Farzan Farnia

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 50

Top Topics

Pattern Generation

Gaussian Mixture

Asymptotic Properties

Supervised Learning

Top Venues

IEEE J. Sel. Areas Inf. Theory

Publications

Haoyu Lei, Amin Gohari, Farzan Farnia
On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms. CoRR (2024)
Zixiao Wang, Jingwei Zhang, Wenqian Zhao, Farzan Farnia, Bei Yu
MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations. CoRR (2024)
Zixiao Wang, Yunheng Shen, Xufeng Yao, Wenqian Zhao, Yang Bai, Farzan Farnia, Bei Yu
ChatPattern: Layout Pattern Customization via Natural Language. CoRR (2024)
Cheuk Ting Li, Jingwei Zhang, Farzan Farnia
On Convergence in Wasserstein Distance and f-divergence Minimization Problems. AISTATS (2024)
Xiwei Cheng, Kexin Fu, Farzan Farnia
Stability and Generalization in Free Adversarial Training. CoRR (2024)
Jingwei Zhang, Cheuk Ting Li, Farzan Farnia
An Interpretable Evaluation of Entropy-based Novelty of Generative Models. CoRR (2024)
Azim Ospanov, Jingwei Zhang, Mohammad Jalali, Xuenan Cao, Andrej Bogdanov, Farzan Farnia
Towards a Scalable Reference-Free Evaluation of Generative Models. CoRR (2024)
Xiaoyan Hu, Ho-fung Leung, Farzan Farnia
An Optimism-based Approach to Online Evaluation of Generative Models. CoRR (2024)
Xiwei Cheng, Kexin Fu, Farzan Farnia
On the Mode-Seeking Properties of Langevin Dynamics. CoRR (2024)
Jingwei Zhang, Mohammad Jalali, Cheuk Ting Li, Farzan Farnia
Towards a Scalable Identification of Novel Modes in Generative Models. CoRR (2024)
Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee
Provably Efficient CVaR RL in Low-rank MDPs. ICLR (2024)
Shizhan Gong, Qi Dou, Farzan Farnia
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training. CoRR (2024)
Jingwei Zhang, Farzan Farnia
Sparse Domain Transfer via Elastic Net Regularization. CoRR (2024)
Xiaoyan Hu, Farzan Farnia, Ho-fung Leung
An Information Theoretic Approach to Interaction-Grounded Learning. CoRR (2024)
Yulai Zhao, Wenhao Zhan, Xiaoyan Hu, Ho-fung Leung, Farzan Farnia, Wen Sun, Jason D. Lee
Provably Efficient CVaR RL in Low-rank MDPs. CoRR (2023)
Cheuk Ting Li, Farzan Farnia
Mode-Seeking Divergences: Theory and Applications to GANs. AISTATS (2023)
Jingwei Zhang, Farzan Farnia
MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope. CoRR (2023)
Farzan Farnia, William W. Wang, Subhro Das, Ali Jadbabaie
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models. SIAM J. Math. Data Sci. 5 (1) (2023)
Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu
DiffPattern: Layout Pattern Generation via Discrete Diffusion. CoRR (2023)
Mohammad Jalali, Cheuk Ting Li, Farzan Farnia
An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions. NeurIPS (2023)
Zixiao Wang, Farzan Farnia, Zhenghao Lin, Yunheng Shen, Bei Yu
On the Evaluation of Generative Models in Distributed Learning Tasks. CoRR (2023)
Jingwei Zhang, Farzan Farnia
MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope. ICCV (2023)
Haniyeh Ehsani Oskouie, Farzan Farnia
Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations. ICASSP (2023)
Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu
DiffPattern: Layout Pattern Generation via Discrete Diffusion. DAC (2023)
Yilin Wang, Farzan Farnia
On the Role of Generalization in Transferability of Adversarial Examples. UAI (2023)
Farzan Farnia, Amirhossein Reisizadeh, Ramtin Pedarsani, Ali Jadbabaie
An Optimal Transport Approach to Personalized Federated Learning. IEEE J. Sel. Areas Inf. Theory 3 (2) (2022)
Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie
On Convergence of Gradient Descent Ascent: A Tight Local Analysis. ICML (2022)
Farzan Farnia, Amirhossein Reisizadeh, Ramtin Pedarsani, Ali Jadbabaie
An Optimal Transport Approach to Personalized Federated Learning. CoRR (2022)
Yilin Wang, Farzan Farnia
On the Role of Generalization in Transferability of Adversarial Examples. CoRR (2022)
Haniyeh Ehsani Oskouie, Farzan Farnia
Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations. CoRR (2022)
Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie
On Convergence of Gradient Descent Ascent: A Tight Local Analysis. CoRR (2022)
Ching Lam Choi, Farzan Farnia
Universal Adversarial Directions. CoRR (2022)
Farzan Farnia, Asuman E. Ozdaglar
Train simultaneously, generalize better: Stability of gradient-based minimax learners. ICML (2021)
Farzan Farnia, Amirali Aghazadeh, James Zou, David Tse
Group-Structured Adversarial Training. CoRR (2021)
Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman E. Ozdaglar
A Wasserstein Minimax Framework for Mixed Linear Regression. ICML (2021)
Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman E. Ozdaglar
A Wasserstein Minimax Framework for Mixed Linear Regression. CoRR (2021)
Farzan Farnia, William Wang, Subhro Das, Ali Jadbabaie
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models. CoRR (2020)
Farzan Farnia, Asuman E. Ozdaglar
Train simultaneously, generalize better: Stability of gradient-based minimax learners. CoRR (2020)
Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie
Robust Federated Learning: The Case of Affine Distribution Shifts. CoRR (2020)
Farzan Farnia, Asuman E. Ozdaglar
Do GANs always have Nash equilibria? ICML (2020)
Farzan Farnia, Jesse M. Zhang, David N. C. Tse
A Fourier-Based Approach to Generalization and Optimization in Deep Learning. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie
Robust Federated Learning: The Case of Affine Distribution Shifts. NeurIPS (2020)
Farzan Farnia, Asuman E. Ozdaglar
GANs May Have No Nash Equilibria. CoRR (2020)
Soheil Feizi, Farzan Farnia, Tony Ginart, David Tse
Understanding GANs in the LQG Setting: Formulation, Generalization and Stability. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Farzan Farnia, Jesse M. Zhang, David Tse
Generalizable Adversarial Training via Spectral Normalization. ICLR (Poster) (2019)
Farzan Farnia, David Tse
A Convex Duality Framework for GANs. NeurIPS (2018)
Farzan Farnia, Jesse M. Zhang, David Tse
Generalizable Adversarial Training via Spectral Normalization. CoRR (2018)
Farzan Farnia, David Tse
A Convex Duality Framework for GANs. CoRR (2018)
Farzan Farnia, David Tse
A Minimax Approach to Supervised Learning. CoRR (2016)
Farzan Farnia, David Tse
A Minimax Approach to Supervised Learning. NIPS (2016)
Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse
Minimum HGR correlation principle: From marginals to joint distribution. ISIT (2015)
Meisam Razaviyayn, Farzan Farnia, David N. C. Tse
Discrete Rényi Classifiers. CoRR (2015)
Yishun Dong, Farzan Farnia, Ayfer Özgür
Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication. IEEE J. Sel. Areas Commun. 33 (3) (2015)
Meisam Razaviyayn, Farzan Farnia, David Tse
Discrete Rényi Classifiers. NIPS (2015)
Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse
Minimum HGR Correlation Principle: From Marginals to Joint Distribution. CoRR (2015)
Bobbie Chern, Farzan Farnia, Ayfer Özgür
On Feedback in Gaussian Multihop Networks. IEEE Trans. Inf. Theory 61 (7) (2015)
Farzan Farnia, Ayfer Özgür
On feedback in Gaussian multi-hop networks. ITA (2014)
Yishun Dong, Farzan Farnia, Ayfer Özgür
Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication. CoRR (2014)
Farzan Farnia, S. Jamaloddin Golestani
Asymptotic behavior of network capacity under spatial network coding. WCNC (2013)