Meisam Razaviyayn

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 90

Top Venues

Publications

Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization. CoRR (2024)
James Flemings, Meisam Razaviyayn, Murali Annavaram
Differentially Private Next-Token Prediction of Large Language Models. CoRR (2024)
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization. ICLR (2024)
Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization. ICLR (2024)
James Flemings, Meisam Razaviyayn, Murali Annavaram
Differentially Private Next-Token Prediction of Large Language Models. NAACL-HLT (2024)
Sina Baharlouei, Shivam Patel, Meisam Razaviyayn
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization. CoRR (2023)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Noise amplifiation of momentum-based optimization algorithms. ACC (2023)
Sina Baharlouei, Sze-Chuan Suen, Meisam Razaviyayn
RIFLE: Imputation and Robust Inference from Low Order Marginals. Trans. Mach. Learn. Res. 2023 (2023)
Andrew Lowy, Devansh Gupta, Meisam Razaviyayn
Stochastic Differentially Private and Fair Learning. ICLR (2023)
Ali Ghafelebashi, Meisam Razaviyayn, Maged Dessouky
Incentive Systems for Fleets of New Mobility Services. CoRR (2023)
Daniel Lundström, Meisam Razaviyayn
A Unifying Framework to the Analysis of Interaction Methods using Synergy Functions. ICML (2023)
Tianjian Huang, Shaunak Ashish Halbe, Chinnadhurai Sankar, Pooyan Amini, Satwik Kottur, Alborz Geramifard, Meisam Razaviyayn, Ahmad Beirami
Robustness through Data Augmentation Loss Consistency. Trans. Mach. Learn. Res. 2023 (2023)
Andrew Lowy, Meisam Razaviyayn
Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses. ICLR (2023)
Andrew Lowy, Zeman Li, Tianjian Huang, Meisam Razaviyayn
Optimal Differentially Private Learning with Public Data. CoRR (2023)
Zhongruo Wang, Krishnakumar Balasubramanian, Shiqian Ma, Meisam Razaviyayn
Zeroth-order algorithms for nonconvex-strongly-concave minimax problems with improved complexities. J. Glob. Optim. 87 (2) (2023)
Andrew Lowy, Meisam Razaviyayn
Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses. ALT (2023)
Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn
Private Non-Convex Federated Learning Without a Trusted Server. AISTATS (2023)
Sina Baharlouei, Fatemeh Sheikholeslami, Meisam Razaviyayn, Zico Kolter
Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes. AISTATS (2023)
Daniel Lundström, Meisam Razaviyayn
Distributing Synergy Functions: Unifying Game-Theoretic Interaction Methods for Machine-Learning Explainability. CoRR (2023)
Daniel Lundström, Meisam Razaviyayn
Four Axiomatic Characterizations of the Integrated Gradients Attribution Method. CoRR (2023)
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators. CoRR (2023)
Sina Baharlouei, Meisam Razaviyayn
Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Framework. CoRR (2023)
S. Karen Khatamifard, Zamshed I. Chowdhury, Nakul Pande, Meisam Razaviyayn, Chris H. Kim, Ulya R. Karpuzcu
GeNVoM: Read Mapping Near Non-Volatile Memory. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (6) (2022)
Andrew Lowy, Meisam Razaviyayn
Private Stochastic Optimization in the Presence of Outliers: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses. CoRR (2022)
Sina Baharlouei, Fatemeh Sheikholeslami, Meisam Razaviyayn, Zico Kolter
Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes. CoRR (2022)
Daniel Lundström, Tianjian Huang, Meisam Razaviyayn
A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions. CoRR (2022)
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
CRAM-Seq: Accelerating RNA-Seq Abundance Quantification Using Computational RAM. IEEE Trans. Emerg. Top. Comput. 10 (4) (2022)
Andrew Lowy, Devansh Gupta, Meisam Razaviyayn
Stochastic Differentially Private and Fair Learning. AFCP (2022)
Sina Baharlouei, Meisam Razaviyayn, Elizabeth Tseng, David Tse
I-CONVEX: Fast and Accurate de Novo Transcriptome Recovery from Long Reads. PKDD/ECML Workshops (2) (2022)
Andrew Lowy, Sina Baharlouei, Rakesh Pavan, Meisam Razaviyayn, Ahmad Beirami
A Stochastic Optimization Framework for Fair Risk Minimization. Trans. Mach. Learn. Res. 2022 (2022)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Tradeoffs between convergence rate and noise amplification for momentum-based accelerated optimization algorithms. CoRR (2022)
Andrew Lowy, Ali Ghafelebashi, Meisam Razaviyayn
Private Non-Convex Federated Learning Without a Trusted Server. CoRR (2022)
Andrew Lowy, Devansh Gupta, Meisam Razaviyayn
Stochastic Differentially Private and Fair Learning. CoRR (2022)
Maher Nouiehed, Meisam Razaviyayn
Learning Deep Models: Critical Points and Local Openness. INFORMS J. Optim. 4 (2) (2022)
Daniel Lundström, Tianjian Huang, Meisam Razaviyayn
A Rigorous Study of Integrated Gradients Method and Extensions to Internal Neuron Attributions. ICML (2022)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Robustness of Accelerated First-Order Algorithms for Strongly Convex Optimization Problems. IEEE Trans. Autom. Control. 66 (6) (2021)
Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn
Alternating Direction Method of Multipliers for Quantization. AISTATS (2021)
Andrew Lowy, Meisam Razaviyayn
Locally Differentially Private Federated Learning: Efficient Algorithms with Tight Risk Bounds. CoRR (2021)
Babak Barazandeh, Ali Ghafelebashi, Meisam Razaviyayn, Ram Sriharsha
Efficient Algorithms for Estimating the Parameters of Mixed Linear Regression Models. CoRR (2021)
Songtao Lu, Jason D. Lee, Meisam Razaviyayn, Mingyi Hong
Linearized ADMM Converges to Second-Order Stationary Points for Non-Convex Problems. IEEE Trans. Signal Process. 69 (2021)
Andrew Lowy, Rakesh Pavan, Sina Baharlouei, Meisam Razaviyayn, Ahmad Beirami
FERMI: Fair Empirical Risk Minimization via Exponential Rényi Mutual Information. CoRR (2021)
Dmitrii M. Ostrovskii, Babak Barazandeh, Meisam Razaviyayn
Nonconvex-Nonconcave Min-Max Optimization with a Small Maximization Domain. CoRR (2021)
Tianjian Huang, Shaunak Halbe, Chinnadhurai Sankar, Pooyan Amini, Satwik Kottur, Alborz Geramifard, Meisam Razaviyayn, Ahmad Beirami
DAIR: Data Augmented Invariant Regularization. CoRR (2021)
Dmitrii M. Ostrovskii, Andrew Lowy, Meisam Razaviyayn
Efficient Search of First-Order Nash Equilibria in Nonconvex-Concave Smooth Min-Max Problems. SIAM J. Optim. 31 (4) (2021)
Sina Baharlouei, Kelechi Ogudu, Sze-chuan Suen, Meisam Razaviyayn
RIFLE: Robust Inference from Low Order Marginals. CoRR (2021)
Andrew Lowy, Meisam Razaviyayn
Output Perturbation for Differentially Private Convex Optimization with Improved Population Loss Bounds, Runtimes and Applications to Private Adversarial Training. CoRR (2021)
Babak Barazandeh, Meisam Razaviyayn
Solving Non-Convex Non-Differentiable Min-Max Games Using Proximal Gradient Method. ICASSP (2020)
Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn
Alternating Direction Method of Multipliers for Quantization. CoRR (2020)
Mingyi Hong, Tsung-Hui Chang, Xiangfeng Wang, Meisam Razaviyayn, Shiqian Ma, Zhi-Quan Luo
A Block Successive Upper-Bound Minimization Method of Multipliers for Linearly Constrained Convex Optimization. Math. Oper. Res. 45 (3) (2020)
Meisam Razaviyayn, Tianjian Huang, Songtao Lu, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong
Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. IEEE Signal Process. Mag. 37 (5) (2020)
Zhongruo Wang, Krishnakumar Balasubramanian, Shiqian Ma, Meisam Razaviyayn
Zeroth-Order Algorithms for Nonconvex Minimax Problems with Improved Complexities. CoRR (2020)
Meisam Razaviyayn, Tianjian Huang, Songtao Lu, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong
Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. CoRR (2020)
Babak Barazandeh, Meisam Razaviyayn
Solving Non-Convex Non-Differentiable Min-Max Games using Proximal Gradient Method. CoRR (2020)
Maher Nouiehed, Meisam Razaviyayn
A Trust Region Method for Finding Second-Order Stationarity in Linearly Constrained Nonconvex Optimization. SIAM J. Optim. 30 (3) (2020)
Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong
Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems. NeurIPS (2020)
Sina Baharlouei, Maher Nouiehed, Ahmad Beirami, Meisam Razaviyayn
Rényi Fair Inference. ICLR (2020)
Maher Nouiehed, Jong-Shi Pang, Meisam Razaviyayn
Correction to: On the pervasiveness of difference-convexity in optimization and statistics. Math. Program. 174 (1-2) (2019)
Maher Nouiehed, Jong-Shi Pang, Meisam Razaviyayn
On the pervasiveness of difference-convexity in optimization and statistics. Math. Program. 174 (1-2) (2019)
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 (2019)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Performance of noisy Nesterov's accelerated method for strongly convex optimization problems. ACC (2019)
Sina Baharlouei, Maher Nouiehed, Meisam Razaviyayn
Rényi Fair Inference. CoRR (2019)
Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong
SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems. CoRR (2019)
Maziar Sanjabi, Sina Baharlouei, Meisam Razaviyayn, Jason D. Lee
When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima? CoRR (2019)
Babak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi
Training Generative Networks Using Random Discriminators. DSW (2019)
Babak Barazandeh, Meisam Razaviyayn, Maziar Sanjabi
Training generative networks using random discriminators. CoRR (2019)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Robustness of accelerated first-order algorithms for strongly convex optimization problems. CoRR (2019)
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)
Meisam Razaviyayn, Mingyi Hong, Navid Reyhanian, Zhi-Quan Luo
A linearly convergent doubly stochastic Gauss-Seidel algorithm for solving linear equations and a certain class of over-parameterized optimization problems. Math. Program. 176 (1-2) (2019)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
Variance Amplification of Accelerated First-Order Algorithms for Strongly Convex Quadratic Optimization Problems. CDC (2018)
Augusto Aubry, Antonio De Maio, Alessio Zappone, Meisam Razaviyayn, Zhi-Quan Luo
A New Sequential Optimization Procedure and Its Applications to Resource Allocation for Wireless Systems. IEEE Trans. Signal Process. 66 (24) (2018)
Zamshed I. Chowdhury, S. Karen Khatamifard, Zhengyang Zhao, Masoud Zabihi, Salonik Resch, Meisam Razaviyayn, Jianping Wang, Sachin S. Sapatnekar, Ulya R. Karpuzcu
Computational RAM to Accelerate String Matching at Scale. CoRR (2018)
Mingyi Hong, Meisam Razaviyayn, Jason D. Lee
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks. ICML (2018)
Maziar Sanjabi, Meisam Razaviyayn, Jason D. Lee
Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition. CoRR (2018)
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. NeurIPS (2018)
Babak Barazandeh, Meisam Razaviyayn
On the Behavior of the Expectation-Maximization Algorithm for Mixture Models. CoRR (2018)
Babak Barazandeh, Meisam Razaviyayn
On the Behavior of the Expectation-Maximization Algorithm for Mixture Models. GlobalSIP (2018)
Hesameddin Mohammadi, Meisam Razaviyayn, Mihailo R. Jovanovic
On the stability of gradient flow dynamics for a rank-one matrix approximation problem. ACC (2018)
Mingyi Hong, Jason D. Lee, Meisam Razaviyayn
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solutions for Nonconvex Distributed Optimization. CoRR (2018)
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
Solving Approximate Wasserstein GANs to Stationarity. CoRR (2018)
Maher Nouiehed, Meisam Razaviyayn
Learning Deep Models: Critical Points and Local Openness. ICLR (Workshop) (2018)
Ahmad Beirami, Meisam Razaviyayn, Shahin Shahrampour, Vahid Tarokh
On Optimal Generalizability in Parametric Learning. NIPS (2017)
Ahmad Beirami, Meisam Razaviyayn, Shahin Shahrampour, Vahid Tarokh
On Optimal Generalizability in Parametric Learning. CoRR (2017)
Mingyi Hong, Xiangfeng Wang, Meisam Razaviyayn, Zhi-Quan Luo
Iteration complexity analysis of block coordinate descent methods. Math. Program. 163 (1-2) (2017)
S. Karen Khatamifard, Zamshed I. Chowdhury, Nakul Pande, Meisam Razaviyayn, Chris H. Kim, Ulya R. Karpuzcu
A Non-volatile Near-Memory Read Mapping Accelerator. CoRR (2017)
Jong-Shi Pang, Meisam Razaviyayn, Alberth Alvarado
Computing B-Stationary Points of Nonsmooth DC Programs. Math. Oper. Res. 42 (1) (2017)
Mingyi Hong, Zhi-Quan Luo, Meisam Razaviyayn
Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems. SIAM J. Optim. 26 (1) (2016)
Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
SINR Constrained Beamforming for a MIMO Multi-User Downlink System: Algorithms and Convergence Analysis. IEEE Trans. Signal Process. 64 (11) (2016)
Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo, Jong-Shi Pang
A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing. IEEE Signal Process. Mag. 33 (1) (2016)
Qingjiang Shi, Haoran Sun, Songtao Lu, Mingyi Hong, Meisam Razaviyayn
Inexact Block Coordinate Descent Methods For Symmetric Nonnegative Matrix Factorization. CoRR (2016)
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) (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)
Meisam Razaviyayn, Farzan Farnia, David Tse
Discrete Rényi Classifiers. NIPS (2015)
Meisam Razaviyayn, Hung-Wei Tseng, Zhi-Quan Luo
Computational Intractability of Dictionary Learning for Sparse Representation. CoRR (2015)
Farzan Farnia, Meisam Razaviyayn, Sreeram Kannan, David Tse
Minimum HGR Correlation Principle: From Marginals to Joint Distribution. CoRR (2015)
Mingyi Hong, Zhi-Quan Luo, Meisam Razaviyayn
Convergence analysis of alternating direction method of multipliers for a family of nonconvex problems. ICASSP (2015)
Qingjiang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
SINR Constrained Beamforming for a MIMO Multi-user Downlink System. CoRR (2015)
Mingyi Hong, Tsung-Hui Chang, Xiangfeng Wang, Meisam Razaviyayn, Shiqian Ma, Zhi-Quan Luo
A block coordinate descent method of multipliers: Convergence analysis and applications. ICASSP (2014)
Meisam Razaviyayn, Mohammad Hadi Baligh, Aaron Callard, Zhi-Quan Luo
Joint User Grouping and Transceiver Design in a MIMO Interfering Broadcast Channel. IEEE Trans. Signal Process. 62 (1) (2014)
Meisam Razaviyayn, Hung-Wei Tseng, Zhi-Quan Luo
Dictionary learning for sparse representation: Complexity and algorithms. ICASSP (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Meisam Razaviyayn