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2020 – today
- 2022
[c100]Udaya Ghai, Udari Madhushani, Naomi Ehrich Leonard, Elad Hazan:
A Regret Minimization Approach to Multi-Agent Control. ICML 2022: 7422-7434- [c99]Udaya Ghai, Xinyi Chen, Elad Hazan, Alexandre Megretski:
Robust Online Control with Model Misspecification. L4DC 2022: 1163-1175 - [i85]Udaya Ghai, Udari Madhushani, Naomi Ehrich Leonard, Elad Hazan:
A Regret Minimization Approach to Multi-Agent Contro. CoRR abs/2201.13288 (2022) - [i84]Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan:
Online Control of Unknown Time-Varying Dynamical Systems. CoRR abs/2202.07890 (2022) - [i83]Zhou Lu, Wenhan Xia, Sanjeev Arora, Elad Hazan:
Adaptive Gradient Methods with Local Guarantees. CoRR abs/2203.01400 (2022) - [i82]Udaya Ghai, Zhou Lu, Elad Hazan:
Non-convex online learning via algorithmic equivalence. CoRR abs/2205.15235 (2022) - [i81]Xinyi Chen, Elad Hazan, Tongyang Li, Zhou Lu, Xinzhao Wang, Rui Yang:
Adaptive Online Learning of Quantum States. CoRR abs/2206.00220 (2022) - [i80]Zhou Lu, Elad Hazan:
Efficient Adaptive Regret Minimization. CoRR abs/2207.00646 (2022) - 2021
- [c98]Nataly Brukhim, Elad Hazan:
Online Boosting with Bandit Feedback. ALT 2021: 397-420 - [c97]Xinyi Chen, Elad Hazan:
Black-Box Control for Linear Dynamical Systems. COLT 2021: 1114-1143 - [c96]Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh:
A Regret Minimization Approach to Iterative Learning Control. ICML 2021: 100-109 - [c95]Elad Hazan, Karan Singh:
Boosting for Online Convex Optimization. ICML 2021: 4140-4149 - [c94]Udaya Ghai, David Snyder, Anirudha Majumdar, Elad Hazan:
Generating Adversarial Disturbances for Controller Verification. L4DC 2021: 1192-1204 - [c93]Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire:
Multiclass Boosting and the Cost of Weak Learning. NeurIPS 2021: 3057-3067 - [c92]Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan:
Online Control of Unknown Time-Varying Dynamical Systems. NeurIPS 2021: 15934-15945 - [c91]Noga Alon
, Alon Gonen, Elad Hazan, Shay Moran:
Boosting simple learners. STOC 2021: 481-489 - [i79]Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel Cohen, Elad Hazan:
Machine Learning for Mechanical Ventilation Control. CoRR abs/2102.06779 (2021) - [i78]Elad Hazan, Karan Singh:
Boosting for Online Convex Optimization. CoRR abs/2102.09305 (2021) - [i77]Paula Gradu, John Hallman, Daniel Suo, Alex Yu, Naman Agarwal, Udaya Ghai, Karan Singh, Cyril Zhang, Anirudha Majumdar, Elad Hazan:
Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking. CoRR abs/2102.09968 (2021) - [i76]Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh:
A Regret Minimization Approach to Iterative Learning Control. CoRR abs/2102.13478 (2021) - [i75]Xinyi Chen, Udaya Ghai, Elad Hazan, Alexandre Megretski:
Robust Online Control with Model Misspecification. CoRR abs/2107.07732 (2021) - [i74]Nataly Brukhim, Elad Hazan, Karan Singh:
A Boosting Approach to Reinforcement Learning. CoRR abs/2108.09767 (2021) - [i73]Xinyi Chen, Edgar Minasyan, Jason D. Lee, Elad Hazan:
Provable Regret Bounds for Deep Online Learning and Control. CoRR abs/2110.07807 (2021) - [i72]Daniel Suo, Cyril Zhang, Paula Gradu, Udaya Ghai, Xinyi Chen, Edgar Minasyan, Naman Agarwal, Karan Singh, Julienne LaChance, Tom Zajdel, Manuel Schottdorf, Daniel Cohen, Elad Hazan:
Machine Learning for Mechanical Ventilation Control (Extended Abstract). CoRR abs/2111.10434 (2021) - 2020
- [c90]Udaya Ghai, Elad Hazan, Yoram Singer:
Exponentiated Gradient Meets Gradient Descent. ALT 2020: 386-407 - [c89]Elad Hazan, Sham M. Kakade, Karan Singh:
The Nonstochastic Control Problem. ALT 2020: 408-421 - [c88]Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth:
The Gradient Complexity of Linear Regression. COLT 2020: 627-647 - [c87]Elad Hazan, Edgar Minasyan:
Faster Projection-free Online Learning. COLT 2020: 1877-1893 - [c86]Max Simchowitz, Karan Singh, Elad Hazan:
Improper Learning for Non-Stochastic Control. COLT 2020: 3320-3436 - [c85]Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang:
Extreme Tensoring for Low-Memory Preconditioning. ICLR 2020 - [c84]Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu:
Boosting for Control of Dynamical Systems. ICML 2020: 96-103 - [c83]Nataly Brukhim, Xinyi Chen, Elad Hazan, Shay Moran:
Online Agnostic Boosting via Regret Minimization. NeurIPS 2020 - [c82]Paula Gradu, John Hallman, Elad Hazan:
Non-Stochastic Control with Bandit Feedback. NeurIPS 2020 - [c81]Orestis Plevrakis, Elad Hazan:
Geometric Exploration for Online Control. NeurIPS 2020 - [i71]Max Simchowitz, Karan Singh, Elad Hazan:
Improper Learning for Non-Stochastic Control. CoRR abs/2001.09254 (2020) - [i70]Elad Hazan, Edgar Minasyan:
Faster Projection-free Online Learning. CoRR abs/2001.11568 (2020) - [i69]Noga Alon, Alon Gonen, Elad Hazan, Shay Moran:
Boosting Simple Learners. CoRR abs/2001.11704 (2020) - [i68]Naman Agarwal, Rohan Anil, Elad Hazan, Tomer Koren, Cyril Zhang:
Disentangling Adaptive Gradient Methods from Learning Rates. CoRR abs/2002.11803 (2020) - [i67]Nataly Brukhim, Xinyi Chen, Elad Hazan, Shay Moran:
Online Agnostic Boosting via Regret Minimization. CoRR abs/2003.01150 (2020) - [i66]Paula Gradu, Elad Hazan, Edgar Minasyan:
Adaptive Regret for Control of Time-Varying Dynamics. CoRR abs/2007.04393 (2020) - [i65]Xinyi Chen, Elad Hazan:
Black-Box Control for Linear Dynamical Systems. CoRR abs/2007.06650 (2020) - [i64]Nataly Brukhim, Elad Hazan:
Online Boosting with Bandit Feedback. CoRR abs/2007.11975 (2020) - [i63]Paula Gradu, John Hallman, Elad Hazan:
Non-Stochastic Control with Bandit Feedback. CoRR abs/2008.05523 (2020) - [i62]Orestis Plevrakis, Elad Hazan:
Geometric Exploration for Online Control. CoRR abs/2010.13178 (2020) - [i61]Udaya Ghai, David Snyder, Anirudha Majumdar, Elad Hazan:
Generating Adversarial Disturbances for Controller Verification. CoRR abs/2012.06695 (2020)
2010 – 2019
- 2019
- [c80]Brian Bullins, Elad Hazan, Adam Kalai, Roi Livni:
Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning. ALT 2019: 235-246 - [c79]Naman Agarwal, Alon Gonen, Elad Hazan:
Learning in Non-convex Games with an Optimization Oracle. COLT 2019: 18-29 - [c78]Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang:
Efficient Full-Matrix Adaptive Regularization. ICML 2019: 102-110 - [c77]Naman Agarwal, Brian Bullins, Elad Hazan, Sham M. Kakade, Karan Singh:
Online Control with Adversarial Disturbances. ICML 2019: 111-119 - [c76]Elad Hazan, Sham M. Kakade, Karan Singh, Abby Van Soest:
Provably Efficient Maximum Entropy Exploration. ICML 2019: 2681-2691 - [c75]Alon Gonen, Elad Hazan, Shay Moran:
Private Learning Implies Online Learning: An Efficient Reduction. NeurIPS 2019: 8699-8709 - [c74]Naman Agarwal, Elad Hazan, Karan Singh:
Logarithmic Regret for Online Control. NeurIPS 2019: 10175-10184 - [i60]Udaya Ghai, Elad Hazan, Yoram Singer:
Exponentiated Gradient Meets Gradient Descent. CoRR abs/1902.01903 (2019) - [i59]Xinyi Chen, Naman Agarwal, Elad Hazan, Cyril Zhang, Yi Zhang:
Extreme Tensoring for Low-Memory Preconditioning. CoRR abs/1902.04620 (2019) - [i58]Naman Agarwal, Brian Bullins, Elad Hazan, Sham M. Kakade, Karan Singh:
Online Control with Adversarial Disturbances. CoRR abs/1902.08721 (2019) - [i57]Alon Gonen, Elad Hazan, Shay Moran:
Private Learning Implies Online Learning: An Efficient Reduction. CoRR abs/1905.11311 (2019) - [i56]Naman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu:
Boosting for Dynamical Systems. CoRR abs/1906.08720 (2019) - [i55]Elad Hazan:
Lecture Notes: Optimization for Machine Learning. CoRR abs/1909.03550 (2019) - [i54]Naman Agarwal, Elad Hazan, Karan Singh:
Logarithmic Regret for Online Control. CoRR abs/1909.05062 (2019) - [i53]Elad Hazan:
Introduction to Online Convex Optimization. CoRR abs/1909.05207 (2019) - [i52]Mark Braverman, Elad Hazan, Max Simchowitz, Blake E. Woodworth:
The gradient complexity of linear regression. CoRR abs/1911.02212 (2019) - [i51]Elad Hazan, Sham M. Kakade, Karan Singh:
The Nonstochastic Control Problem. CoRR abs/1911.12178 (2019) - 2018
- [c73]Naman Agarwal, Elad Hazan:
Lower Bounds for Higher-Order Convex Optimization. COLT 2018: 774-792 - [c72]Elad Hazan, Roi Livni:
Open problem: Improper learning of mixtures of Gaussians. COLT 2018: 3399-3402 - [c71]Sanjeev Arora, Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Towards Provable Control for Unknown Linear Dynamical Systems. ICLR (Workshop) 2018 - [c70]Elad Hazan, Adam R. Klivans, Yang Yuan:
Hyperparameter optimization: a spectral approach. ICLR (Poster) 2018 - [c69]Sanjeev Arora, Nadav Cohen, Elad Hazan:
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. ICML 2018: 244-253 - [c68]Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Spectral Filtering for General Linear Dynamical Systems. NeurIPS 2018: 4639-4648 - [c67]Elad Hazan, Wei Hu, Yuanzhi Li, Zhiyuan Li:
Online Improper Learning with an Approximation Oracle. NeurIPS 2018: 5657-5665 - [c66]Scott Aaronson, Xinyi Chen, Elad Hazan, Satyen Kale, Ashwin Nayak:
Online Learning of Quantum States. NeurIPS 2018: 8976-8986 - [i50]Elad Hazan, Holden Lee, Karan Singh, Cyril Zhang, Yi Zhang:
Spectral Filtering for General Linear Dynamical Systems. CoRR abs/1802.03981 (2018) - [i49]Sanjeev Arora, Nadav Cohen, Elad Hazan:
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. CoRR abs/1802.06509 (2018) - [i48]Scott Aaronson, Xinyi Chen, Elad Hazan, Ashwin Nayak:
Online Learning of Quantum States. CoRR abs/1802.09025 (2018) - [i47]Elad Hazan, Wei Hu, Yuanzhi Li, Zhiyuan Li:
Online Improper Learning with an Approximation Oracle. CoRR abs/1804.07837 (2018) - [i46]Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang, Yi Zhang:
The Case for Full-Matrix Adaptive Regularization. CoRR abs/1806.02958 (2018) - [i45]Alon Gonen, Elad Hazan:
Learning in Non-convex Games with an Optimization Oracle. CoRR abs/1810.07362 (2018) - [i44]Elad Hazan, Sham M. Kakade, Karan Singh, Abby Van Soest:
Provably Efficient Maximum Entropy Exploration. CoRR abs/1812.02690 (2018) - 2017
- [j23]Naman Agarwal, Brian Bullins, Elad Hazan:
Second-Order Stochastic Optimization for Machine Learning in Linear Time. J. Mach. Learn. Res. 18: 116:1-116:40 (2017) - [j22]Elad Hazan, Satyen Kale, Shai Shalev-Shwartz:
Near-Optimal Algorithms for Online Matrix Prediction. SIAM J. Comput. 46(2): 744-773 (2017) - [c65]Elad Hazan, Karan Singh, Cyril Zhang:
Efficient Regret Minimization in Non-Convex Games. ICML 2017: 1433-1441 - [c64]Zeyuan Allen-Zhu, Elad Hazan, Wei Hu, Yuanzhi Li:
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. NIPS 2017: 6191-6200 - [c63]Elad Hazan, Karan Singh, Cyril Zhang:
Learning Linear Dynamical Systems via Spectral Filtering. NIPS 2017: 6702-6712 - [c62]Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma:
Finding approximate local minima faster than gradient descent. STOC 2017: 1195-1199 - [i43]Elad Hazan, Adam R. Klivans, Yang Yuan:
Hyperparameter Optimization: A Spectral Approach. CoRR abs/1706.00764 (2017) - [i42]Elad Hazan, Karan Singh, Cyril Zhang:
Efficient Regret Minimization in Non-Convex Games. CoRR abs/1708.00075 (2017) - [i41]Zeyuan Allen-Zhu, Elad Hazan, Wei Hu, Yuanzhi Li:
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. CoRR abs/1708.02105 (2017) - [i40]Naman Agarwal, Elad Hazan:
Lower Bounds for Higher-Order Convex Optimization. CoRR abs/1710.10329 (2017) - [i39]Elad Hazan, Karan Singh, Cyril Zhang:
Learning Linear Dynamical Systems via Spectral Filtering. CoRR abs/1711.00946 (2017) - 2016
- [j21]Elad Hazan:
Introduction to Online Convex Optimization. Found. Trends Optim. 2(3-4): 157-325 (2016) - [j20]Elad Hazan, Zohar S. Karnin:
Volumetric Spanners: An Efficient Exploration Basis for Learning. J. Mach. Learn. Res. 17: 119:1-119:34 (2016) - [j19]Elad Hazan, Satyen Kale, Manfred K. Warmuth:
Learning rotations with little regret. Mach. Learn. 104(1): 129-148 (2016) - [j18]Dan Garber, Elad Hazan:
Sublinear time algorithms for approximate semidefinite programming. Math. Program. 158(1-2): 329-361 (2016) - [j17]Elad Hazan, Tomer Koren:
A linear-time algorithm for trust region problems. Math. Program. 158(1-2): 363-381 (2016) - [j16]Dan Garber, Elad Hazan:
A Linearly Convergent Variant of the Conditional Gradient Algorithm under Strong Convexity, with Applications to Online and Stochastic Optimization. SIAM J. Optim. 26(3): 1493-1528 (2016) - [c61]Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour:
Online Learning with Low Rank Experts. COLT 2016: 1096-1114 - [c60]Zeyuan Allen Zhu, Elad Hazan:
Variance Reduction for Faster Non-Convex Optimization. ICML 2016: 699-707 - [c59]Elad Hazan, Haipeng Luo:
Variance-Reduced and Projection-Free Stochastic Optimization. ICML 2016: 1263-1271 - [c58]Elad Hazan, Kfir Yehuda Levy, Shai Shalev-Shwartz:
On Graduated Optimization for Stochastic Non-Convex Problems. ICML 2016: 1833-1841 - [c57]Jacob D. Abernethy, Elad Hazan:
Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier. ICML 2016: 2520-2528 - [c56]Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford:
Faster Eigenvector Computation via Shift-and-Invert Preconditioning. ICML 2016: 2626-2634 - [c55]Zeyuan Allen Zhu, Elad Hazan:
Optimal Black-Box Reductions Between Optimization Objectives. NIPS 2016: 1606-1614 - [c54]Elad Hazan, Tengyu Ma:
A Non-generative Framework and Convex Relaxations for Unsupervised Learning. NIPS 2016: 3306-3314 - [c53]Brian Bullins, Elad Hazan, Tomer Koren:
The Limits of Learning with Missing Data. NIPS 2016: 3495-3503 - [c52]Elad Hazan, Tomer Koren:
The computational power of optimization in online learning. STOC 2016: 128-141 - [i38]Elad Hazan, Haipeng Luo:
Variance-Reduced and Projection-Free Stochastic Optimization. CoRR abs/1602.02101 (2016) - [i37]Naman Agarwal, Brian Bullins, Elad Hazan:
Second Order Stochastic Optimization in Linear Time. CoRR abs/1602.03943 (2016) - [i36]Elad Hazan, Yuanzhi Li:
An optimal algorithm for bandit convex optimization. CoRR abs/1603.04350 (2016) - [i35]Zeyuan Allen Zhu, Elad Hazan:
Optimal Black-Box Reductions Between Optimization Objectives. CoRR abs/1603.05642 (2016) - [i34]Zeyuan Allen Zhu, Elad Hazan:
Variance Reduction for Faster Non-Convex Optimization. CoRR abs/1603.05643 (2016) - [i33]Elad Hazan, Tomer Koren, Roi Livni, Yishay Mansour:
Online Learning with Low Rank Experts. CoRR abs/1603.06352 (2016) - [i32]Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford:
Faster Eigenvector Computation via Shift-and-Invert Preconditioning. CoRR abs/1605.08754 (2016) - [i31]Elad Hazan, Tengyu Ma:
A Non-generative Framework and Convex Relaxations for Unsupervised Learning. CoRR abs/1610.01132 (2016) - [i30]Naman Agarwal, Zeyuan Allen Zhu, Brian Bullins, Elad Hazan, Tengyu Ma:
Finding Approximate Local Minima for Nonconvex Optimization in Linear Time. CoRR abs/1611.01146 (2016) - 2015
- [j15]Aharon Ben-Tal, Elad Hazan, Tomer Koren, Shie Mannor:
Oracle-Based Robust Optimization via Online Learning. Oper. Res. 63(3): 628-638 (2015) - [c51]Peter Grünwald, Elad Hazan:
Conference on Learning Theory 2015: Preface. COLT 2015: 1-3 - [c50]Elad Hazan, Roi Livni, Yishay Mansour:
Classification with Low Rank and Missing Data. ICML 2015: 257-266 - [c49]Dan Garber, Elad Hazan:
Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets. ICML 2015: 541-549 - [c48]Dan Garber, Elad Hazan, Tengyu Ma:
Online Learning of Eigenvectors. ICML 2015: 560-568 - [c47]Oren Anava, Elad Hazan, Assaf Zeevi:
Online Time Series Prediction with Missing Data. ICML 2015: 2191-2199 - [c46]Oren Anava, Elad Hazan, Shie Mannor:
Online Learning for Adversaries with Memory: Price of Past Mistakes. NIPS 2015: 784-792 - [c45]Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz:
Beyond Convexity: Stochastic Quasi-Convex Optimization. NIPS 2015: 1594-1602 - [c44]Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo:
Online Gradient Boosting. NIPS 2015: 2458-2466 - [e1]Peter Grünwald, Elad Hazan, Satyen Kale:
Proceedings of The 28th Conference on Learning Theory, COLT 2015, Paris, France, July 3-6, 2015. JMLR Workshop and Conference Proceedings 40, JMLR.org 2015 [contents] - [i29]Elad Hazan, Roi Livni, Yishay Mansour:
Classification with Low Rank and Missing Data. CoRR abs/1501.03273 (2015) - [i28]Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz:
On Graduated Optimization for Stochastic Non-Convex Problems. CoRR abs/1503.03712 (2015) - [i27]Elad Hazan, Tomer Koren:
The Computational Power of Optimization in Online Learning. CoRR abs/1504.02089 (2015) - [i26]Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo:
Online Gradient Boosting. CoRR abs/1506.04820 (2015) - [i25]Elad Hazan, Kfir Y. Levy, Shai Shalev-Shwartz:
Beyond Convexity: Stochastic Quasi-Convex Optimization. CoRR abs/1507.02030 (2015) - [i24]Jacob D. Abernethy, Elad Hazan:
Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier. CoRR abs/1507.02528 (2015) - [i23]Dan Garber, Elad Hazan:
Fast and Simple PCA via Convex Optimization. CoRR abs/1509.05647 (2015) - 2014
- [j14]Elad Hazan, Satyen Kale:
Beyond the regret minimization barrier: optimal algorithms for stochastic strongly-convex optimization. J. Mach. Learn. Res. 15(1): 2489-2512 (2014) - [c43]