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Maziar Sanjabi
Maziar Sanjabi Boroujeni
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2020 – today
- 2024
- [c32]Neha Mukund Kalibhat, Kanika Narang, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features. AAAI 2024: 13031-13039 - [c31]Samyadeep Basu, Shell Xu Hu, Maziar Sanjabi, Daniela Massiceti, Soheil Feizi:
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP. EMNLP 2024: 6105-6113 - [c30]Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Oliviero Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
Differentially Private Representation Learning via Image Captioning. ICML 2024 - [c29]Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
ViP: A Differentially Private Foundation Model for Computer Vision. ICML 2024 - [c28]Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, Asli Celikyilmaz:
RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models. NAACL-HLT 2024: 5784-5809 - [i41]Tom Sander, Yaodong Yu, Maziar Sanjabi, Alain Durmus, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
Differentially Private Representation Learning via Image Captioning. CoRR abs/2403.02506 (2024) - [i40]Jonathan Lebensold, Maziar Sanjabi, Pietro Astolfi, Adriana Romero-Soriano, Kamalika Chaudhuri, Mike Rabbat, Chuan Guo:
DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-Tuning. CoRR abs/2403.14421 (2024) - [i39]Hamed Firooz, Maziar Sanjabi, Wenlong Jiang, Xiaoling Zhai:
Lost-in-Distance: Impact of Contextual Proximity on LLM Performance in Graph Tasks. CoRR abs/2410.01985 (2024) - 2023
- [j9]Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith:
On Tilted Losses in Machine Learning: Theory and Applications. J. Mach. Learn. Res. 24: 142:1-142:79 (2023) - [c27]Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi:
Text2Concept: Concept Activation Vectors Directly from Text. CVPR Workshops 2023: 3744-3749 - [c26]Ajinkya Tejankar, Maziar Sanjabi, Qifan Wang, Sinong Wang, Hamed Firooz, Hamed Pirsiavash, Liang Tan:
Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning. CVPR 2023: 12239-12249 - [c25]Nan Wang, Qifan Wang, Yi-Chia Wang, Maziar Sanjabi, Jingzhou Liu
, Hamed Firooz, Hongning Wang, Shaoliang Nie:
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation. EMNLP 2023: 13258-13275 - [c24]John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat:
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. ICLR 2023 - [c23]Chuan Guo, Alexandre Sablayrolles, Maziar Sanjabi:
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano. ICML 2023: 11998-12011 - [c22]Neha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Identifying Interpretable Subspaces in Image Representations. ICML 2023: 15623-15638 - [c21]Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi:
Text-To-Concept (and Back) via Cross-Model Alignment. ICML 2023: 25037-25060 - [i38]Ajinkya Tejankar, Maziar Sanjabi, Qifan Wang, Sinong Wang, Hamed Firooz, Hamed Pirsiavash, Liang Tan:
Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning. CoRR abs/2304.01482 (2023) - [i37]Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi:
Text-To-Concept (and Back) via Cross-Model Alignment. CoRR abs/2305.06386 (2023) - [i36]Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo:
ViP: A Differentially Private Foundation Model for Computer Vision. CoRR abs/2306.08842 (2023) - [i35]Samyadeep Basu, Maziar Sanjabi, Daniela Massiceti, Shell Xu Hu, Soheil Feizi:
Augmenting CLIP with Improved Visio-Linguistic Reasoning. CoRR abs/2307.09233 (2023) - [i34]Neha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Identifying Interpretable Subspaces in Image Representations. CoRR abs/2307.10504 (2023) - [i33]Samyadeep Basu, Mehrdad Saberi, Shweta Bhardwaj, Atoosa Malemir Chegini, Daniela Massiceti, Maziar Sanjabi, Shell Xu Hu, Soheil Feizi:
EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods. CoRR abs/2310.02426 (2023) - [i32]Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, Asli Celikyilmaz:
Resprompt: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models. CoRR abs/2310.04743 (2023) - [i31]Animesh Sinha, Bo Sun, Anmol Kalia, Arantxa Casanova, Elliot Blanchard, David Yan, Winnie Zhang, Tony Nelli, Jiahui Chen, Hardik Shah, Licheng Yu, Mitesh Kumar Singh, Ankit Ramchandani, Maziar Sanjabi, Sonal Gupta, Amy Bearman, Dhruv Mahajan:
Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression. CoRR abs/2311.10794 (2023) - 2022
- [j8]Samuel Horváth, Maziar Sanjabi, Lin Xiao, Peter Richtárik, Michael G. Rabbat:
FedShuffle: Recipes for Better Use of Local Work in Federated Learning. Trans. Mach. Learn. Res. 2022 (2022) - [c20]Khalil Mrini, Shaoliang Nie, Jiatao Gu, Sinong Wang, Maziar Sanjabi, Hamed Firooz:
Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problem. ACL (Findings) 2022: 1972-1983 - [c19]Brihi Joshi, Aaron Chan, Ziyi Liu, Shaoliang Nie, Maziar Sanjabi, Hamed Firooz, Xiang Ren:
ER-Test: Evaluating Explanation Regularization Methods for Language Models. EMNLP (Findings) 2022: 3315-3336 - [c18]Aaron Chan, Maziar Sanjabi, Lambert Mathias, Liang Tan, Shaoliang Nie, Xiaochang Peng, Xiang Ren, Hamed Firooz:
UNIREX: A Unified Learning Framework for Language Model Rationale Extraction. ICML 2022: 2867-2889 - [c17]Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael G. Rabbat, Maziar Sanjabi, Lin Xiao:
Federated Learning with Partial Model Personalization. ICML 2022: 17716-17758 - [i30]Nimit Sharad Sohoni, Maziar Sanjabi, Nicolas Ballas, Aditya Grover, Shaoliang Nie, Hamed Firooz, Christopher Ré:
BARACK: Partially Supervised Group Robustness With Guarantees. CoRR abs/2201.00072 (2022) - [i29]Neha Mukund Kalibhat, Kanika Narang, Liang Tan, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Understanding Failure Modes of Self-Supervised Learning. CoRR abs/2203.01881 (2022) - [i28]Krishna Pillutla, Kshitiz Malik, Abdelrahman Mohamed, Michael G. Rabbat, Maziar Sanjabi, Lin Xiao:
Federated Learning with Partial Model Personalization. CoRR abs/2204.03809 (2022) - [i27]Khalil Mrini, Shaoliang Nie, Jiatao Gu, Sinong Wang, Maziar Sanjabi, Hamed Firooz:
Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problem. CoRR abs/2204.05990 (2022) - [i26]Samuel Horváth
FedShuffle: Recipes for Better Use of Local Work in Federated Learning. CoRR abs/2204.13169 (2022) - [i25]Brihi Joshi, Aaron Chan, Ziyi Liu, Shaoliang Nie, Maziar Sanjabi, Hamed Firooz, Xiang Ren:
ER-TEST: Evaluating Explanation Regularization Methods for NLP Models. CoRR abs/2205.12542 (2022) - [i24]John Nguyen, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat:
Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning. CoRR abs/2206.15387 (2022) - [i23]Aaron Chan, Shaoliang Nie, Liang Tan, Xiaochang Peng, Hamed Firooz, Maziar Sanjabi, Xiang Ren:
FRAME: Evaluating Simulatability Metrics for Free-Text Rationales. CoRR abs/2207.00779 (2022) - [i22]John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael G. Rabbat:
Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. CoRR abs/2210.08090 (2022) - [i21]Chuan Guo, Alexandre Sablayrolles, Maziar Sanjabi:
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano. CoRR abs/2210.13662 (2022) - [i20]Nan Wang, Shaoliang Nie, Qifan Wang, Yi-Chia Wang, Maziar Sanjabi, Jingzhou Liu, Hamed Firooz, Hongning Wang:
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation. CoRR abs/2210.15500 (2022) - 2021
- [c16]Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn:
Alternating Direction Method of Multipliers for Quantization. AISTATS 2021: 208-216 - [c15]Woojeong Jin, Maziar Sanjabi, Shaoliang Nie, Liang Tan, Xiang Ren, Hamed Firooz:
MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding. EMNLP (Findings) 2021: 3557-3569 - [c14]Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith:
Tilted Empirical Risk Minimization. ICLR 2021 - [i19]Woojeong Jin, Maziar Sanjabi, Shaoliang Nie, Liang Tan, Xiang Ren, Hamed Firooz:
Modality-specific Distillation. CoRR abs/2101.01881 (2021) - [i18]Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith:
On Tilted Losses in Machine Learning: Theory and Applications. CoRR abs/2109.06141 (2021) - [i17]Aaron Chan, Maziar Sanjabi, Lambert Mathias, Liang Tan, Shaoliang Nie, Xiaochang Peng, Xiang Ren, Hamed Firooz:
UniREx: A Unified Learning Framework for Language Model Rationale Extraction. CoRR abs/2112.08802 (2021) - [i16]Ajinkya Tejankar, Maziar Sanjabi, Bichen Wu, Saining Xie, Madian Khabsa, Hamed Pirsiavash, Hamed Firooz:
A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision. CoRR abs/2112.13884 (2021) - 2020
- [j7]Meisam Razaviyayn
Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. IEEE Signal Process. Mag. 37(5): 55-66 (2020) - [c13]Jingwen Liang, Han Liu, Yiwei Zhao, Maziar Sanjabi, Mohsen Sardari, Harold Chaput, Navid Aghdaie, Kazi A. Zaman:
Building Placements In Urban Modeling Using Conditional Generative Latent Optimization. ICIP 2020: 3249-3253 - [c12]Tian Li, Maziar Sanjabi, Ahmad Beirami, Virginia Smith:
Fair Resource Allocation in Federated Learning. ICLR 2020 - [c11]Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith:
Federated Optimization in Heterogeneous Networks. MLSys 2020 - [i15]Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith:
FedDANE: A Federated Newton-Type Method. CoRR abs/2001.01920 (2020) - [i14]Meisam Razaviyayn, Tianjian Huang, Songtao Lu, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong:
Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. CoRR abs/2006.08141 (2020) - [i13]Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith:
Tilted Empirical Risk Minimization. CoRR abs/2007.01162 (2020) - [i12]Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn:
Alternating Direction Method of Multipliers for Quantization. CoRR abs/2009.03482 (2020)
2010 – 2019
- 2019
- [j6]Yiwei Zhao, Han Liu, Igor Borovikov, Ahmad Beirami, Maziar Sanjabi, Kazi A. Zaman:
Multi-theme generative adversarial terrain amplification. ACM Trans. Graph. 38(6): 200:1-200:14 (2019) - [c10]Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, Virginia Smith:
FedDANE: A Federated Newton-Type Method. ACSSC 2019: 1227-1231 - [c9]Babak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi:
Training Generative Networks Using Random Discriminators. DSW 2019: 327-332 - [c8]Maher Nouiehed, Maziar Sanjabi, Tianjian Huang, Jason D. Lee, Meisam Razaviyayn:
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods. NeurIPS 2019: 14905-14916 - [i11]Maher Nouiehed, Maziar Sanjabi, Tianjian Huang, Jason D. Lee, Meisam Razaviyayn:
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods. CoRR abs/1902.08297 (2019) - [i10]Babak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi:
Training generative networks using random discriminators. CoRR abs/1904.09775 (2019) - [i9]Tian Li, Maziar Sanjabi, Virginia Smith:
Fair Resource Allocation in Federated Learning. CoRR abs/1905.10497 (2019) - [i8]Maziar Sanjabi, Sina Baharlouei, Meisam Razaviyayn, Jason D. Lee:
When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima? CoRR abs/1911.09815 (2019) - 2018
- [c7]Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee:
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. NeurIPS 2018: 7091-7101 - [i7]Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee:
Solving Approximate Wasserstein GANs to Stationarity. CoRR abs/1802.08249 (2018) - [i6]Maziar Sanjabi, Meisam Razaviyayn, Jason D. Lee:
Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition. CoRR abs/1812.02878 (2018) - [i5]Anit Kumar Sahu, Tian Li, Maziar Sanjabi, Manzil Zaheer, Ameet Talwalkar, Virginia Smith:
On the Convergence of Federated Optimization in Heterogeneous Networks. CoRR abs/1812.06127 (2018) - 2017
- [c6]Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar:
Federated Multi-Task Learning. NIPS 2017: 4424-4434 - [i4]Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar:
Federated Multi-Task Learning. CoRR abs/1705.10467 (2017) - 2016
- [j5]Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo:
A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks. Math. Program. 157(2): 515-545 (2016) - 2015
- [c5]Mojtaba Kadkhodaie, Konstantina Christakopoulou, Maziar Sanjabi, Arindam Banerjee:
Accelerated Alternating Direction Method of Multipliers. KDD 2015: 497-506 - 2014
- [j4]Hadi Baligh, Mingyi Hong, Wei-Cheng Liao, Zhi-Quan Luo, Meisam Razaviyayn, Maziar Sanjabi, Ruoyu Sun:
Cross-Layer Provision of Future Cellular Networks: A WMMSE-based approach. IEEE Signal Process. Mag. 31(6): 56-68 (2014) - [j3]Maziar Sanjabi, Meisam Razaviyayn, Zhi-Quan Luo:
Optimal Joint Base Station Assignment and Beamforming for Heterogeneous Networks. IEEE Trans. Signal Process. 62(8): 1950-1961 (2014) - [c4]Maziar Sanjabi, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo:
Joint base station clustering and beamformer design for partial coordinated transmission using statistical channel state information. SPAWC 2014: 359-363 - [i3]Hadi Baligh, Mingyi Hong, Wei-Cheng Liao, Zhi-Quan Luo, Meisam Razaviyayn, Maziar Sanjabi, Ruoyu Sun:
Cross Layer Provision of Future Cellular Networks. CoRR abs/1407.1424 (2014) - 2013
- [c3]Meisam Razaviyayn, Maziar Sanjabi Boroujeni, Zhi-Quan Luo:
A stochastic weighted MMSE approach to sum rate maximization for a MIMO interference channel. SPAWC 2013: 325-329 - [i2]Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo:
A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks. CoRR abs/1307.4457 (2013) - 2012
- [j2]Enbin Song, Qingjiang Shi, Maziar Sanjabi, Ruoyu Sun, Zhi-Quan Luo:
Robust SINR-Constrained MISO Downlink Beamforming: When is Semidefinite Programming Relaxation Tight? EURASIP J. Wirel. Commun. Netw. 2012: 243 (2012) - [j1]Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo:
Linear Transceiver Design for Interference Alignment: Complexity and Computation. IEEE Trans. Inf. Theory 58(5): 2896-2910 (2012) - [c2]Maziar Sanjabi, Meisam Razaviyayn, Zhi-Quan Luo:
Optimal joint base station assignment and downlink beamforming for heterogeneous networks. ICASSP 2012: 2821-2824 - 2011
- [c1]Enbin Song, Qingjiang Shi, Maziar Sanjabi, Ruoyu Sun, Zhi-Quan Luo:
Robust SINR-constrained MISO downlink beamforming: When is semidefinite programming relaxation tight? ICASSP 2011: 3096-3099 - 2010
- [i1]Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo:
Linear Transceiver Design for Interference Alignment: Complexity and Computation. CoRR abs/1009.3481 (2010)
Coauthor Index
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last updated on 2024-11-15 19:32 CET by the dblp team
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