Optimal joint base station assignment and downlink beamforming for heterogeneous networks. - Maziar Sanjabi; Meisam Razaviyayn; Zhi-Quan Luo (ICASSP, 2012)

Robust SINR-Constrained MISO Downlink Beamforming: When is Semidefinite Programming Relaxation Tight? - Enbin Song; Qingjiang Shi; Maziar Sanjabi; Ruoyu Sun 001; Zhi-Quan Luo (EURASIP J. Wirel. Commun. Netw., 2012)

Linear Transceiver Design for Interference Alignment: Complexity and Computation. - Meisam Razaviyayn; Maziar Sanjabi; Zhi-Quan Luo (IEEE Trans. Inf. Theory, 2012)

A stochastic weighted MMSE approach to sum rate maximization for a MIMO interference channel. - Meisam Razaviyayn; Maziar Sanjabi Boroujeni; Zhi-Quan Luo (SPAWC, 2013)

Joint base station clustering and beamformer design for partial coordinated transmission using statistical channel state information. - Maziar Sanjabi; Mingyi Hong 001; Meisam Razaviyayn; Zhi-Quan Luo (SPAWC, 2014)

Cross Layer Provision of Future Cellular Networks. - Hadi Baligh; Mingyi Hong 001; Wei-Cheng Liao; Zhi-Quan Luo; Meisam Razaviyayn; Maziar Sanjabi; Ruoyu Sun 001 (CoRR, 2014)

Cross-Layer Provision of Future Cellular Networks: A WMMSE-based approach. - Hadi Baligh; Mingyi Hong 001; Wei-Cheng Liao; Zhi-Quan Luo; Meisam Razaviyayn; Maziar Sanjabi; Ruoyu Sun 001 (IEEE Signal Process. Mag., 2014)

Optimal Joint Base Station Assignment and Beamforming for Heterogeneous Networks. - Maziar Sanjabi; Meisam Razaviyayn; Zhi-Quan Luo (IEEE Trans. Signal Process., 2014)

Accelerated Alternating Direction Method of Multipliers. - Mojtaba Kadkhodaie; Konstantina Christakopoulou; Maziar Sanjabi; Arindam Banerjee 001 (KDD, 2015)

A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks. - Meisam Razaviyayn; Maziar Sanjabi; Zhi-Quan Luo (Math. Program., 2016)

Federated Multi-Task Learning. - Virginia Smith; Chao-Kai Chiang; Maziar Sanjabi; Ameet Talwalkar (NIPS, 2017)

On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. - Maziar Sanjabi; Jimmy Ba; Meisam Razaviyayn; Jason D. Lee (NeurIPS, 2018)

Solving Approximate Wasserstein GANs to Stationarity. - Maziar Sanjabi; Jimmy Ba; Meisam Razaviyayn; Jason D. Lee (CoRR, 2018)

Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition. - Maziar Sanjabi; Meisam Razaviyayn; Jason D. Lee (CoRR, 2018)

On the Convergence of Federated Optimization in Heterogeneous Networks. - Anit Kumar Sahu; Tian Li 005; Maziar Sanjabi; Manzil Zaheer; Ameet Talwalkar; Virginia Smith (CoRR, 2018)

FedDANE: A Federated Newton-Type Method. - Tian Li 005; Anit Kumar Sahu; Manzil Zaheer; Maziar Sanjabi; Ameet Talwalkar; Virginia Smith (ACSSC, 2019)

Training Generative Networks Using Random Discriminators. - Babak Barazandeh; Meisam Razaviyayn; Maziar Sanjabi (DSW, 2019)

Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods. - Maher Nouiehed; Maziar Sanjabi; Tianjian Huang; Jason D. Lee; Meisam Razaviyayn (NeurIPS, 2019)

Fair Resource Allocation in Federated Learning. - Tian Li 005; Maziar Sanjabi; Virginia Smith (CoRR, 2019)

When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima? - Maziar Sanjabi; Sina Baharlouei; Meisam Razaviyayn; Jason D. Lee (CoRR, 2019)

Multi-theme generative adversarial terrain amplification. - Yiwei Zhao; Han Liu; Igor Borovikov; Ahmad Beirami; Maziar Sanjabi; Kazi A. Zaman (ACM Trans. Graph., 2019)

Building Placements In Urban Modeling Using Conditional Generative Latent Optimization. - Jingwen Liang; Han Liu; Yiwei Zhao; Maziar Sanjabi; Mohsen Sardari; Harold Chaput; Navid Aghdaie; Kazi A. Zaman (ICIP, 2020)

Fair Resource Allocation in Federated Learning. - Tian Li 005; Maziar Sanjabi; Ahmad Beirami; Virginia Smith (ICLR, 2020)

Federated Optimization in Heterogeneous Networks. - Tian Li 005; Anit Kumar Sahu; Manzil Zaheer; Maziar Sanjabi; Ameet Talwalkar; Virginia Smith (MLSys, 2020)

Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. - Meisam Razaviyayn; Tianjian Huang; Songtao Lu; Maher Nouiehed; Maziar Sanjabi; Mingyi Hong 001 (CoRR, 2020)

Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. - Meisam Razaviyayn; Tianjian Huang; Songtao Lu; Maher Nouiehed; Maziar Sanjabi; Mingyi Hong 001 (IEEE Signal Process. Mag., 2020)

Alternating Direction Method of Multipliers for Quantization. - Tianjian Huang; Prajwal Singhania; Maziar Sanjabi; Pabitra Mitra; Meisam Razaviyayn (AISTATS, 2021)

MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding. - Woojeong Jin 001; Maziar Sanjabi; Shaoliang Nie; Liang Tan 005; Xiang Ren 001; Hamed Firooz (EMNLP (Findings), 2021)

Tilted Empirical Risk Minimization. - Tian Li 005; Ahmad Beirami; Maziar Sanjabi; Virginia Smith (ICLR, 2021)

Modality-specific Distillation. - Woojeong Jin 001; Maziar Sanjabi; Shaoliang Nie; Liang Tan 005; Xiang Ren 001; Hamed Firooz (CoRR, 2021)

A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision. - Ajinkya Tejankar; Maziar Sanjabi; Bichen Wu; Saining Xie; Madian Khabsa; Hamed Pirsiavash; Hamed Firooz (CoRR, 2021)

Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problem. - Khalil Mrini; Shaoliang Nie; Jiatao Gu; Sinong Wang; Maziar Sanjabi; Hamed Firooz (ACL (Findings), 2022)

ER-Test: Evaluating Explanation Regularization Methods for Language Models. - Brihi Joshi; Aaron Chan; Ziyi Liu 007; Shaoliang Nie; Maziar Sanjabi; Hamed Firooz; Xiang Ren 001 (EMNLP (Findings), 2022)

UNIREX: A Unified Learning Framework for Language Model Rationale Extraction. - Aaron Chan; Maziar Sanjabi; Lambert Mathias; Liang Tan 005; Shaoliang Nie; Xiaochang Peng; Xiang Ren 001; Hamed Firooz (ICML, 2022)

Federated Learning with Partial Model Personalization. - Krishna Pillutla; Kshitiz Malik; Abdelrahman Mohamed; Michael G. Rabbat; Maziar Sanjabi; Lin Xiao 003 (ICML, 2022)

BARACK: Partially Supervised Group Robustness With Guarantees. - Nimit Sharad Sohoni; Maziar Sanjabi; Nicolas Ballas; Aditya Grover; Shaoliang Nie; Hamed Firooz; Christopher Ré (CoRR, 2022)

Understanding Failure Modes of Self-Supervised Learning. - Neha Mukund Kalibhat; Kanika Narang; Liang Tan 005; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (CoRR, 2022)

ER-TEST: Evaluating Explanation Regularization Methods for NLP Models. - Brihi Joshi; Aaron Chan; Ziyi Liu 007; Shaoliang Nie; Maziar Sanjabi; Hamed Firooz; Xiang Ren 001 (CoRR, 2022)

Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning. - John Nguyen; Kshitiz Malik; Maziar Sanjabi; Michael G. Rabbat (CoRR, 2022)

FRAME: Evaluating Simulatability Metrics for Free-Text Rationales. - Aaron Chan; Shaoliang Nie; Liang Tan 005; Xiaochang Peng; Hamed Firooz; Maziar Sanjabi; Xiang Ren 001 (CoRR, 2022)

FedShuffle: Recipes for Better Use of Local Work in Federated Learning. - Samuel Horváth; Maziar Sanjabi; Lin Xiao 003; Peter Richtárik; Michael G. Rabbat (Trans. Mach. Learn. Res., 2022)

Text2Concept: Concept Activation Vectors Directly from Text. - Mazda Moayeri; Keivan Rezaei; Maziar Sanjabi; Soheil Feizi (CVPR Workshops, 2023)

Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning. - Ajinkya Tejankar; Maziar Sanjabi; Qifan Wang 001; Sinong Wang; Hamed Firooz; Hamed Pirsiavash; Liang Tan 005 (CVPR, 2023)

COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation. - Nan Wang; Qifan Wang 001; Yi-Chia Wang; Maziar Sanjabi; Jingzhou Liu; Hamed Firooz; Hongning Wang; Shaoliang Nie (EMNLP, 2023)

Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning. - John Nguyen; Jianyu Wang; Kshitiz Malik; Maziar Sanjabi; Michael G. Rabbat (ICLR, 2023)

Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano. - Chuan Guo 001; Alexandre Sablayrolles; Maziar Sanjabi (ICML, 2023)

Identifying Interpretable Subspaces in Image Representations. - Neha Mukund Kalibhat; Shweta Bhardwaj; C. Bayan Bruss; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (ICML, 2023)

Text-To-Concept (and Back) via Cross-Model Alignment. - Mazda Moayeri; Keivan Rezaei; Maziar Sanjabi; Soheil Feizi (ICML, 2023)

Augmenting CLIP with Improved Visio-Linguistic Reasoning. - Samyadeep Basu; Maziar Sanjabi; Daniela Massiceti; Shell Xu Hu; Soheil Feizi (CoRR, 2023)

EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods. - Samyadeep Basu; Mehrdad Saberi; Shweta Bhardwaj; Atoosa Malemir Chegini; Daniela Massiceti; Maziar Sanjabi; Shell Xu Hu; Soheil Feizi (CoRR, 2023)

On Tilted Losses in Machine Learning: Theory and Applications. - Tian Li 005; Ahmad Beirami; Maziar Sanjabi; Virginia Smith (J. Mach. Learn. Res., 2023)

Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features. - Neha Mukund Kalibhat; Kanika Narang; Hamed Firooz; Maziar Sanjabi; Soheil Feizi (AAAI, 2024)

Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression. - 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; et al. (ECCV (70), 2024)

Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP. - Samyadeep Basu; Shell Xu Hu; Maziar Sanjabi; Daniela Massiceti; Soheil Feizi (EMNLP, 2024)

Differentially Private Representation Learning via Image Captioning. - Tom Sander; Yaodong Yu; Maziar Sanjabi; Alain Oliviero Durmus; Yi Ma 001; Kamalika Chaudhuri; Chuan Guo 001 (ICML, 2024)

ViP: A Differentially Private Foundation Model for Computer Vision. - Yaodong Yu; Maziar Sanjabi; Yi Ma 001; Kamalika Chaudhuri; Chuan Guo 001 (ICML, 2024)

RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models. - Song Jiang 002; Zahra Shakeri; Aaron Chan; Maziar Sanjabi; Hamed Firooz; Yinglong Xia; Bugra Akyildiz; Yizhou Sun; Jinchao Li; Qifan Wang 001; Asli Celikyilmaz (NAACL-HLT, 2024)

DP-RDM: Adapting Diffusion Models to Private Domains Without Fine-Tuning. - Jonathan Lebensold; Maziar Sanjabi; Pietro Astolfi; Adriana Romero-Soriano; Kamalika Chaudhuri; Mike Rabbat; Chuan Guo 001 (CoRR, 2024)

Lost-in-Distance: Impact of Contextual Proximity on LLM Performance in Graph Tasks. - Hamed Firooz; Maziar Sanjabi; Wenlong Jiang; Xiaoling Zhai (CoRR, 2024)

CoT-ICL Lab: A Synthetic Framework for Studying Chain-of-Thought Learning from In-Context Demonstrations. - Vignesh Kothapalli; Hamed Firooz; Maziar Sanjabi (ACL (1), 2025)

360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation. - Hamed Firooz; Maziar Sanjabi; Adrian Englhardt; Aman Gupta; Ben Levine; Dre Olgiati; Gungor Polatkan; Iuliia Melnychuk; Karthik Ramgopal; Kirill Talanine; Kutta Srinivasan; Luke Simon; et al. (CoRR, 2025)

Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications. - Kayhan Behdin; Yun Dai; Ata Fatahi Baarzi; Aman Gupta; Qingquan Song; Shao Tang; Hejian Sang; Gregory Dexter; Sirou Zhu; Siyu Zhu; Tejas Dharamsi; Maziar Sanjabi; et al. (CoRR, 2025)

CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context Demonstrations. - Vignesh Kothapalli; Hamed Firooz; Maziar Sanjabi (CoRR, 2025)