Meisam Razaviyayn

158 papers A* 17A 4B 2C 3Misc 9Journal 106Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Less is More: Convergence Benefits of Fewer Data Weight Updates over Longer Horizon. CoRR Rudrajit Das, Neel Patel, Meisam Razaviyayn, Vahab Mirrokni
2026	J	`jnl`	Memory Caching: RNNs with Growing Memory. CoRR Ali Behrouz, Zeman Li, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni
2025	J	`jnl`	ATLAS: Learning to Optimally Memorize the Context at Test Time. CoRR Ali Behrouz, Zeman Li, Praneeth Kacham, Majid Daliri, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni
2025	A*	`conf`	Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. ICLR Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni
2025	A*	`conf`	DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. ICLR Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni
2025	J	`jnl`	Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs. CoRR James Flemings, Haosheng Gan, Hongyi Li, Meisam Razaviyayn, Murali Annavaram
2025	—	`conf`	Efficient Algorithms for Estimating the Parameters of Mixed Linear Regression Models. MLSP Babak Barazandeh, Ali Ghafelebashi, Meisam Razaviyayn, Ram Sriharsha
2025	J	`jnl`	Four Axiomatic Characterizations of the Integrated Gradients Attribution Method. J. Mach. Learn. Res. Daniel Lundström, Meisam Razaviyayn
2025	J	`jnl`	Incentive Systems for Fleets of New Mobility Services. IEEE Trans. Intell. Transp. Syst. Ali Ghafelebashi, Meisam Razaviyayn, Maged M. Dessouky
2025	J	`jnl`	It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization. CoRR Ali Behrouz, Meisam Razaviyayn, Peilin Zhong, Vahab Mirrokni
2025	J	`jnl`	Memory-Efficient Differentially Private Training with Gradient Random Projection. CoRR Alex Mulrooney, Devansh Gupta, James Flemings, Huanyu Zhang, Murali Annavaram, Meisam Razaviyayn, Xinwei Zhang
2025	J	`jnl`	Nested Learning: The Illusion of Deep Learning Architectures. CoRR Ali Behrouz, Meisam Razaviyayn, Peilin Zhong, Vahab Mirrokni
2025	J	`jnl`	On the Inherent Privacy of Zeroth Order Projected Gradient Descent. CoRR Devansh Gupta, Meisam Razaviyayn, Vatsal Sharan
2025	A	`conf`	On the Inherent Privacy of Zeroth-Order Projected Gradient Descent. AISTATS Devansh Gupta, Meisam Razaviyayn, Vatsal Sharan
2025	J	`jnl`	PiKE: Adaptive Data Mixing for Multi-Task Learning Under Low Gradient Conflicts. CoRR Zeman Li, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni
2025	J	`jnl`	Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators. SIAM J. Control. Optim. Yinbin Han, Meisam Razaviyayn, Renyuan Xu
2025	J	`jnl`	Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter. J. Priv. Confidentiality Andrew Lowy, Meisam Razaviyayn
2025	J	`jnl`	Sampling and Loss Weights in Multi-Domain Training. CoRR Mahdi Salmani, Pratik Worah, Meisam Razaviyayn, Vahab Mirrokni
2025	A*	`conf`	Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence. ICML Yinbin Han, Meisam Razaviyayn, Renyuan Xu
2025	A*	`conf`	Synthetic Text Generation for Training Large Language Models via Gradient Matching. ICML Dang Nguyen, Zeman Li, MohammadHossein Bateni, Vahab Mirrokni, Meisam Razaviyayn, Baharan Mirzasoleiman
2025	J	`jnl`	Synthetic Text Generation for Training Large Language Models via Gradient Matching. CoRR Dang Nguyen, Zeman Li, MohammadHossein Bateni, Vahab Mirrokni, Meisam Razaviyayn, Baharan Mirzasoleiman
2025	J	`jnl`	TNT: Improving Chunkwise Training for Test-Time Memorization. CoRR Zeman Li, Ali Behrouz, Yuan Deng, Peilin Zhong, Praneeth Kacham, Mahdi Karami, Meisam Razaviyayn, Vahab Mirrokni
2025	J	`jnl`	Tradeoffs Between Convergence Rate and Noise Amplification for Momentum-Based Accelerated Optimization Algorithms. IEEE Trans. Autom. Control. Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2024	J	`jnl`	A Stochastic Optimization Framework for Private and Fair Learning From Decentralized Data. CoRR Devansh Gupta, A. S. Poornash, Andrew Lowy, Meisam Razaviyayn
2024	J	`jnl`	Adaptively Private Next-Token Prediction of Large Language Models. CoRR James Flemings, Meisam Razaviyayn, Murali Annavaram
2024	J	`jnl`	Addax: Utilizing Zeroth-Order Gradients to Improve Memory Efficiency and Performance of SGD for Fine-Tuning Language Models. CoRR Zeman Li, Xinwei Zhang, Peilin Zhong, Yuan Deng, Meisam Razaviyayn, Vahab Mirrokni
2024	A*	`conf`	DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction. NeurIPS Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn
2024	J	`jnl`	DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction. CoRR Xinwei Zhang, Zhiqi Bu, Mingyi Hong, Meisam Razaviyayn
2024	J	`jnl`	DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction. CoRR Xinwei Zhang, Zhiqi Bu, Borja Balle, Mingyi Hong, Meisam Razaviyayn, Vahab Mirrokni
2024	—	`conf`	Differentially Private Next-Token Prediction of Large Language Models. NAACL-HLT James Flemings, Meisam Razaviyayn, Murali Annavaram
2024	J	`jnl`	Differentially Private Next-Token Prediction of Large Language Models. CoRR James Flemings, Meisam Razaviyayn, Murali Annavaram
2024	A*	`conf`	Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization. ICLR Yinbin Han, Meisam Razaviyayn, Renyuan Xu
2024	J	`jnl`	Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization. CoRR Yinbin Han, Meisam Razaviyayn, Renyuan Xu
2024	A*	`conf`	Optimal Differentially Private Model Training with Public Data. ICML Andrew Lowy, Zeman Li, Tianjian Huang, Meisam Razaviyayn
2024	J	`jnl`	Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence. CoRR Yinbin Han, Meisam Razaviyayn, Renyuan Xu
2024	A*	`conf`	f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization. ICLR Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
2023	A*	`conf`	A Unifying Framework to the Analysis of Interaction Methods using Synergy Functions. ICML Daniel Lundström, Meisam Razaviyayn
2023	J	`jnl`	Distributing Synergy Functions: Unifying Game-Theoretic Interaction Methods for Machine-Learning Explainability. CoRR Daniel Lundström, Meisam Razaviyayn
2023	J	`jnl`	Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Framework. CoRR Sina Baharlouei, Meisam Razaviyayn
2023	J	`jnl`	Four Axiomatic Characterizations of the Integrated Gradients Attribution Method. CoRR Daniel Lundström, Meisam Razaviyayn
2023	A	`conf`	Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes. AISTATS Sina Baharlouei, Fatemeh Sheikholeslami, Meisam Razaviyayn, Zico Kolter
2023	J	`jnl`	Incentive Systems for Fleets of New Mobility Services. CoRR Ali Ghafelebashi, Meisam Razaviyayn, Maged M. Dessouky
2023	C	`conf`	Noise amplifiation of momentum-based optimization algorithms. ACC Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2023	J	`jnl`	Optimal Differentially Private Learning with Public Data. CoRR Andrew Lowy, Zeman Li, Tianjian Huang, Meisam Razaviyayn
2023	J	`jnl`	Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators. CoRR Yinbin Han, Meisam Razaviyayn, Renyuan Xu
2023	A*	`conf`	Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses. ICLR Andrew Lowy, Meisam Razaviyayn
2023	A	`conf`	Private Non-Convex Federated Learning Without a Trusted Server. AISTATS Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn
2023	B	`conf`	Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses. ALT Andrew Lowy, Meisam Razaviyayn
2023	J	`jnl`	RIFLE: Imputation and Robust Inference from Low Order Marginals. Trans. Mach. Learn. Res. Sina Baharlouei, Sze-Chuan Suen, Meisam Razaviyayn
2023	J	`jnl`	Robustness through Data Augmentation Loss Consistency. Trans. Mach. Learn. Res. Tianjian Huang, Shaunak Ashish Halbe, Chinnadhurai Sankar, Pooyan Amini, Satwik Kottur, Alborz Geramifard, Meisam Razaviyayn, Ahmad Beirami
2023	A*	`conf`	Stochastic Differentially Private and Fair Learning. ICLR Andrew Lowy, Devansh Gupta, Meisam Razaviyayn
2023	J	`jnl`	Zeroth-order algorithms for nonconvex-strongly-concave minimax problems with improved complexities. J. Glob. Optim. Zhongruo Wang, Krishnakumar Balasubramanian, Shiqian Ma, Meisam Razaviyayn
2023	J	`jnl`	f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization. CoRR Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
2022	A*	`conf`	A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions. ICML Daniel Lundström, Tianjian Huang, Meisam Razaviyayn
2022	J	`jnl`	A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions. CoRR Daniel Lundström, Tianjian Huang, Meisam Razaviyayn
2022	J	`jnl`	A Stochastic Optimization Framework for Fair Risk Minimization. Trans. Mach. Learn. Res. Andrew Lowy, Sina Baharlouei, Rakesh Pavan, Meisam Razaviyayn, Ahmad Beirami
2022	J	`jnl`	CRAM-Seq: Accelerating RNA-Seq Abundance Quantification Using Computational RAM. IEEE Trans. Emerg. Top. Comput. Zamshed I. Chowdhury, S. Karen Khatamifard, Salonik Resch, M. Hüsrev Cilasun, Zhengyang Zhao, Masoud Zabihi, Meisam Razaviyayn, Jian-Ping Wang, Sachin S. Sapatnekar, Ulya R. Karpuzcu
2022	J	`jnl`	GeNVoM: Read Mapping Near Non-Volatile Memory. IEEE ACM Trans. Comput. Biol. Bioinform. S. Karen Khatamifard, Zamshed I. Chowdhury, Nakul Pande, Meisam Razaviyayn, Chris H. Kim, Ulya R. Karpuzcu
2022	—	`conf`	I-CONVEX: Fast and Accurate de Novo Transcriptome Recovery from Long Reads. PKDD/ECML Workshops (2) Sina Baharlouei, Meisam Razaviyayn, Elizabeth Tseng, David Tse
2022	J	`jnl`	Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes. CoRR Sina Baharlouei, Fatemeh Sheikholeslami, Meisam Razaviyayn, Zico Kolter
2022	J	`jnl`	Learning Deep Models: Critical Points and Local Openness. INFORMS J. Optim. Maher Nouiehed, Meisam Razaviyayn
2022	J	`jnl`	Private Non-Convex Federated Learning Without a Trusted Server. CoRR Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn
2022	J	`jnl`	Private Stochastic Optimization in the Presence of Outliers: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses. CoRR Andrew Lowy, Meisam Razaviyayn
2022	—	`conf`	Stochastic Differentially Private and Fair Learning. AFCP Andrew Lowy, Devansh Gupta, Meisam Razaviyayn
2022	J	`jnl`	Stochastic Differentially Private and Fair Learning. CoRR Andrew Lowy, Devansh Gupta, Meisam Razaviyayn
2022	J	`jnl`	Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms. CoRR Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2021	A	`conf`	Alternating Direction Method of Multipliers for Quantization. AISTATS Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn
2021	J	`jnl`	DAIR: Data Augmented Invariant Regularization. CoRR Tianjian Huang, Shaunak Ashish Halbe, Chinnadhurai Sankar, Pooyan Amini, Satwik Kottur, Alborz Geramifard, Meisam Razaviyayn, Ahmad Beirami
2021	J	`jnl`	Efficient Algorithms for Estimating the Parameters of Mixed Linear Regression Models. CoRR Babak Barazandeh, Ali Ghafelebashi, Meisam Razaviyayn, Ram Sriharsha
2021	J	`jnl`	Efficient Search of First-Order Nash Equilibria in Nonconvex-Concave Smooth Min-Max Problems. SIAM J. Optim. Dmitrii M. Ostrovskii, Andrew Lowy, Meisam Razaviyayn
2021	J	`jnl`	FERMI: Fair Empirical Risk Minimization via Exponential Rényi Mutual Information. CoRR Andrew Lowy, Rakesh Pavan, Sina Baharlouei, Meisam Razaviyayn, Ahmad Beirami
2021	J	`jnl`	Linearized ADMM Converges to Second-Order Stationary Points for Non-Convex Problems. IEEE Trans. Signal Process. Songtao Lu, Jason D. Lee, Meisam Razaviyayn, Mingyi Hong
2021	J	`jnl`	Locally Differentially Private Federated Learning: Efficient Algorithms with Tight Risk Bounds. CoRR Andrew Lowy, Meisam Razaviyayn
2021	J	`jnl`	Nonconvex-Nonconcave Min-Max Optimization with a Small Maximization Domain. CoRR Dmitrii M. Ostrovskii, Babak Barazandeh, Meisam Razaviyayn
2021	J	`jnl`	Output Perturbation for Differentially Private Convex Optimization with Improved Population Loss Bounds, Runtimes and Applications to Private Adversarial Training. CoRR Andrew Lowy, Meisam Razaviyayn
2021	J	`jnl`	RIFLE: Robust Inference from Low Order Marginals. CoRR Sina Baharlouei, Kelechi Ogudu, Sze-Chuan Suen, Meisam Razaviyayn
2021	J	`jnl`	Robustness of Accelerated First-Order Algorithms for Strongly Convex Optimization Problems. IEEE Trans. Autom. Control. Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2020	J	`jnl`	A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization. Math. Oper. Res. Mingyi Hong, Tsung-Hui Chang, Xiangfeng Wang, Meisam Razaviyayn, Shiqian Ma, Zhi-Quan Luo
2020	J	`jnl`	A Trust Region Method for Finding Second-Order Stationarity in Linearly Constrained Nonconvex Optimization. SIAM J. Optim. Maher Nouiehed, Meisam Razaviyayn
2020	J	`jnl`	Alternating Direction Method of Multipliers for Quantization. CoRR Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn
2020	A*	`conf`	Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems. NeurIPS Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong
2020	J	`jnl`	Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. CoRR Meisam Razaviyayn, Tianjian Huang, Songtao Lu, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong
2020	J	`jnl`	Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. IEEE Signal Process. Mag. Meisam Razaviyayn, Tianjian Huang, Songtao Lu, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong
2020	A*	`conf`	Rényi Fair Inference. ICLR Sina Baharlouei, Maher Nouiehed, Ahmad Beirami, Meisam Razaviyayn
2020	Misc	`conf`	Solving Non-Convex Non-Differentiable Min-Max Games Using Proximal Gradient Method. ICASSP Babak Barazandeh, Meisam Razaviyayn
2020	J	`jnl`	Solving Non-Convex Non-Differentiable Min-Max Games using Proximal Gradient Method. CoRR Babak Barazandeh, Meisam Razaviyayn
2020	J	`jnl`	Zeroth-Order Algorithms for Nonconvex Minimax Problems with Improved Complexities. CoRR Zhongruo Wang, Krishnakumar Balasubramanian, Shiqian Ma, Meisam Razaviyayn
2019	J	`jnl`	A linearly convergent doubly stochastic Gauss-Seidel algorithm for solving linear equations and a certain class of over-parameterized optimization problems. Math. Program. Meisam Razaviyayn, Mingyi Hong, Navid Reyhanian, Zhi-Quan Luo
2019	J	`jnl`	Correction to: On the pervasiveness of difference-convexity in optimization and statistics. Math. Program. Maher Nouiehed, Jong-Shi Pang, Meisam Razaviyayn
2019	J	`jnl`	On the pervasiveness of difference-convexity in optimization and statistics. Math. Program. Maher Nouiehed, Jong-Shi Pang, Meisam Razaviyayn
2019	C	`conf`	Performance of noisy Nesterov's accelerated method for strongly convex optimization problems. ACC Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2019	J	`jnl`	Robustness of accelerated first-order algorithms for strongly convex optimization problems. CoRR Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2019	J	`jnl`	Rényi Fair Inference. CoRR Sina Baharlouei, Maher Nouiehed, Meisam Razaviyayn
2019	J	`jnl`	SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems. CoRR Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong
2019	A*	`conf`	Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods. NeurIPS Maher Nouiehed, Maziar Sanjabi, Tianjian Huang, Jason D. Lee, Meisam Razaviyayn
2019	J	`jnl`	Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods. CoRR Maher Nouiehed, Maziar Sanjabi, Tianjian Huang, Jason D. Lee, Meisam Razaviyayn
2019	—	`conf`	Training Generative Networks Using Random Discriminators. DSW Babak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi
2019	J	`jnl`	Training generative networks using random discriminators. CoRR Babak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi
2019	J	`jnl`	When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima? CoRR Maziar Sanjabi, Sina Baharlouei, Meisam Razaviyayn, Jason D. Lee
2018	J	`jnl`	A New Sequential Optimization Procedure and Its Applications to Resource Allocation for Wireless Systems. IEEE Trans. Signal Process. Augusto Aubry, Antonio De Maio, Alessio Zappone, Meisam Razaviyayn, Zhi-Quan Luo
2018	J	`jnl`	Computational RAM to Accelerate String Matching at Scale. CoRR Zamshed I. Chowdhury, S. Karen Khatamifard, Zhengyang Zhao, Masoud Zabihi, Salonik Resch, Meisam Razaviyayn, Jianping Wang, Sachin S. Sapatnekar, Ulya R. Karpuzcu
2018	A*	`conf`	Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks. ICML Mingyi Hong, Meisam Razaviyayn, Jason D. Lee
2018	J	`jnl`	Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solutions for Nonconvex Distributed Optimization. CoRR Mingyi Hong, Jason D. Lee, Meisam Razaviyayn
2018	—	`conf`	Learning Deep Models: Critical Points and Local Openness. ICLR (Workshop) Maher Nouiehed, Meisam Razaviyayn
2018	—	`conf`	On the Behavior of the Expectation-Maximization Algorithm for Mixture Models. GlobalSIP Babak Barazandeh, Meisam Razaviyayn
2018	J	`jnl`	On the Behavior of the Expectation-Maximization Algorithm for Mixture Models. CoRR Babak Barazandeh, Meisam Razaviyayn
2018	A*	`conf`	On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. NeurIPS Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
2018	C	`conf`	On the stability of gradient flow dynamics for a rank-one matrix approximation problem. ACC Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2018	J	`jnl`	Solving Approximate Wasserstein GANs to Stationarity. CoRR Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
2018	J	`jnl`	Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition. CoRR Maziar Sanjabi, Meisam Razaviyayn, Jason D. Lee
2018	—	`conf`	Variance Amplification of Accelerated First-Order Algorithms for Strongly Convex Quadratic Optimization Problems. CDC Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
2017	J	`jnl`	A Non-volatile Near-Memory Read Mapping Accelerator. CoRR S. Karen Khatamifard, Zamshed I. Chowdhury, Nakul Pande, Meisam Razaviyayn, Chris H. Kim, Ulya R. Karpuzcu
2017	J	`jnl`	Computing B-Stationary Points of Nonsmooth DC Programs. Math. Oper. Res. Jong-Shi Pang, Meisam Razaviyayn, Alberth Alvarado
2017	J	`jnl`	Iteration complexity analysis of block coordinate descent methods. Math. Program. Mingyi Hong, Xiangfeng Wang, Meisam Razaviyayn, Zhi-Quan Luo
2017	—	`conf`	On Optimal Generalizability in Parametric Learning. NIPS Ahmad Beirami, Meisam Razaviyayn, Shahin Shahrampour, Vahid Tarokh
2017	J	`jnl`	On Optimal Generalizability in Parametric Learning. CoRR Ahmad Beirami, Meisam Razaviyayn, Shahin Shahrampour, Vahid Tarokh
2016	J	`jnl`	A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks. Math. Program. Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo
2016	J	`jnl`	A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing. IEEE Signal Process. Mag. Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo, Jong-Shi Pang
2016	—	`ch.`	A unified distributed algorithm for non-cooperative games. Big Data over Networks Jong-Shi Pang, Meisam Razaviyayn
2016	J	`jnl`	Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems. SIAM J. Optim. Mingyi Hong, Zhi-Quan Luo, Meisam Razaviyayn
2016	J	`jnl`	Inexact Block Coordinate Descent Methods For Symmetric Nonnegative Matrix Factorization. CoRR Qingjiang Shi, Haoran Sun, Songtao Lu, Mingyi Hong, Meisam Razaviyayn
2016	J	`jnl`	SINR Constrained Beamforming for a MIMO Multi-User Downlink System: Algorithms and Convergence Analysis. IEEE Trans. Signal Process. Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
2015	J	`jnl`	Computational Intractability of Dictionary Learning for Sparse Representation. CoRR Meisam Razaviyayn, Hung-Wei Tseng, Zhi-Quan Luo
2015	Misc	`conf`	Convergence analysis of alternating direction method of multipliers for a family of nonconvex problems. ICASSP Mingyi Hong, Zhi-Quan Luo, Meisam Razaviyayn
2015	—	`conf`	Discrete Rényi Classifiers. NIPS Meisam Razaviyayn, Farzan Farnia, David Tse
2015	J	`jnl`	Discrete Rényi Classifiers. CoRR Meisam Razaviyayn, Farzan Farnia, David N. C. Tse
2015	J	`jnl`	Minimum HGR Correlation Principle: From Marginals to Joint Distribution. CoRR Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse
2015	B	`conf`	Minimum HGR correlation principle: From marginals to joint distribution. ISIT Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse
2015	J	`jnl`	SINR Constrained Beamforming for a MIMO Multi-user Downlink System. CoRR Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
2014	Misc	`conf`	A block coordinate descent method of multipliers: Convergence analysis and applications. ICASSP Mingyi Hong, Tsung-Hui Chang, Xiangfeng Wang, Meisam Razaviyayn, Shiqian Ma, Zhi-Quan Luo
2014	J	`jnl`	Cross Layer Provision of Future Cellular Networks. CoRR Hadi Baligh, Mingyi Hong, Wei-Cheng Liao, Zhi-Quan Luo, Meisam Razaviyayn, Maziar Sanjabi, Ruoyu Sun
2014	J	`jnl`	Cross-Layer Provision of Future Cellular Networks: A WMMSE-based approach. IEEE Signal Process. Mag. Hadi Baligh, Mingyi Hong, Wei-Cheng Liao, Zhi-Quan Luo, Meisam Razaviyayn, Maziar Sanjabi, Ruoyu Sun
2014	Misc	`conf`	Dictionary learning for sparse representation: Complexity and algorithms. ICASSP Meisam Razaviyayn, Hung-Wei Tseng, Zhi-Quan Luo
2014	J	`jnl`	Joint User Grouping and Transceiver Design in a MIMO Interfering Broadcast Channel. IEEE Trans. Signal Process. Meisam Razaviyayn, Mohammad Hadi Baligh, Aaron Callard, Zhi-Quan Luo
2014	—	`conf`	Joint base station clustering and beamformer design for partial coordinated transmission using statistical channel state information. SPAWC Maziar Sanjabi, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo
2014	Misc	`conf`	Joint day-ahead power procurement and load scheduling using stochastic alternating direction method of multipliers. ICASSP Xiangfeng Wang, Mingyi Hong, Tsung-Hui Chang, Meisam Razaviyayn, Zhi-Quan Luo
2014	J	`jnl`	Optimal Joint Base Station Assignment and Beamforming for Heterogeneous Networks. IEEE Trans. Signal Process. Maziar Sanjabi, Meisam Razaviyayn, Zhi-Quan Luo
2014	—	`conf`	Parallel Successive Convex Approximation for Nonsmooth Nonconvex Optimization. NIPS Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo, Jong-Shi Pang
2013	J	`jnl`	A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks. CoRR Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo
2013	J	`jnl`	A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization. SIAM J. Optim. Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
2013	—	`conf`	A stochastic weighted MMSE approach to sum rate maximization for a MIMO interference channel. SPAWC Meisam Razaviyayn, Maziar Sanjabi Boroujeni, Zhi-Quan Luo
2013	J	`jnl`	Joint User Grouping and Linear Virtual Beamforming: Complexity, Algorithms and Approximation Bounds. IEEE J. Sel. Areas Commun. Mingyi Hong, Zi Xu, Meisam Razaviyayn, Zhi-Quan Luo
2013	J	`jnl`	Linear transceiver design for a MIMO interfering broadcast channel achieving max-min fairness. Signal Process. Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
2012	J	`jnl`	Joint User Grouping and Linear Virtual Beamforming: Complexity, Algorithms and Approximation Bounds CoRR Mingyi Hong, Zi Xu, Meisam Razaviyayn, Zhi-Quan Luo
2012	—	`conf`	Joint transceiver design and base station clustering for heterogeneous networks. ACSCC Mingyi Hong, Meisam Razaviyayn, Ruoyu Sun, Zhi-Quan Luo
2012	J	`jnl`	Linear Transceiver Design for Interference Alignment: Complexity and Computation. IEEE Trans. Inf. Theory Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo
2012	J	`jnl`	Linear Transceiver Design for a MIMO Interfering Broadcast Channel Achieving Max-Min Fairness CoRR Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
2012	J	`jnl`	On the Degrees of Freedom Achievable Through Interference Alignment in a MIMO Interference Channel. IEEE Trans. Signal Process. Meisam Razaviyayn, Gennady Lyubeznik, Zhi-Quan Luo
2012	Misc	`conf`	Optimal joint base station assignment and downlink beamforming for heterogeneous networks. ICASSP Maziar Sanjabi, Meisam Razaviyayn, Zhi-Quan Luo
2012	—	`conf`	SINR constrained beamforming for a MIMO multi-user downlink system. ACSCC Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
2011	J	`jnl`	A stackelberg game approach to distributed spectrum management. Math. Program. Meisam Razaviyayn, Zhi-Quan Luo, Paul Tseng, Jong-Shi Pang
2011	J	`jnl`	An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel. IEEE Trans. Signal Process. Qingjiang Shi, Meisam Razaviyayn, Zhi-Quan Luo, Chen He
2011	Misc	`conf`	An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel. ICASSP Qingjiang Shi, Meisam Razaviyayn, Zhi-Quan Luo, Chen He
2011	Misc	`conf`	Joint transceiver design and user grouping in a MIMO interfering broadcast channel. CISS Meisam Razaviyayn, Hadi Baligh, Aaron Callard, Zhi-Quan Luo
2011	—	`conf`	Linear transceiver design for a MIMO interfering broadcast channel achieving max-min fairness. ACSCC Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
2011	J	`jnl`	On the Degrees of Freedom Achievable Through Interference Alignment in a MIMO Interference Channel CoRR Meisam Razaviyayn, Gennady Lyubeznik, Zhi-Quan Luo
2010	Misc	`conf`	A Stackelberg game approach to distributed spectrum management. ICASSP Meisam Razaviyayn, Yao Morin, Zhi-Quan Luo
2010	J	`jnl`	Linear Transceiver Design for Interference Alignment: Complexity and Computation CoRR Meisam Razaviyayn, Maziar Sanjabi, Zhi-Quan Luo