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ORCIDFarzan Farnia
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2020 – today
- 2024
[c24]Cheuk Ting Li, Jingwei Zhang, Farzan Farnia:
On Convergence in Wasserstein Distance and f-divergence Minimization Problems. AISTATS 2024: 2062-2070- [c23]Shizhan Gong, Qi Dou, Farzan Farnia:
Structured Gradient-Based Interpretations via Norm-Regularized Adversarial Training. CVPR 2024: 11009-11018 - [c22]Zixiao Wang, Yunheng Shen, Xufeng Yao, Wenqian Zhao, Yang Bai, Farzan Farnia, Bei Yu:
ChatPattern: Layout Pattern Customization via Natural Language. DAC 2024: 87:1-87:6 - [c21]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 - [c20]Xiaoyan Hu, Farzan Farnia, Ho-fung Leung:
An Information Theoretic Approach to Interaction-Grounded Learning. ICML 2024 - [c19]Jingwei Zhang, Cheuk Ting Li, Farzan Farnia:
An Interpretable Evaluation of Entropy-based Novelty of Generative Models. ICML 2024 - [i34]Xiaoyan Hu, Farzan Farnia, Ho-fung Leung:
An Information Theoretic Approach to Interaction-Grounded Learning. CoRR abs/2401.05015 (2024) - [i33]Jingwei Zhang, Cheuk Ting Li, Farzan Farnia:
An Interpretable Evaluation of Entropy-based Novelty of Generative Models. CoRR abs/2402.17287 (2024) - [i32]Haoyu Lei, Amin Gohari, Farzan Farnia:
On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms. CoRR abs/2402.18129 (2024) - [i31]Zixiao Wang, Yunheng Shen, Xufeng Yao, Wenqian Zhao, Yang Bai, Farzan Farnia, Bei Yu:
ChatPattern: Layout Pattern Customization via Natural Language. CoRR abs/2403.15434 (2024) - [i30]Shizhan Gong, Qi Dou, Farzan Farnia:
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training. CoRR abs/2404.04647 (2024) - [i29]Xiwei Cheng, Kexin Fu, Farzan Farnia:
Stability and Generalization in Free Adversarial Training. CoRR abs/2404.08980 (2024) - [i28]Jingwei Zhang, Mohammad Jalali, Cheuk Ting Li, Farzan Farnia:
Towards a Scalable Identification of Novel Modes in Generative Models. CoRR abs/2405.02700 (2024) - [i27]Jingwei Zhang, Farzan Farnia:
Sparse Domain Transfer via Elastic Net Regularization. CoRR abs/2405.07489 (2024) - [i26]Xiwei Cheng, Kexin Fu, Farzan Farnia:
On the Mode-Seeking Properties of Langevin Dynamics. CoRR abs/2406.02017 (2024) - [i25]Zixiao Wang, Jingwei Zhang, Wenqian Zhao, Farzan Farnia, Bei Yu:
MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations. CoRR abs/2406.07017 (2024) - [i24]Xiaoyan Hu, Ho-fung Leung, Farzan Farnia:
An Optimism-based Approach to Online Evaluation of Generative Models. CoRR abs/2406.07451 (2024) - [i23]Azim Ospanov, Jingwei Zhang, Mohammad Jalali, Xuenan Cao, Andrej Bogdanov, Farzan Farnia:
Towards a Scalable Reference-Free Evaluation of Generative Models. CoRR abs/2407.02961 (2024) - [i22]Hossein Goli, Farzan Farnia:
Certified Adversarial Robustness via Partition-based Randomized Smoothing. CoRR abs/2409.13546 (2024) - 2023
- [j6]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): 122-146 (2023) - [c18]Cheuk Ting Li, Farzan Farnia:
Mode-Seeking Divergences: Theory and Applications to GANs. AISTATS 2023: 8321-8350 - [c17]Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu:
DiffPattern: Layout Pattern Generation via Discrete Diffusion. DAC 2023: 1-6 - [c16]Haniyeh Ehsani Oskouie, Farzan Farnia:
Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations. ICASSP 2023: 1-5 - [c15]Jingwei Zhang, Farzan Farnia:
MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope. ICCV 2023: 2021-2030 - [c14]Mohammad Jalali, Cheuk Ting Li, Farzan Farnia:
An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions. NeurIPS 2023 - [c13]Yilin Wang, Farzan Farnia:
On the Role of Generalization in Transferability of Adversarial Examples. UAI 2023: 2259-2270 - [i21]Jingwei Zhang, Farzan Farnia:
MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope. CoRR abs/2302.05294 (2023) - [i20]Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu:
DiffPattern: Layout Pattern Generation via Discrete Diffusion. CoRR abs/2303.13060 (2023) - [i19]Zixiao Wang, Farzan Farnia, Zhenghao Lin, Yunheng Shen, Bei Yu:
On the Evaluation of Generative Models in Distributed Learning Tasks. CoRR abs/2310.11714 (2023) - [i18]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 abs/2311.11965 (2023) - 2022
- [j5]Farzan Farnia, Amirhossein Reisizadeh, Ramtin Pedarsani, Ali Jadbabaie:
An Optimal Transport Approach to Personalized Federated Learning. IEEE J. Sel. Areas Inf. Theory 3(2): 162-171 (2022) - [c12]Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie:
On Convergence of Gradient Descent Ascent: A Tight Local Analysis. ICML 2022: 12717-12740 - [i17]Farzan Farnia, Amirhossein Reisizadeh, Ramtin Pedarsani, Ali Jadbabaie:
An Optimal Transport Approach to Personalized Federated Learning. CoRR abs/2206.02468 (2022) - [i16]Yilin Wang, Farzan Farnia:
On the Role of Generalization in Transferability of Adversarial Examples. CoRR abs/2206.09238 (2022) - [i15]Haochuan Li, Farzan Farnia, Subhro Das, Ali Jadbabaie:
On Convergence of Gradient Descent Ascent: A Tight Local Analysis. CoRR abs/2207.00957 (2022) - [i14]Ching Lam Choi, Farzan Farnia:
Universal Adversarial Directions. CoRR abs/2210.15997 (2022) - [i13]Haniyeh Ehsani Oskouie, Farzan Farnia:
Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations. CoRR abs/2212.03095 (2022) - 2021
- [c11]Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman E. Ozdaglar:
A Wasserstein Minimax Framework for Mixed Linear Regression. ICML 2021: 2697-2706 - [c10]Farzan Farnia, Asuman E. Ozdaglar:
Train simultaneously, generalize better: Stability of gradient-based minimax learners. ICML 2021: 3174-3185 - [i12]Theo Diamandis, Yonina C. Eldar, Alireza Fallah, Farzan Farnia, Asuman E. Ozdaglar:
A Wasserstein Minimax Framework for Mixed Linear Regression. CoRR abs/2106.07537 (2021) - [i11]Farzan Farnia, Amirali Aghazadeh, James Zou, David Tse:
Group-Structured Adversarial Training. CoRR abs/2106.10324 (2021) - 2020
- [j4]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): 145-156 (2020) - [j3]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): 304-311 (2020) - [c9]Farzan Farnia, Asuman E. Ozdaglar:
Do GANs always have Nash equilibria? ICML 2020: 3029-3039 - [c8]Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie:
Robust Federated Learning: The Case of Affine Distribution Shifts. NeurIPS 2020 - [i10]Farzan Farnia, Asuman E. Ozdaglar:
GANs May Have No Nash Equilibria. CoRR abs/2002.09124 (2020) - [i9]Amirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie:
Robust Federated Learning: The Case of Affine Distribution Shifts. CoRR abs/2006.08907 (2020) - [i8]Farzan Farnia, William Wang, Subhro Das, Ali Jadbabaie:
GAT-GMM: Generative Adversarial Training for Gaussian Mixture Models. CoRR abs/2006.10293 (2020) - [i7]Farzan Farnia, Asuman E. Ozdaglar:
Train simultaneously, generalize better: Stability of gradient-based minimax learners. CoRR abs/2010.12561 (2020)
2010 – 2019
- 2019
- [c7]Farzan Farnia, Jesse M. Zhang, David Tse:
Generalizable Adversarial Training via Spectral Normalization. ICLR (Poster) 2019 - 2018
- [c6]Farzan Farnia, David Tse:
A Convex Duality Framework for GANs. NeurIPS 2018: 5254-5263 - [i6]Farzan Farnia, David Tse:
A Convex Duality Framework for GANs. CoRR abs/1810.11740 (2018) - [i5]Farzan Farnia, Jesse M. Zhang, David Tse:
Generalizable Adversarial Training via Spectral Normalization. CoRR abs/1811.07457 (2018) - 2016
- [c5]Farzan Farnia, David Tse:
A Minimax Approach to Supervised Learning. NIPS 2016: 4233-4241 - [i4]Farzan Farnia, David Tse:
A Minimax Approach to Supervised Learning. CoRR abs/1606.02206 (2016) - 2015
- [j2]Yishun Dong, Farzan Farnia, Ayfer Özgür:
Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication. IEEE J. Sel. Areas Commun. 33(3): 540-557 (2015) - [j1]Bobbie Chern, Farzan Farnia, Ayfer Özgür:
On Feedback in Gaussian Multihop Networks. IEEE Trans. Inf. Theory 61(7): 3763-3772 (2015) - [c4]Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse:
Minimum HGR correlation principle: From marginals to joint distribution. ISIT 2015: 1377-1381 - [c3]Meisam Razaviyayn, Farzan Farnia, David Tse:
Discrete Rényi Classifiers. NIPS 2015: 3276-3284 - [i3]Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse:
Minimum HGR Correlation Principle: From Marginals to Joint Distribution. CoRR abs/1504.06010 (2015) - [i2]Meisam Razaviyayn, Farzan Farnia, David N. C. Tse:
Discrete Rényi Classifiers. CoRR abs/1511.01764 (2015) - 2014
- [c2]Farzan Farnia, Ayfer Özgür:
On feedback in Gaussian multi-hop networks. ITA 2014: 1-5 - [i1]Yishun Dong, Farzan Farnia, Ayfer Özgür:
Near Optimal Energy Control and Approximate Capacity of Energy Harvesting Communication. CoRR abs/1405.1156 (2014) - 2013
- [c1]Farzan Farnia, S. Jamaloddin Golestani:
Asymptotic behavior of network capacity under spatial network coding. WCNC 2013: 2434-2439
Coauthor Index
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last updated on 2024-11-14 22:05 CET by the dblp team
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