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2020 – today
- 2024
[c115]Arun Sai Suggala, Y. Jennifer Sun, Praneeth Netrapalli, Elad Hazan:
Second Order Methods for Bandit Optimization and Control. COLT 2024: 4691-4763- [c114]Xinyi Chen, Elad Hazan:
Open Problem: Black-Box Reductions and Adaptive Gradient Methods for Nonconvex Optimization. COLT 2024: 5317-5324 - [c113]Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan:
Adaptive Regret for Bandits Made Possible: Two Queries Suffice. ICLR 2024 - [i104]Wenhan Xia, Chengwei Qin, Elad Hazan:
Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning. CoRR abs/2401.04151 (2024) - [i103]Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David P. Woodruff, Elad Hazan:
Adaptive Regret for Bandits Made Possible: Two Queries Suffice. CoRR abs/2401.09278 (2024) - [i102]Arun Sai Suggala, Y. Jennifer Sun, Praneeth Netrapalli, Elad Hazan:
Second Order Methods for Bandit Optimization and Control. CoRR abs/2402.08929 (2024) - [i101]Noah Golowich, Elad Hazan, Zhou Lu, Dhruv Rohatgi, Y. Jennifer Sun:
Online Control in Population Dynamics. CoRR abs/2406.01799 (2024) - [i100]Y. Isabel Liu, Windsor Nguyen, Yagiz Devre, Evan Dogariu, Anirudha Majumdar, Elad Hazan:
Flash STU: Fast Spectral Transform Units. CoRR abs/2409.10489 (2024) - [i99]Naman Agarwal, Xinyi Chen, Evan Dogariu, Vladimir Feinberg, Daniel Suo, Peter L. Bartlett, Elad Hazan:
FutureFill: Fast Generation from Convolutional Sequence Models. CoRR abs/2410.03766 (2024) - [i98]Annie Marsden, Evan Dogariu, Naman Agarwal, Xinyi Chen, Daniel Suo, Elad Hazan:
Provable Length Generalization in Sequence Prediction via Spectral Filtering. CoRR abs/2411.01035 (2024) - 2023
- [j24]Noga Alon, Alon Gonen, Elad Hazan, Shay Moran:
Boosting Simple Learners. TheoretiCS 2 (2023) - [c112]Zhou Lu, Nataly Brukhim, Paula Gradu, Elad Hazan:
Projection-free Adaptive Regret with Membership Oracles. ALT 2023: 1055-1073 - [c111]David Snyder, Meghan Booker, Nathaniel Simon, Wenhan Xia, Daniel Suo, Elad Hazan, Anirudha Majumdar:
Online Learning for Obstacle Avoidance. CoRL 2023: 2926-2954 - [c110]Paula Gradu, Elad Hazan, Edgar Minasyan:
Adaptive Regret for Control of Time-Varying Dynamics. L4DC 2023: 560-572 - [c109]Xinyi Chen, Edgar Minasyan, Jason D. Lee, Elad Hazan:
Regret Guarantees for Online Deep Control. L4DC 2023: 1032-1045 - [c108]Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan:
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret. L4DC 2023: 1345-1356 - [c107]Xinyi Chen, Elad Hazan:
Online Control for Meta-optimization. NeurIPS 2023 - [c106]Vladimir Feinberg, Xinyi Chen, Y. Jennifer Sun, Rohan Anil, Elad Hazan:
Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions. NeurIPS 2023 - [c105]Udaya Ghai, Arushi Gupta, Wenhan Xia, Karan Singh, Elad Hazan:
Online Nonstochastic Model-Free Reinforcement Learning. NeurIPS 2023 - [c104]Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun:
Partial Matrix Completion. NeurIPS 2023 - [c103]Y. Jennifer Sun, Stephen H. Newman, Elad Hazan:
Optimal Rates for Bandit Nonstochastic Control. NeurIPS 2023 - [i97]Xinyi Chen, Elad Hazan:
A Nonstochastic Control Approach to Optimization. CoRR abs/2301.07902 (2023) - [i96]Vladimir Feinberg, Xinyi Chen, Y. Jennifer Sun, Rohan Anil, Elad Hazan:
Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions. CoRR abs/2302.03764 (2023) - [i95]Y. Jennifer Sun, Stephen H. Newman, Elad Hazan:
Optimal Rates for Bandit Nonstochastic Control. CoRR abs/2305.15352 (2023) - [i94]Udaya Ghai, Arushi Gupta, Wenhan Xia, Karan Singh, Elad Hazan:
Online Nonstochastic Model-Free Reinforcement Learning. CoRR abs/2305.17552 (2023) - [i93]David Snyder, Meghan Booker, Nathaniel Simon, Wenhan Xia, Daniel Suo, Elad Hazan, Anirudha Majumdar:
Online Learning for Obstacle Avoidance. CoRR abs/2306.08776 (2023) - [i92]Elad Hazan, Nimrod Megiddo:
An Efficient Interior-Point Method for Online Convex Optimization. CoRR abs/2307.11668 (2023) - [i91]Xinyi Chen, Angelica Chen, Dean P. Foster, Elad Hazan:
AI safety by debate via regret minimization. CoRR abs/2312.04792 (2023) - [i90]Naman Agarwal, Daniel Suo, Xinyi Chen, Elad Hazan:
Spectral State Space Models. CoRR abs/2312.06837 (2023) - 2022
- [c102]Udaya Ghai, Udari Madhushani, Naomi Ehrich Leonard, Elad Hazan:
A Regret Minimization Approach to Multi-Agent Control. ICML 2022: 7422-7434 - [c101]Udaya Ghai, Xinyi Chen, Elad Hazan, Alexandre Megretski:
Robust Online Control with Model Misspecification. L4DC 2022: 1163-1175 - [c100]Nataly Brukhim, Elad Hazan, Karan Singh:
A Boosting Approach to Reinforcement Learning. NeurIPS 2022 - [c99]Udaya Ghai, Zhou Lu, Elad Hazan:
Non-convex online learning via algorithmic equivalence. NeurIPS 2022 - [i89]Udaya Ghai, Udari Madhushani, Naomi Ehrich Leonard, Elad Hazan:
A Regret Minimization Approach to Multi-Agent Contro. CoRR abs/2201.13288 (2022) - [i88]Edgar Minasyan, Paula Gradu, Max Simchowitz, Elad Hazan:
Online Control of Unknown Time-Varying Dynamical Systems. CoRR abs/2202.07890 (2022) - [i87]Zhou Lu
, Wenhan Xia, Sanjeev Arora, Elad Hazan:
Adaptive Gradient Methods with Local Guarantees. CoRR abs/2203.01400 (2022) - [i86]Udaya Ghai, Zhou Lu, Elad Hazan:
Non-convex online learning via algorithmic equivalence. CoRR abs/2205.15235 (2022) - [i85]Xinyi Chen, Elad Hazan, Tongyang Li, Zhou Lu, Xinzhao Wang, Rui Yang:
Adaptive Online Learning of Quantum States. CoRR abs/2206.00220 (2022) - [i84]Zhou Lu, Elad Hazan:
Efficient Adaptive Regret Minimization. CoRR abs/2207.00646 (2022) - [i83]Varun Kanade, Elad Hazan, Adam Tauman Kalai:
Partial Matrix Completion. CoRR abs/2208.12063 (2022) - [i82]Elad Hazan, Karan Singh:
Introduction to Online Nonstochastic Control. CoRR abs/2211.09619 (2022) - [i81]Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan:
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret. CoRR abs/2211.11219 (2022) - [i80]Zhou Lu, Nataly Brukhim, Paula Gradu, Elad Hazan:
Projection-free Adaptive Regret with Membership Oracles. CoRR abs/2211.12638 (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 J. 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 J. 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]Elad Hazan, Tomer Koren, Kfir Y. Levy:
Logistic Regression: Tight Bounds for Stochastic and Online Optimization. COLT 2014: 197-209 - [c42]Elad Hazan, Zohar Shay Karnin, Raghu Meka:
Volumetric Spanners: an Efficient Exploration Basis for Learning. COLT 2014: 408-422 - [c41]Zohar Shay Karnin, Elad Hazan:
Hard-Margin Active Linear Regression. ICML 2014: 883-891 - [c40]Elad Hazan, Kfir Y. Levy:
Bandit Convex Optimization: Towards Tight Bounds. NIPS 2014: 784-792 - [c39]Ofer Dekel, Elad Hazan, Tomer Koren:
The Blinded Bandit: Learning with Adaptive Feedback. NIPS 2014: 1610-1618 - [i22]Elad Hazan, Tomer Koren:
A Linear-Time Algorithm for Trust Region Problems. CoRR abs/1401.6757 (2014) - [i21]Aharon Ben-Tal, Elad Hazan, Tomer Koren, Shie Mannor:
Oracle-Based Robust Optimization via Online Learning. CoRR abs/1402.6361 (2014) - [i20]Elad Hazan, Tomer Koren, Kfir Y. Levy:
Logistic Regression: Tight Bounds for Stochastic and Online Optimization. CoRR abs/1405.3843 (2014) - [i19]Dan Garber, Elad Hazan:
Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets. CoRR abs/1406.1305 (2014) - 2013
- [j13]Dan Garber, Elad Hazan:
Adaptive Universal Linear Filtering. IEEE Trans. Signal Process. 61(7): 1595-1604 (2013) - [c38]Oren Anava, Elad Hazan, Shie Mannor, Ohad Shamir:
Online Learning for Time Series Prediction. COLT 2013: 172-184 - [c37]Dan Garber, Elad Hazan:
Playing Non-linear Games with Linear Oracles. FOCS 2013: 420-428 - [c36]Ofer Dekel, Elad Hazan:
Better Rates for Any Adversarial Deterministic MDP. ICML (3) 2013: 675-683 - [i18]Dan Garber, Elad Hazan:
A Polynomial Time Conditional Gradient Algorithm with Applications to Online and Stochastic Optimization. CoRR abs/1301.4666 (2013) - [i17]Oren Anava, Elad Hazan, Shie Mannor, Ohad Shamir:
Online Learning for Time Series Prediction. CoRR abs/1302.6927 (2013) - [i16]Oren Anava, Elad Hazan, Shie Mannor:
Online Learning for Loss Functions with Memory and Applications to Statistical Arbitrage. CoRR abs/1302.6937 (2013) - [i15]Elad Hazan, Zohar Shay Karnin, Raghu Meka:
Volumetric Spanners and their Applications to Machine Learning. CoRR abs/1312.6214 (2013) - 2012
- [j12]Kenneth L. Clarkson, Elad Hazan, David P. Woodruff:
Sublinear optimization for machine learning. J. ACM 59(5): 23:1-23:49 (2012) - [j11]Elad Hazan, Satyen Kale:
Online submodular minimization. J. Mach. Learn. Res. 13: 2903-2922 (2012) - [j10]Jacob D. Abernethy, Elad Hazan, Alexander Rakhlin:
Interior-Point Methods for Full-Information and Bandit Online Learning. IEEE Trans. Inf. Theory 58(7): 4164-4175 (2012) - [j9]Sanjeev Arora, Elad Hazan, Satyen Kale:
The Multiplicative Weights Update Method: a Meta-Algorithm and Applications. Theory Comput. 8(1): 121-164 (2012) - [c35]Elad Hazan, Satyen Kale:
Projection-free Online Learning. ICML 2012 - [c34]Elad Hazan, Tomer Koren:
Linear Regression with Limited Observation. ICML 2012 - [c33]Elad Hazan, Zohar Shay Karnin:
A Polylog Pivot Steps Simplex Algorithm for Classification. NIPS 2012: 638-646 - [c32]Elad Hazan, Sham M. Kakade:
(weak) Calibration is Computationally Hard. COLT 2012: 3.1-3.10 - [c31]Elad Hazan, Satyen Kale, Shai Shalev-Shwartz:
Near-Optimal Algorithms for Online Matrix Prediction. COLT 2012: 38.1-38.13 - [i14]Elad Hazan, Sham M. Kakade:
(weak) Calibration is Computationally Hard. CoRR abs/1202.4478 (2012) - [i13]Elad Hazan, Satyen Kale, Shai Shalev-Shwartz:
Near-Optimal Algorithms for Online Matrix Prediction. CoRR abs/1204.0136 (2012) - [i12]Elad Hazan, Satyen Kale:
Projection-free Online Learning. CoRR abs/1206.4657 (2012) - [i11]Elad Hazan, Tomer Koren:
Linear Regression with Limited Observation. CoRR abs/1206.4678 (2012) - [i10]Dan Garber, Elad Hazan:
Almost Optimal Sublinear Time Algorithm for Semidefinite Programming. CoRR abs/1208.5211 (2012) - 2011
- [j8]Elad Hazan, Satyen Kale:
Better Algorithms for Benign Bandits. J. Mach. Learn. Res. 12: 1287-1311 (2011) - [j7]John C. Duchi, Elad Hazan, Yoram Singer:
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. J. Mach. Learn. Res. 12: 2121-2159 (2011) - [j6]Elad Hazan, Robert Krauthgamer:
How Hard Is It to Approximate the Best Nash Equilibrium? SIAM J. Comput. 40(1): 79-91 (2011) - [c30]Elad Hazan, Satyen Kale:
Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction. NIPS 2011: 891-899 - [c29]Dan Garber, Elad Hazan:
Approximating Semidefinite Programs in Sublinear Time. NIPS 2011: 1080-1088 - [c28]Elad Hazan, Tomer Koren, Nati Srebro:
Beating SGD: Learning SVMs in Sublinear Time. NIPS 2011: 1233-1241 - [c27]Jacob D. Abernethy, Peter L. Bartlett, Elad Hazan:
Blackwell Approachability and No-Regret Learning are Equivalent. COLT 2011: 27-46 - [c26]Elad Hazan, Satyen Kale:
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization. COLT 2011: 421-436 - [c25]Elad Hazan, Satyen Kale:
A simple multi-armed bandit algorithm with optimal variation-bounded regret. COLT 2011: 817-820 - [i9]Elad Hazan, Tomer Koren:
Optimal Algorithms for Ridge and Lasso Regression with Partially Observed Attributes. CoRR abs/1108.4559 (2011) - [i8]Dan Garber, Elad Hazan:
Universal MMSE Filtering With Logarithmic Adaptive Regret. CoRR abs/1111.1136 (2011) - 2010
- [j5]Elad Hazan, Satyen Kale:
Extracting certainty from uncertainty: regret bounded by variation in costs. Mach. Learn. 80(2-3): 165-188 (2010) - [j4]Sanjeev Arora, Elad Hazan, Satyen Kale:
O(sqrt(log(n)) Approximation to SPARSEST CUT in Õ(n2) Time. SIAM J. Comput. 39(5): 1748-1771 (2010) - [c24]Elad Hazan, Satyen Kale, Manfred K. Warmuth:
Learning Rotations with Little Regret. COLT 2010: 144-154 - [c23]John C. Duchi, Elad Hazan, Yoram Singer:
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. COLT 2010: 257-269 - [c22]Elad Hazan, Satyen Kale, Manfred K. Warmuth:
On-line Variance Minimization in O(n2) per Trial? COLT 2010: 314-315 - [c21]Kenneth L. Clarkson, Elad Hazan, David P. Woodruff:
Sublinear Optimization for Machine Learning. FOCS 2010: 449-457 - [i7]Kenneth L. Clarkson, Elad Hazan, David P. Woodruff:
Sublinear Optimization for Machine Learning. CoRR abs/1010.4408 (2010) - [i6]Jacob D. Abernethy, Peter L. Bartlett, Elad Hazan:
Blackwell Approachability and Low-Regret Learning are Equivalent. CoRR abs/1011.1936 (2010)
2000 – 2009
- 2009
- [c20]Elad Hazan, C. Seshadhri:
Efficient learning algorithms for changing environments. ICML 2009: 393-400 - [c19]Elad Hazan, Satyen Kale:
Beyond Convexity: Online Submodular Minimization. NIPS 2009: 700-708 - [c18]Elad Hazan, Satyen Kale:
On Stochastic and Worst-case Models for Investing. NIPS 2009: 709-717 - [c17]Elad Hazan, Satyen Kale:
Better algorithms for benign bandits. SODA 2009: 38-47 - [c16]Elad Hazan, Robert Krauthgamer:
How hard is it to approximate the best Nash equilibrium? SODA 2009: 720-727 - 2008
- [c15]Elad Hazan, Satyen Kale:
Extracting Certainty from Uncertainty: Regret Bounded by Variation in Costs. COLT 2008: 57-68 - [c14]Jacob D. Abernethy, Elad Hazan, Alexander Rakhlin:
Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization. COLT 2008: 263-274 - [c13]Elad Hazan:
Sparse Approximate Solutions to Semidefinite Programs. LATIN 2008: 306-316 - 2007
- [j3]Elad Hazan, Amit Agarwal, Satyen Kale:
Logarithmic regret algorithms for online convex optimization. Mach. Learn. 69(2-3): 169-192 (2007) - [c12]Elad Hazan, Nimrod Megiddo:
Online Learning with Prior Knowledge. COLT 2007: 499-513 - [c11]Peter L. Bartlett, Elad Hazan, Alexander Rakhlin:
Adaptive Online Gradient Descent. NIPS 2007: 65-72 - [c10]Elad Hazan, Satyen Kale:
Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria. NIPS 2007: 625-632 - [i5]Elad Hazan, C. Seshadhri:
Adaptive Algorithms for Online Decision Problems. Electron. Colloquium Comput. Complex. TR07 (2007) - 2006
- [j2]Elad Hazan, Shmuel Safra, Oded Schwartz:
On the complexity of approximating k-set packing. Comput. Complex. 15(1): 20-39 (2006) - [j1]Eran Halperin, Elad Hazan:
HAPLOFREQ-Estimating Haplotype Frequencies Efficiently. J. Comput. Biol. 13(2): 481-500 (2006) - [c9]Sanjeev Arora, Elad Hazan, Satyen Kale:
A Fast Random Sampling Algorithm for Sparsifying Matrices. APPROX-RANDOM 2006: 272-279 - [c8]Elad Hazan, Adam Kalai, Satyen Kale, Amit Agarwal:
Logarithmic Regret Algorithms for Online Convex Optimization. COLT 2006: 499-513 - [c7]Amit Agarwal, Elad Hazan, Satyen Kale, Robert E. Schapire:
Algorithms for portfolio management based on the Newton method. ICML 2006: 9-16 - [i4]Elad Hazan:
Approximate Convex Optimization by Online Game Playing. CoRR abs/cs/0610119 (2006) - [i3]Amit Agarwal, Elad Hazan:
Efficient Algorithms for Online Game Playing and Universal Portfolio Management. Electron. Colloquium Comput. Complex. TR06 (2006) - 2005
- [c6]Sanjeev Arora, Eli Berger, Elad Hazan, Guy Kindler, Muli Safra:
On Non-Approximability for Quadratic Programs. FOCS 2005: 206-215 - [c5]Sanjeev Arora, Elad Hazan, Satyen Kale:
Fast Algorithms for Approximate Semide.nite Programming using the Multiplicative Weights Update Method. FOCS 2005: 339-348 - [c4]Satyen Kale, Elad Hazan, Fengyun Cao, Jaswinder Pal Singh:
Analysis and Algorithms for Content-Based Event Matching. ICDCS Workshops 2005: 363-369 - [c3]Eran Halperin, Elad Hazan:
HAPLOFREQ - Estimating Haplotype Frequencies E.ciently. RECOMB 2005: 553-568 - [i2]Sanjeev Arora, Eli Berger, Elad Hazan, Guy Kindler, Muli Safra:
On Non-Approximability for Quadratic Programs. Electron. Colloquium Comput. Complex. TR05 (2005) - 2004
- [c2]Sanjeev Arora, Elad Hazan, Satyen Kale:
0(sqrt (log n)) Approximation to SPARSEST CUT in Õ(n2) Time. FOCS 2004: 238-247 - 2003
- [c1]Elad Hazan, Shmuel Safra, Oded Schwartz:
On the Complexity of Approximating k-Dimensional Matching. RANDOM-APPROX 2003: 83-97 - [i1]Elad Hazan, Shmuel Safra, Oded Schwartz:
On the Hardness of Approximating k-Dimensional Matching. Electron. Colloquium Comput. Complex. TR03 (2003)
Coauthor Index
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