gong; Haoyu Lei; Qi Dou 001; Farzan Farnia (ICLR, 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 (ICLR, 2025)

Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees. - Azim Ospanov; Farzan Farnia (UAI, 2025)

Boosting Generalization in Diffusion-Based Neural Combinatorial Solver via Energy-guided Sampling. - Haoyu Lei; Kaiwen Zhou; Yinchuan Li; Zhitang Chen; Farzan Farnia (CoRR, 2025)

pFedFair: Towards Optimal Group Fairness-Accuracy Trade-off in Heterogeneous Federated Learning. - Haoyu Lei; Shizhan Gong; Qi Dou 001; Farzan Farnia (CoRR, 2025)

DiffPattern-Flex: Efficient Layout Pattern Generation via Discrete Diffusion. - Zixiao Wang 001; Wenqian Zhao 002; Yunheng Shen; Yang Bai; Guojin Chen; Farzan Farnia; Bei Yu 001 (CoRR, 2025)

APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning. - Azim Ospanov; Farzan Farnia; Roozbeh Yousefzadeh (CoRR, 2025)

PromptWise: Online Learning for Cost-Aware Prompt Assignment in Generative Models. - Xiaoyan Hu 003; Lauren Pick; Ho-fung Leung; Farzan Farnia (CoRR, 2025)

Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models. - Shizhan Gong; Yankai Jiang 003; Qi Dou 001; Farzan Farnia (CoRR, 2025)

Towards an Explainable Comparison and Alignment of Feature Embeddings. - Mohammad Jalali; Bahar Dibaei Nia; Farzan Farnia (CoRR, 2025)

Fusing Cross-modal and Uni-modal Representations: A Kronecker Product Approach. - Youqi Wu; Jingwei Zhang; Farzan Farnia (CoRR, 2025)

SPARKE: Scalable Prompt-Aware Diversity Guidance in Diffusion Models via RKE Score. - Mohammad Jalali; Haoyu Lei; Amin Gohari; Farzan Farnia (CoRR, 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., 2025)

PermLLM: Learnable Channel Permutation for N:M Sparse Large Language Models. - Lancheng Zou; Shuo Yin; Zehua Pei; Tsung-Yi Ho; Farzan Farnia; Bei Yu 001 (CoRR, 2025)