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Journal Articles
- 2023
[j17]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): 181-189 (2023)- 2022
- [j16]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): 2923-2932 (2022) - [j15]Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi:
Efficient fair principal component analysis. Mach. Learn. 111(10): 3671-3702 (2022) - [j14]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): 2509-2523 (2022) - 2020
- [j13]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): 4594-4602 (2020) - 2015
- [j12]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu:
An efficient primal dual prox method for non-smooth optimization. Mach. Learn. 98(3): 369-406 (2015) - 2014
- [j11]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Shenghuo Zhu:
Regret bounded by gradual variation for online convex optimization. Mach. Learn. 95(2): 183-223 (2014) - [j10]Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu:
Random Projections for Classification: A Recovery Approach. IEEE Trans. Inf. Theory 60(11): 7300-7316 (2014) - [j9]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): 17:1-17:38 (2014) - 2013
- [j8]Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard, Mohammad Reza Meybodi:
Efficient stochastic algorithms for document clustering. Inf. Sci. 220: 269-291 (2013) - [j7]Rong Jin, Tianbao Yang, Mehrdad Mahdavi, Yufeng Li, Zhi-Hua Zhou:
Improved Bounds for the Nyström Method With Application to Kernel Classification. IEEE Trans. Inf. Theory 59(10): 6939-6949 (2013) - 2012
- [j6]Mehrdad Mahdavi, Rong Jin, Tianbao Yang:
Trading regret for efficiency: online convex optimization with long term constraints. J. Mach. Learn. Res. 13: 2503-2528 (2012) - 2009
- [j5]Mehrdad Mahdavi, Hassan Abolhassani:
Harmony K-means algorithm for document clustering. Data Min. Knowl. Discov. 18(3): 370-391 (2009) - 2008
- [j4]Mahamed G. H. Omran, Mehrdad Mahdavi:
Global-best harmony search. Appl. Math. Comput. 198(2): 643-656 (2008) - [j3]Mehrdad Mahdavi, Morteza Haghir Chehreghani, Hassan Abolhassani, Rana Forsati:
Novel meta-heuristic algorithms for clustering web documents. Appl. Math. Comput. 201(1-2): 441-451 (2008) - [j2]Rana Forsati, A. T. Haghighat, Mehrdad Mahdavi:
Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing. Comput. Commun. 31(10): 2505-2519 (2008) - 2007
- [j1]Mehrdad Mahdavi, Mohammad Fesanghary, Ebrahim Damangir:
An improved harmony search algorithm for solving optimization problems. Appl. Math. Comput. 188(2): 1567-1579 (2007)
Conference and Workshop Papers
- 2024
- [c44]Yuyang Deng, Junyuan Hong, Jiayu Zhou, Mehrdad Mahdavi:
On the Generalization Ability of Unsupervised Pretraining. AISTATS 2024: 4519-4527 - [c43]Guneykan Ozgul, Xiantao Li, Mehrdad Mahdavi, Chunhao Wang:
Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions. ICML 2024 - 2023
- [c42]Weilin Cong, Mehrdad Mahdavi:
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. AISTATS 2023: 6674-6703 - [c41]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 - [c40]Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi:
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. NeurIPS 2023 - [c39]Yuyang Deng, Mohammad Mahdi Kamani, Pouria Mahdavinia, Mehrdad Mahdavi:
Distributed Personalized Empirical Risk Minimization. NeurIPS 2023 - [c38]Haobo Zhang, Junyuan Hong, Yuyang Deng, Mehrdad Mahdavi, Jiayu Zhou:
Understanding Deep Gradient Leakage via Inversion Influence Functions. NeurIPS 2023 - [c37]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: 442-450 - 2022
- [c36]Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi:
Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time. AISTATS 2022: 6840-6861 - [c35]Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi:
Learning Distributionally Robust Models at Scale via Composite Optimization. ICLR 2022 - [c34]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 - [c33]Pouria Mahdavinia, Yuyang Deng, Haochuan Li, Mehrdad Mahdavi:
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems. NeurIPS 2022 - 2021
- [c32]Yuyang Deng, Mehrdad Mahdavi:
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency. AISTATS 2021: 1387-1395 - [c31]Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi:
Federated Learning with Compression: Unified Analysis and Sharp Guarantees. AISTATS 2021: 2350-2358 - [c30]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. NeurIPS 2021: 7497-7509 - [c29]Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi:
On Provable Benefits of Depth in Training Graph Convolutional Networks. NeurIPS 2021: 9936-9949 - 2020
- [c28]Md Fahim Faysal Khan, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Vijaykrishnan Narayanan:
Learning to Quantize Deep Neural Networks: A Competitive-Collaborative Approach. DAC 2020: 1-6 - [c27]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: 595-605 - [c26]Mohammad Mahdi Kamani, Sadegh Farhang, Mehrdad Mahdavi, James Z. Wang:
Targeted Data-driven Regularization for Out-of-Distribution Generalization. KDD 2020: 882-891 - [c25]Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi:
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. KDD 2020: 1393-1403 - [c24]Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi:
Distributionally Robust Federated Averaging. NeurIPS 2020 - [c23]Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Anand Sivasubramaniam, Mahmut T. Kandemir:
GCN meets GPU: Decoupling "When to Sample" from "How to Sample". NeurIPS 2020 - [c22]Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong:
Online Structured Meta-learning. NeurIPS 2020 - 2019
- [c21]Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe:
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization. ICML 2019: 2545-2554 - [c20]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: 197-216 - [c19]Samet Oymak, Mehrdad Mahdavi, Jiasi Chen:
Learning Feature Nonlinearities with Regularized Binned Regression. ISIT 2019: 1452-1456 - [c18]Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe:
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization. NeurIPS 2019: 11080-11092 - 2017
- [c17]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: 1150-1158 - 2016
- [c16]Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David A. Sontag:
Train and Test Tightness of LP Relaxations in Structured Prediction. ICML 2016: 1776-1785 - 2015
- [c15]Mehrdad Mahdavi, Lijun Zhang, Rong Jin:
Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave Optimization. COLT 2015: 1305-1320 - [c14]Ofer Meshi, Mehrdad Mahdavi, Alexander G. Schwing:
Smooth and Strong: MAP Inference with Linear Convergence. NIPS 2015: 298-306 - 2013
- [c13]Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang, Shenghuo Zhu:
Recovering the Optimal Solution by Dual Random Projection. COLT 2013: 135-157 - [c12]Mehrdad Mahdavi, Rong Jin:
Passive Learning with Target Risk. COLT 2013: 252-269 - [c11]Mehrdad Mahdavi, Lijun Zhang, Rong Jin:
Mixed Optimization for Smooth Functions. NIPS 2013: 674-682 - [c10]Lijun Zhang, Mehrdad Mahdavi, Rong Jin:
Linear Convergence with Condition Number Independent Access of Full Gradients. NIPS 2013: 980-988 - [c9]Mehrdad Mahdavi, Tianbao Yang, Rong Jin:
Stochastic Convex Optimization with Multiple Objectives. NIPS 2013: 1115-1123 - 2012
- [c8]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi:
Online Kernel Selection: Algorithms and Evaluations. AAAI 2012: 1197-1203 - [c7]Jinfeng Yi, Tianbao Yang, Rong Jin, Anil K. Jain, Mehrdad Mahdavi:
Robust Ensemble Clustering by Matrix Completion. ICDM 2012: 1176-1181 - [c6]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou:
Multiple Kernel Learning from Noisy Labels by Stochastic Programming. ICML 2012 - [c5]Tianbao Yang, Yufeng Li, Mehrdad Mahdavi, Rong Jin, Zhi-Hua Zhou:
Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison. NIPS 2012: 485-493 - [c4]Mehrdad Mahdavi, Tianbao Yang, Rong Jin, Shenghuo Zhu, Jinfeng Yi:
Stochastic Gradient Descent with Only One Projection. NIPS 2012: 503-511 - [c3]Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin, Shenghuo Zhu:
Online Optimization with Gradual Variations. COLT 2012: 6.1-6.20 - 2008
- [c2]Mehrdad Mahdavi, Rana Forsati, Ali Movaghar:
Bandwidth-Delay Constrained Least Cost Multicast Routing for Multimedia Communication. CSICC 2008: 737-740 - [c1]Rana Forsati, Mohammad Reza Meybodi, Mehrdad Mahdavi, Azadeh Ghari Neiat:
Hybridization of K-Means and Harmony Search Methods for Web Page Clustering. Web Intelligence 2008: 329-335
Parts in Books or Collections
- 2010
- [p1]Rana Forsati, Mehrdad Mahdavi:
Web Text Mining Using Harmony Search. Recent Advances In Harmony Search Algorithm 2010: 51-64
Informal and Other Publications
- 2024
- [i49]Weilin Cong, Jian Kang, Hanghang Tong, Mehrdad Mahdavi:
On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method. CoRR abs/2402.16387 (2024) - [i48]Yuyang Deng, Junyuan Hong, Jiayu Zhou, Mehrdad Mahdavi:
On the Generalization Ability of Unsupervised Pretraining. CoRR abs/2403.06871 (2024) - [i47]Yuyang Deng, Fuli Qiao, Mehrdad Mahdavi:
Stochastic Compositional Minimax Optimization with Provable Convergence Guarantees. CoRR abs/2408.12505 (2024) - 2023
- [i46]Weilin Cong, Mehrdad Mahdavi:
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection. CoRR abs/2302.08990 (2023) - [i45]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 abs/2302.11636 (2023) - [i44]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 abs/2302.12351 (2023) - [i43]Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi:
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. CoRR abs/2309.10736 (2023) - [i42]Haobo Zhang, Junyuan Hong, Yuyang Deng, Mehrdad Mahdavi, Jiayu Zhou:
Understanding Deep Gradient Leakage via Inversion Influence Functions. CoRR abs/2309.13016 (2023) - [i41]Guneykan Ozgul, Xiantao Li, Mehrdad Mahdavi, Chunhao Wang:
Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions. CoRR abs/2310.11445 (2023) - [i40]Yuyang Deng, Mohammad Mahdi Kamani, Pouria Mahdavinia, Mehrdad Mahdavi:
Distributed Personalized Empirical Risk Minimization. CoRR abs/2310.17761 (2023) - 2022
- [i39]Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Amin Karbasi:
Learning Distributionally Robust Models at Scale via Composite Optimization. CoRR abs/2203.09607 (2022) - [i38]Pouria Mahdavinia, Yuyang Deng, Haochuan Li, Mehrdad Mahdavi:
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems. CoRR abs/2210.09382 (2022) - 2021
- [i37]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 abs/2102.04282 (2021) - [i36]Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi:
Distributionally Robust Federated Averaging. CoRR abs/2102.12660 (2021) - [i35]Yuyang Deng, Mehrdad Mahdavi:
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency. CoRR abs/2102.13152 (2021) - [i34]Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi:
On the Importance of Sampling in Learning Graph Convolutional Networks. CoRR abs/2103.02696 (2021) - [i33]Mohammad Mahdi Kamani, Rana Forsati, James Z. Wang, Mehrdad Mahdavi:
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing. CoRR abs/2104.01634 (2021) - [i32]Yuyang Deng, Mehrdad Mahdavi:
Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time. CoRR abs/2107.10868 (2021) - [i31]Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn:
Meta-learning with an Adaptive Task Scheduler. CoRR abs/2110.14057 (2021) - [i30]Weilin Cong, Morteza Ramezani, Mehrdad Mahdavi:
On Provable Benefits of Depth in Training Graph Convolutional Networks. CoRR abs/2110.15174 (2021) - [i29]Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Mahmut T. Kandemir, Anand Sivasubramaniam:
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks. CoRR abs/2111.08202 (2021) - [i28]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 abs/2111.10447 (2021) - 2020
- [i27]Yuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi:
Adaptive Personalized Federated Learning. CoRR abs/2003.13461 (2020) - [i26]Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi:
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. CoRR abs/2006.13866 (2020) - [i25]Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi:
Federated Learning with Compression: Unified Analysis and Sharp Guarantees. CoRR abs/2007.01154 (2020) - [i24]Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong:
Online Structured Meta-learning. CoRR abs/2010.11545 (2020) - 2019
- [i23]Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe:
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization. CoRR abs/1910.13598 (2019) - [i22]Farzin Haddadpour, Mehrdad Mahdavi:
On the Convergence of Local Descent Methods in Federated Learning. CoRR abs/1910.14425 (2019) - [i21]Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi:
Efficient Fair Principal Component Analysis. CoRR abs/1911.04931 (2019) - 2017
- [i20]Samet Oymak, Mehrdad Mahdavi, Jiasi Chen:
Learning Feature Nonlinearities with Non-Convex Regularized Binned Regression. CoRR abs/1705.07256 (2017) - 2016
- [i19]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 abs/1610.03045 (2016) - 2015
- [i18]Ofer Meshi, Mehrdad Mahdavi, David A. Sontag:
On the Tightness of LP Relaxations for Structured Prediction. CoRR abs/1511.01419 (2015) - 2014
- [i17]Mehrdad Mahdavi, Rong Jin:
Excess Risk Bounds for Exponentially Concave Losses. CoRR abs/1401.4566 (2014) - [i16]Mehrdad Mahdavi, Lijun Zhang, Rong Jin:
Binary Excess Risk for Smooth Convex Surrogates. CoRR abs/1402.1792 (2014) - [i15]Mehrdad Mahdavi:
Exploiting Smoothness in Statistical Learning, Sequential Prediction, and Stochastic Optimization. CoRR abs/1407.5908 (2014) - [i14]Rana Forsati, Mehrdad Mahdavi, Mehrnoush Shamsfard, Mohamed Sarwat:
Matrix Factorization with Explicit Trust and Distrust Relationships. CoRR abs/1408.0325 (2014) - 2013
- [i13]Rong Jin, Tianbao Yang, Mehrdad Mahdavi:
Sparse Multiple Kernel Learning with Geometric Convergence Rate. CoRR abs/1302.0315 (2013) - [i12]Mehrdad Mahdavi, Rong Jin:
Passive Learning with Target Risk. CoRR abs/1302.2157 (2013) - [i11]Mehrdad Mahdavi, Rong Jin:
MixedGrad: An O(1/T) Convergence Rate Algorithm for Stochastic Smooth Optimization. CoRR abs/1307.7192 (2013) - [i10]Lijun Zhang, Mehrdad Mahdavi, Rong Jin:
Improving the Minimax Rate of Active Learning. CoRR abs/1311.4803 (2013) - 2012
- [i9]Tianbao Yang, Rong Jin, Mehrdad Mahdavi, Shenghuo Zhu:
An Efficient Primal-Dual Prox Method for Non-Smooth Optimization. CoRR abs/1201.5283 (2012) - [i8]Mehrdad Mahdavi, Tianbao Yang, Rong Jin:
Efficient Constrained Regret Minimization. CoRR abs/1205.2265 (2012) - [i7]Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou:
Multiple Kernel Learning from Noisy Labels by Stochastic Programming. CoRR abs/1206.4629 (2012) - [i6]Mehrdad Mahdavi, Tianbao Yang, Rong Jin:
An Improved Bound for the Nystrom Method for Large Eigengap. CoRR abs/1209.0001 (2012) - [i5]Lijun Zhang, Mehrdad Mahdavi, Rong Jin, Tianbao Yang:
Recovering Optimal Solution by Dual Random Projection. CoRR abs/1211.3046 (2012) - [i4]Mehrdad Mahdavi, Tianbao Yang, Rong Jin:
Online Stochastic Optimization with Multiple Objectives. CoRR abs/1211.6013 (2012) - 2011
- [i3]Rong Jin, Tianbao Yang, Mehrdad Mahdavi:
Improved Bound for the Nystrom's Method and its Application to Kernel Classification. CoRR abs/1111.2262 (2011) - [i2]Mehrdad Mahdavi, Rong Jin, Tianbao Yang:
Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints. CoRR abs/1111.6082 (2011) - [i1]Tianbao Yang, Rong Jin, Mehrdad Mahdavi:
Regret Bound by Variation for Online Convex Optimization. CoRR abs/1111.6337 (2011)
Coauthor Index
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