Mehrdad Mahdavi

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 67

Top Venues

Publications

Yuyang Deng, Junyuan Hong, Jiayu Zhou, Mehrdad Mahdavi
On the Generalization Ability of Unsupervised Pretraining. CoRR (2024)
Weilin Cong, Jian Kang, Hanghang Tong, Mehrdad Mahdavi
On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method. CoRR (2024)
Yuyang Deng, Junyuan Hong, Jiayu Zhou, Mehrdad Mahdavi
On the Generalization Ability of Unsupervised Pretraining. AISTATS (2024)
Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
Do We Really Need Complicated Model Architectures For Temporal Networks? ICLR (2023)
Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. CoRR (2023)
Guneykan Ozgul, Xiantao Li, Mehrdad Mahdavi, Chunhao Wang
Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions. CoRR (2023)
Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. NeurIPS (2023)
Haobo Zhang, Junyuan Hong, Yuyang Deng, Mehrdad Mahdavi, Jiayu Zhou
Understanding Deep Gradient Leakage via Inversion Influence Functions. CoRR (2023)
Weilin Cong, Mehrdad Mahdavi
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. AISTATS (2023)
Weilin Cong, Si Zhang, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou, Hanghang Tong, Mehrdad Mahdavi
Do We Really Need Complicated Model Architectures For Temporal Networks? CoRR (2023)
Yuyang Deng, Nidham Gazagnadou, Junyuan Hong, Mehrdad Mahdavi, Lingjuan Lyu
On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space. CoRR (2023)
Ryan Tan, Heather Shoenberger, Weilin Cong, Mehrdad Mahdavi
Understanding the Structural Components Behind the Psychological Effects of Autonomous Sensory Meridian Response (ASMR) With Machine Learning and Experimental Methods. J. Media Psychol. Theor. Methods Appl. 35 (3) (2023)
Haobo Zhang, Junyuan Hong, Yuyang Deng, Mehrdad Mahdavi, Jiayu Zhou
Understanding Deep Gradient Leakage via Inversion Influence Functions. NeurIPS (2023)
Weilin Cong, Mehrdad Mahdavi
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. CoRR (2023)
Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi
DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. SDM (2023)
Yuyang Deng, Mohammad Mahdi Kamani, Pouria Mahdavinia, Mehrdad Mahdavi
Distributed Personalized Empirical Risk Minimization. CoRR (2023)
Yuyang Deng, Mohammad Mahdi Kamani, Pouria Mahdavinia, Mehrdad Mahdavi
Distributed Personalized Empirical Risk Minimization. NeurIPS (2023)
Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. ICLR (2022)
Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi
Efficient fair principal component analysis. Mach. Learn. 111 (10) (2022)
Pouria Mahdavinia, Yuyang Deng, Haochuan Li, Mehrdad Mahdavi
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems. NeurIPS (2022)
Huaipan Jiang, Jian Wang, Weilin Cong, Yihe Huang, Morteza Ramezani, Anup Sarma, Nikolay V. Dokholyan, Mehrdad Mahdavi, Mahmut T. Kandemir
Predicting Protein-Ligand Docking Structure with Graph Neural Network. J. Chem. Inf. Model. 62 (12) (2022)
Pouria Mahdavinia, Yuyang Deng, Haochuan Li, Mehrdad Mahdavi
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems. CoRR (2022)
Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi
Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time. AISTATS (2022)
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi
Learning Distributionally Robust Models at Scale via Composite Optimization. ICLR (2022)
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi
Learning Distributionally Robust Models at Scale via Composite Optimization. CoRR (2022)
Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris
Communication-Efficient $k$k-Means for Edge-Based Machine Learning. IEEE Trans. Parallel Distributed Syst. 33 (10) (2022)
Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. CoRR (2021)
Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi
Distributionally Robust Federated Averaging. CoRR (2021)
Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris
Communication-efficient k-Means for Edge-based Machine Learning. CoRR (2021)
Yuyang Deng, Mehrdad Mahdavi
Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time. CoRR (2021)
Yuyang Deng, Mehrdad Mahdavi
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency. AISTATS (2021)
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi
Federated Learning with Compression: Unified Analysis and Sharp Guarantees. AISTATS (2021)
Yuyang Deng, Mehrdad Mahdavi
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency. CoRR (2021)
Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi
On the Importance of Sampling in Learning Graph Convolutional Networks. CoRR (2021)
Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Mehrdad Mahdavi, Chun-cheng Jason Chen
Dynamic Graph Representation Learning via Graph Transformer Networks. CoRR (2021)
Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn
Meta-learning with an Adaptive Task Scheduler. CoRR (2021)
Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi
On Provable Benefits of Depth in Training Graph Convolutional Networks. CoRR (2021)
Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi
On Provable Benefits of Depth in Training Graph Convolutional Networks. NeurIPS (2021)
Mohammad Mahdi Kamani, Rana Forsati, James Z. Wang, Mehrdad Mahdavi
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing. CoRR (2021)
Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn
Meta-learning with an Adaptive Task Scheduler. NeurIPS (2021)
Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong
Online Structured Meta-learning. NeurIPS (2020)
Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi
Distributionally Robust Federated Averaging. NeurIPS (2020)
Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong
Online Structured Meta-learning. CoRR (2020)
Md Fahim Faysal Khan, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Vijaykrishnan Narayanan
Learning to Quantize Deep Neural Networks: A Competitive-Collaborative Approach. DAC (2020)
Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. KDD (2020)
Mohammad Mahdi Kamani, Sadegh Farhang, Mehrdad Mahdavi, James Z. Wang
Targeted Data-driven Regularization for Out-of-Distribution Generalization. KDD (2020)
Huaipan Jiang, Mengran Fan, Jian Wang, Anup Sarma, Shruti Mohanty, Nikolay V. Dokholyan, Mehrdad Mahdavi, Mahmut T. Kandemir
Guiding Conventional Protein-Ligand Docking Software with Convolutional Neural Networks. J. Chem. Inf. Model. 60 (10) (2020)
Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Anand Sivasubramaniam, Mahmut T. Kandemir
GCN meets GPU: Decoupling "When to Sample" from "How to Sample". NeurIPS (2020)
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi
Federated Learning with Compression: Unified Analysis and Sharp Guarantees. CoRR (2020)
Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi
Adaptive Personalized Federated Learning. CoRR (2020)
Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris
Communication-efficient k-Means for Edge-based Machine Learning. ICDCS (2020)
Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. CoRR (2020)
Md Fahim Faysal Khan, Nicholas Anton Jao, Changchi Shuai, Keni Qiu, Mehrdad Mahdavi, Vijaykrishnan Narayanan
Mixed Precision Quantization Scheme for Re-configurable ReRAM Crossbars Targeting Different Energy Harvesting Scenarios. IFIPIoT (2019)
Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi
Efficient Fair Principal Component Analysis. CoRR (2019)
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization. NeurIPS (2019)
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization. ICML (2019)
Samet Oymak, Mehrdad Mahdavi, Jiasi Chen
Learning Feature Nonlinearities with Regularized Binned Regression. ISIT (2019)
Farzin Haddadpour, Mehrdad Mahdavi
On the Convergence of Local Descent Methods in Federated Learning. CoRR (2019)
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization. CoRR (2019)
Samet Oymak, Mehrdad Mahdavi, Jiasi Chen
Learning Feature Nonlinearities with Non-Convex Regularized Binned Regression. CoRR (2017)
Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nati Srebro
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data. AISTATS (2017)
Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David A. Sontag
Train and Test Tightness of LP Relaxations in Structured Prediction. ICML (2016)
Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nathan Srebro
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data. CoRR (2016)
Mehrdad Mahdavi, Lijun Zhang, Rong Jin
Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization. COLT (2015)
Ofer Meshi, Mehrdad Mahdavi, Alexander G. Schwing
Smooth and Strong: MAP Inference with Linear Convergence. NIPS (2015)
Ofer Meshi, Mehrdad Mahdavi, David A. Sontag
On the Tightness of LP Relaxations for Structured Prediction. CoRR (2015)
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu
An efficient primal dual prox method for non-smooth optimization. Mach. Learn. 98 (3) (2015)
Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu
Random Projections for Classification: A Recovery Approach. IEEE Trans. Inf. Theory 60 (11) (2014)
Mehrdad Mahdavi
Exploiting Smoothness in Statistical Learning, Sequential Prediction, and Stochastic Optimization. CoRR (2014)
Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard, Mohamed Sarwat
Matrix Factorization with Explicit Trust and Distrust Relationships. CoRR (2014)
Mehrdad Mahdavi, Lijun Zhang, Rong Jin
Binary Excess Risk for Smooth Convex Surrogates. CoRR (2014)
Mehrdad Mahdavi, Rong Jin
Excess Risk Bounds for Exponentially Concave Losses. CoRR (2014)
Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard, Mohamed Sarwat
Matrix Factorization with Explicit Trust and Distrust Side Information for Improved Social Recommendation. ACM Trans. Inf. Syst. 32 (4) (2014)
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu
Regret bounded by gradual variation for online convex optimization. Mach. Learn. 95 (2) (2014)
Rong Jin, Tianbao Yang, Mehrdad Mahdavi
Sparse Multiple Kernel Learning with Geometric Convergence Rate CoRR (2013)
Rong Jin, Tianbao Yang, Mehrdad Mahdavi, Yu-Feng Li, Zhi-Hua Zhou
Improved Bounds for the Nyström Method With Application to Kernel Classification. IEEE Trans. Inf. Theory 59 (10) (2013)
Lijun Zhang, Mehrdad Mahdavi, Rong Jin
Improving the Minimax Rate of Active Learning. CoRR (2013)
Mehrdad Mahdavi, Lijun Zhang, Rong Jin
Mixed Optimization for Smooth Functions. NIPS (2013)
Mehrdad Mahdavi, Tianbao Yang, Rong Jin
Stochastic Convex Optimization with Multiple Objectives. NIPS (2013)
Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard, Mohammad Reza Meybodi
Efficient stochastic algorithms for document clustering. Inf. Sci. 220 (2013)
Mehrdad Mahdavi, Rong Jin
Passive Learning with Target Risk. COLT (2013)
Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu
Recovering the Optimal Solution by Dual Random Projection. COLT (2013)
Mehrdad Mahdavi, Rong Jin
MixedGrad: An O(1/T) Convergence Rate Algorithm for Stochastic Smooth Optimization. CoRR (2013)
Lijun Zhang, Mehrdad Mahdavi, Rong Jin
Linear Convergence with Condition Number Independent Access of Full Gradients. NIPS (2013)
Mehrdad Mahdavi, Rong Jin
Passive Learning with Target Risk CoRR (2013)
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou
Multiple Kernel Learning from Noisy Labels by Stochastic Programming. ICML (2012)
Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi
Stochastic Gradient Descent with Only One Projection. NIPS (2012)
Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin, Shenghuo Zhu
Online Optimization with Gradual Variations. COLT (2012)
Mehrdad Mahdavi, Tianbao Yang, Rong Jin
An Improved Bound for the Nystrom Method for Large Eigengap CoRR (2012)
Tianbao Yang, Yu-Feng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison. NIPS (2012)
Mehrdad Mahdavi, Tianbao Yang, Rong Jin
Efficient Constrained Regret Minimization CoRR (2012)
Mehrdad Mahdavi, Tianbao Yang, Rong Jin
Online Stochastic Optimization with Multiple Objectives CoRR (2012)
Mehrdad Mahdavi, Rong Jin, Tianbao Yang
Trading regret for efficiency: online convex optimization with long term constraints. J. Mach. Learn. Res. 13 (2012)
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi
Online Kernel Selection: Algorithms and Evaluations. AAAI (2012)
Tianbao Yang, Rong Jin, Mehrdad Mahdavi, Shenghuo Zhu
An Efficient Primal-Dual Prox Method for Non-Smooth Optimization CoRR (2012)
Jinfeng Yi, Tianbao Yang, Rong Jin, Anil K. Jain, Mehrdad Mahdavi
Robust Ensemble Clustering by Matrix Completion. ICDM (2012)
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou
Multiple Kernel Learning from Noisy Labels by Stochastic Programming CoRR (2012)
Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang
Recovering Optimal Solution by Dual Random Projection CoRR (2012)
Mehrdad Mahdavi, Rong Jin, Tianbao Yang
Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints CoRR (2011)
Rong Jin, Tianbao Yang, Mehrdad Mahdavi
Improved Bound for the Nystrom's Method and its Application to Kernel Classification CoRR (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Mehrdad Mahdavi