Journal Articles
- Mehrdad Mahdavi and Pouria Mahdavinia, 2025, "Low-rank Momentum Factorization for Memory Efficient Training", Transactions on Machine Learning Research (TMLR)
- Mehrdad Mahdavi, Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Vijaykrishnan Narayanan, Kevin Chan and Stephen Pasteris, 2022, "Communication-Efficient k-Means for Edge-Based Machine Learning", IEEE Transactions on Parallel and Distributed Systems
- Mehrdad Mahdavi, Huaipan Jiang, Jian Wang, Weilin Cong, Morteza Ramezani, Anup Sarma, Nikolay Dokholyan and Mahmut Kandemir, 2022, "Predicting Protein–Ligand Docking Structure with Graph Neural Network", Journal of Chemical Information and Modeling
- Mehrdad Mahdavi, Mohammad Mahdi Kamani, Farzin Haddadpour and Rana Forsati, 2022, "Efficient fair principal component analysis", Machine Learning
- Mehrdad Mahdavi, Mengran Fan, Jian Wang, Huaipan Jiang, Yilin Feng, Kamesh Madduri, Mahmut T Kandemir and Nikolay Dokholyan, 2021, "Gpu-accelerated Flexible Molecular Docking", The Journal of Physical Chemistry B, 125, (4)
- Mehrdad Mahdavi, Huaipan Jiang, Mengran Fan, Jian Wang, Anup Sarma, Shruti Mohanty, Nikolay Dokholyan and Mahmut T Kandemir, 2020, "Guiding Conventional Protein–Ligand Docking Software with Convolutional Neural Networks", Journal of Chemical Information and Modeling
- Jialei Wang, Jason D Lee, Mehrdad Mahdavi, Mladen Kolar, Nathan Srebro and others, 2018, "Sketching meets random projection in the dual: A provable recovery algorithm for big and high-dimensional data", Electronic Journal of Statistics, 11, (2), pp. 4896--4944
- Mehrdad Mahdavi, 2015, "Random Projections for Classification: A Recovery Approach", IEEE Transactions on Information Theory
- Tianbao Yang, Mehrdad Mahdavi, Rong Jin and Shenghuo Zhu, 2014, "An efficient primal dual prox method for non-smooth optimization", Machine Learning Journal, pp. 1--38
- Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard and Mohamed Sarwat, 2014, "Matrix factorization with explicit trust and distrust side information for improved social recommendation", ACM Transactions on Information Systems (TOIS), 32, (4), pp. 17
- L Zhang, Mehrdad Mahdavi, R Jin, Tinglu Yang and S Zhu, 2014, "Random Projections for Classification: A Recovery Approach", IEEE Transactions on Information Theory
- Tianbao Yang, Mehrdad Mahdavi, Rong Jin and Shenghuo Zhu, 2014, "Regret bounded by gradual variation for online convex optimization", Machine Learning Journal, pp. 1--41
- Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard and Mohammad Reza Meybodi, 2013, "Efficient stochastic algorithms for document clustering", Information Sciences, 220, pp. 269--291
- Mehrdad Mahdavi, Rong Jin and Tianbao Yang, 2012, "Trading regret for efficiency: online convex optimization with long term constraints", Journal of Machine Learning Research (JMLR), 13, pp. 2503--2528
- Mehrdad Mahdavi and Hassan Abolhassani, 2009, "Harmony k-means algorithm for document clustering", Data Mining and Knowledge Discovery, 18, (3), pp. 370--391
- Mahamed GH Omran and Mehrdad Mahdavi, 2008, "Global-best harmony search", Applied Mathematics and Computation, 198, (2), pp. 643--656
- Mehrdad Mahdavi, Mohammad Fesanghary and Ebrahim Damangir, 2007, "An improved harmony search algorithm for solving optimization problems", Applied Mathematics and Computation, 188, (2), pp. 1567--1579
Conference Proceedings
- Mehrdad Mahdavi, Ajay Narayanan Sridhar, Fuli Qiao, Nelson Aldas Daniel Troncoso Aldas, Yanpei Shi, Laurent Itti and Vijaykrishnan Narayanan, 2025, "NaviSense: A Multimodal Assistive Mobile application for Object Retrieval by Persons with Visual Impairment", ACM SIGACCESS Conference on Computers and Accessibility
- Mehrdad Mahdavi, Yuyang Deng and Fuli Qiao, 2025, "Stochastic Compositional Minimax Optimization with Provable Convergence Guarantees", International Conference on Artificial Intelligence and Statistics
- Mehrdad Mahdavi and Weilin Cong, 2023, "Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection"
- Mehrdad Mahdavi, Weilin Cong, Jian Kang, Baichuan Yuan, Hao Wu, Xin Zhou and Hanghang Tong, 2023, "Do We Really Need Complicated Model Architectures For Temporal Networks?"
- Mehrdad Mahdavi, Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia and Chun-cheng Chen, 2023, "DyFormer: A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability", SIAM International Conference on Data Mining (SDM)
- Mehrdad Mahdavi, Pouria Mahdavinia, Yuyang Deng and Haochuan Li, 2022, "Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems"
- Mehrdad Mahdavi and Yuyang Deng, 2022, "Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time"
- Mehrdad Mahdavi, Morteza Ramezani, Weilin Cong, Mahmut T Kandemir and Anand Sivasubramaniam, 2022, "Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks"
- Mehrdad Mahdavi, Farzin Haddadpour, Mohammad Mahdi Kamani and Amin Karbasi, 2022, "Learning Distributionally Robust Models at Scale via Composite Optimization"
- Mehrdad Mahdavi, Weilin Cong and Morteza Ramezani, 2021, "On Provable Benefits of Depth in Training Graph Convolutional Networks"
- Mehrdad Mahdavi, Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Defu Lian and Chelsea Finn, 2021, "Meta-learning with an Adaptive Task Scheduler"
- Mehrdad Mahdavi and Yuyang Deng, 2021, "Local stochastic gradient descent ascent: Convergence analysis and communication efficiency"
- Mehrdad Mahdavi, Farzin Haddadpour, Mohammad Mahdi Kamani and Aryan Mokhtari, 2021, "Federated learning with compression: Unified analysis and sharp guarantees"
- Mehrdad Mahdavi, Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Vijaykrishnan Narayanan, Kevin S. Chan and Stephen Pasteris, 2020, "Communication-efficient k-Means for Edge-based Machine Learning"
- Mehrdad Mahdavi, Md Fahim Faysal Khan, Mohammad Kamani and Vijay Narayanan, 2020, "Learning to Quantize Deep Neural Networks: A Competitive-Collaborative Approach", Design Automation Conference (DAC)
- Mehrdad Mahdavi, Mohammad Mahdi Kamani, Sadegh Farhang and James Z Wang, 2020, "Targeted Data-driven Regularization for Out-of-Distribution Generalization"
- Mehrdad Mahdavi, Weilin Cong, Rana Forsati and Mahmut T Kandemir, 2020, "Minimal variance sampling with provable guarantees for fast training of graph neural networks"
- Mehrdad Mahdavi, Huaxiu Yao, Yingbo Zhou, Zhenhui Li, Richard Socher and Caiming Xiong, 2020, "Online Structured Meta-learning"
- Mehrdad Mahdavi, Yuyang Deng and Mohammad Mahdi Kamani, 2020, "Distributionally Robust Federated Averaging"
- Mehrdad Mahdavi, Morteza Ramezani, Weilin Cong, Anand Sivasubramaniam and Mahmut T Kandemir, 2020, "GCN meets GPU: Decoupling “When to Sample” from “How to Sample”"
- Samet Oymak, Mehrdad Mahdavi and Jiasi Chen, 2019, "Learning Feature Nonlinearities with Non-Convex Regularized Binned Regression"
- Farzin Haddadpour, Mahdi Kamani, Mehrdad Mahdav and, Viveck Cadambe , 2019, "Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization"
- Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi and Viveck Ramesh Cadambe, 2019, "Local SGD with periodic averaging: Tighter analysis and adaptive synchronization", pp. 11080--11092
- Mohammad Mahdi Kamani, Sadegh Farhang, Mehrdad Mahdavi and James Z Wang, 2019, "Targeted meta-learning for critical incident detection in weather data"
- Ofer Meshi, Mehrdad Mahdavi, Adrian Weller and David Sontag, 2016, "Train and Test Tightness of LP Relaxations in Structured Prediction"
- Mehrdad Mahdavi, Lijun Zhang and Rong Jin, 2015, "Lower and upper bounds on the generalization of stochastic exponentially concave optimization", pp. 1305--1320
- Ofer Meshi, Mehrdad Mahdavi and Alex Schwing, 2015, "Smooth and strong: MAP inference with linear convergence", pp. 298--306
- Tianbao Yang, Yu-Feng Li, Mehrdad Mahdavi, Rong Jin and Zhi-Hua Zhou, 2013, "Nystrom method vs random fourier features: a theoretical and empirical comparison", Advances in Neural Information Processing Systems
- Lijun Zhang, Mehrdad Mahdavi and Rong Jin, 2013, "Linear convergence with condition number independent access of full gradients", pp. 980--988
- Mehrdad Mahdavi, Lijun Zhang and Rong Jin, 2013, "Mixed optimization for smooth functions", pp. 674--682
- Mehrdad Mahdavi and Rong Jin, 2013, "Passive learning with target risk"
- Mehrdad Mahdavi, Tianbao Yang and Rong Jin, 2013, "Stochastic convex optimization with multiple objectives", pp. 1115--1123
- Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang and Yang Zhou, 2012, "Multiple kernel learning from noisy labels by stochastic programming"
- Mehrdad Mahdavi, Tianbao Yang and Rong Jin, 2012, "Online decision making under stochastic constraints"
- Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi and Steven CH Hoi, 2012, "Online kernel selection: algorithms and evaluations."
- Lijun Zhang, Mehrdad Mahdavi, Rong Jin and Tianbao Yang, 2012, "Recovering the optimal solution by dual random projection"
- Jinfeng Yi, Tianbao Yang, Rong Jin, Anil K Jain and Mehrdad Mahdavi, 2012, "Robust ensemble clustering by matrix completion", pp. 1176--1181
- Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu and Jinfeng Yi, 2012, "Stochastic gradient descent with only one projection"
- Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin and Shenghuo Zhu, 2012, "Online optimization with gradual variations.", 23, pp. 6--1
- Rana Forsati, Mehrdad Mahdavi, Abolfazl Torghy Haghighat and Azadeh Ghariniyat, 2008, "An efficient algorithm for bandwidth-delay constrained least cost multicast routing", pp. 001641--001646
- Rana Forsati, MohammadReza Meybodi, Mehrdad Mahdavi and AzadehGhari Neiat, 2008, "Hybridization of k-means and harmony search methods for web page clustering", pp. 329--335
- Rana Forsati, Mehrdad Mahdavi, Mohammadreza Kangavari and Banafsheh Safarkhani, 2008, "Web page clustering using harmony search optimization", pp. 001601--001604
- Jialei Wang, Jason Lee, Mehrdad Mahdavi, Mladen Kolar and Nathan Srebro, , "A provable recovery algorithm for big and high-dimensional data"
- Mehrdad Mahdavi and Fuli Qiao, , "Merge before Forget: A Single LoRA Continual Learning via Continual Merging", International Conference on Learning Representations (ICLR), University Park, United States
