On the Complexity of Approximating k-Dimensional Matching. - Elad Hazan; Shmuel Safra; Oded Schwartz (RANDOM-APPROX, 2003)

On the Hardness of Approximating k-Dimensional Matching - Elad Hazan; Shmuel Safra; Oded Schwartz (Electron. Colloquium Comput. Complex., 2003)

0(sqrt (log n)) Approximation to SPARSEST CUT in Õ(n2) Time. - Sanjeev Arora; Elad Hazan; Satyen Kale (FOCS, 2004)

Fast Algorithms for Approximate Semide.nite Programming using the Multiplicative Weights Update Method. - Sanjeev Arora; Elad Hazan; Satyen Kale (FOCS, 2005)

Analysis and Algorithms for Content-Based Event Matching. - Satyen Kale; Elad Hazan; Fengyun Cao; Jaswinder Pal Singh (ICDCS Workshops, 2005)

HAPLOFREQ - Estimating Haplotype Frequencies E.ciently. - Eran Halperin; Elad Hazan (RECOMB, 2005)

On Non-Approximability for Quadratic Programs - Sanjeev Arora; Eli Berger; Elad Hazan; Guy Kindler; Muli Safra (Electron. Colloquium Comput. Complex., 2005)

A Fast Random Sampling Algorithm for Sparsifying Matrices. - Sanjeev Arora; Elad Hazan; Satyen Kale (APPROX-RANDOM, 2006)

Logarithmic Regret Algorithms for Online Convex Optimization. - Elad Hazan; Adam Kalai; Satyen Kale; Amit Agarwal 008 (COLT, 2006)

Algorithms for portfolio management based on the Newton method. - Amit Agarwal 008; Elad Hazan; Satyen Kale; Robert E. Schapire (ICML, 2006)

On the complexity of approximating k-set packing. - Elad Hazan; Shmuel Safra; Oded Schwartz (Comput. Complex., 2006)

Approximate Convex Optimization by Online Game Playing - Elad Hazan (CoRR, 2006)

Efficient Algorithms for Online Game Playing and Universal Portfolio Management. - Amit Agarwal 008; Elad Hazan (Electron. Colloquium Comput. Complex., 2006)

HAPLOFREQ-Estimating Haplotype Frequencies Efficiently. - Eran Halperin; Elad Hazan (J. Comput. Biol., 2006)

Online Learning with Prior Knowledge. - Elad Hazan; Nimrod Megiddo (COLT, 2007)

Adaptive Online Gradient Descent. - Peter L. Bartlett; Elad Hazan; Alexander Rakhlin (NIPS, 2007)

Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria. - Elad Hazan; Satyen Kale (NIPS, 2007)

Adaptive Algorithms for Online Decision Problems. - Elad Hazan; C. Seshadhri 001 (Electron. Colloquium Comput. Complex., 2007)

Logarithmic regret algorithms for online convex optimization. - Elad Hazan; Amit Agarwal 008; Satyen Kale (Mach. Learn., 2007)

Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization. - Jacob D. Abernethy; Elad Hazan; Alexander Rakhlin (COLT, 2008)

Sparse Approximate Solutions to Semidefinite Programs. - Elad Hazan (LATIN, 2008)

Efficient learning algorithms for changing environments. - Elad Hazan; C. Seshadhri 001 (ICML, 2009)

Beyond Convexity: Online Submodular Minimization. - Elad Hazan; Satyen Kale (NIPS, 2009)

On Stochastic and Worst-case Models for Investing. - Elad Hazan; Satyen Kale (NIPS, 2009)

On-line Variance Minimization in O(n2) per Trial? - Elad Hazan; Satyen Kale; Manfred K. Warmuth (COLT, 2010)

Blackwell Approachability and Low-Regret Learning are Equivalent - Jacob D. Abernethy; Peter L. Bartlett; Elad Hazan (CoRR, 2010)

Extracting certainty from uncertainty: regret bounded by variation in costs. - Elad Hazan; Satyen Kale (Mach. Learn., 2010)

O(sqrt(log(n)) Approximation to SPARSEST CUT in Õ(n2) Time. - Sanjeev Arora; Elad Hazan; Satyen Kale (SIAM J. Comput., 2010)

Approximating Semidefinite Programs in Sublinear Time. - Dan Garber; Elad Hazan (NIPS, 2011)

Newtron: an Efficient Bandit algorithm for Online Multiclass Prediction. - Elad Hazan; Satyen Kale (NIPS, 2011)

Beating SGD: Learning SVMs in Sublinear Time. - Elad Hazan; Tomer Koren; Nati Srebro (NIPS, 2011)

Optimal Algorithms for Ridge and Lasso Regression with Partially Observed Attributes - Elad Hazan; Tomer Koren (CoRR, 2011)

Universal MMSE Filtering With Logarithmic Adaptive Regret - Dan Garber; Elad Hazan (CoRR, 2011)

Blackwell Approachability and No-Regret Learning are Equivalent. - Jacob D. Abernethy; Peter L. Bartlett; Elad Hazan (COLT, 2011)

Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. - John C. Duchi; Elad Hazan; Yoram Singer (J. Mach. Learn. Res., 2011)

Better Algorithms for Benign Bandits. - Elad Hazan; Satyen Kale (J. Mach. Learn. Res., 2011)

Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization. - Elad Hazan; Satyen Kale (COLT, 2011)

A simple multi-armed bandit algorithm with optimal variation-bounded regret. - Elad Hazan; Satyen Kale (COLT, 2011)

How Hard Is It to Approximate the Best Nash Equilibrium? - Elad Hazan; Robert Krauthgamer (SIAM J. Comput., 2011)

Projection-free Online Learning. - Elad Hazan; Satyen Kale (ICML, 2012)

Linear Regression with Limited Observation. - Elad Hazan; Tomer Koren (ICML, 2012)

A Polylog Pivot Steps Simplex Algorithm for Classification. - Elad Hazan; Zohar Shay Karnin (NIPS, 2012)

Almost Optimal Sublinear Time Algorithm for Semidefinite Programming - Dan Garber; Elad Hazan (CoRR, 2012)

Sublinear optimization for machine learning. - Kenneth L. Clarkson; Elad Hazan; David P. Woodruff (J. ACM, 2012)

(weak) Calibration is Computationally Hard. - Elad Hazan; Sham M. Kakade (COLT, 2012)

Online submodular minimization. - Elad Hazan; Satyen Kale (J. Mach. Learn. Res., 2012)

Interior-Point Methods for Full-Information and Bandit Online Learning. - Jacob D. Abernethy; Elad Hazan; Alexander Rakhlin (IEEE Trans. Inf. Theory, 2012)

The Multiplicative Weights Update Method: a Meta-Algorithm and Applications. - Sanjeev Arora; Elad Hazan; Satyen Kale (Theory Comput., 2012)

Online Learning for Time Series Prediction. - Oren Anava; Elad Hazan; Shie Mannor; Ohad Shamir (COLT, 2013)

Playing Non-linear Games with Linear Oracles. - Dan Garber; Elad Hazan (FOCS, 2013)

Better Rates for Any Adversarial Deterministic MDP. - Ofer Dekel; Elad Hazan (ICML (3), 2013)

Volumetric Spanners and their Applications to Machine Learning. - Elad Hazan; Zohar Shay Karnin; Raghu Meka (CoRR, 2013)

A Polynomial Time Conditional Gradient Algorithm with Applications to Online and Stochastic Optimization - Dan Garber; Elad Hazan (CoRR, 2013)

Online Learning for Loss Functions with Memory and Applications to Statistical Arbitrage - Oren Anava; Elad Hazan; Shie Mannor (CoRR, 2013)

Adaptive Universal Linear Filtering. - Dan Garber; Elad Hazan (IEEE Trans. Signal Process., 2013)

Logistic Regression: Tight Bounds for Stochastic and Online Optimization. - Elad Hazan; Tomer Koren; Kfir Y. Levy (COLT, 2014)

Volumetric Spanners: an Efficient Exploration Basis for Learning. - Elad Hazan; Zohar Shay Karnin; Raghu Meka (COLT, 2014)

Hard-Margin Active Linear Regression. - Zohar Shay Karnin; Elad Hazan (ICML, 2014)

The Blinded Bandit: Learning with Adaptive Feedback. - Ofer Dekel; Elad Hazan; Tomer Koren (NIPS, 2014)

Bandit Convex Optimization: Towards Tight Bounds. - Elad Hazan; Kfir Y. Levy (NIPS, 2014)

Beyond the regret minimization barrier: optimal algorithms for stochastic strongly-convex optimization. - Elad Hazan; Satyen Kale (J. Mach. Learn. Res., 2014)

Conference on Learning Theory 2015: Preface. - Peter Grünwald; Elad Hazan (COLT, 2015)

Online Time Series Prediction with Missing Data. - Oren Anava; Elad Hazan; Assaf Zeevi (ICML, 2015)

Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets. - Dan Garber; Elad Hazan (ICML, 2015)

Online Learning of Eigenvectors. - Dan Garber; Elad Hazan; Tengyu Ma 001 (ICML, 2015)

Classification with Low Rank and Missing Data. - Elad Hazan; Roi Livni; Yishay Mansour (ICML, 2015)

Online Learning for Adversaries with Memory: Price of Past Mistakes. - Oren Anava; Elad Hazan; Shie Mannor (NIPS, 2015)

Online Gradient Boosting. - Alina Beygelzimer; Elad Hazan; Satyen Kale; Haipeng Luo (NIPS, 2015)

Beyond Convexity: Stochastic Quasi-Convex Optimization. - Elad Hazan; Kfir Y. Levy; Shai Shalev-Shwartz (NIPS, 2015)

Fast and Simple PCA via Convex Optimization. - Dan Garber; Elad Hazan (CoRR, 2015)

Oracle-Based Robust Optimization via Online Learning. - Aharon Ben-Tal; Elad Hazan; Tomer Koren; Shie Mannor (Oper. Res., 2015)

Online Learning with Low Rank Experts. - Elad Hazan; Tomer Koren; Roi Livni; Yishay Mansour (COLT, 2016)

Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier. - Jacob D. Abernethy; Elad Hazan (ICML, 2016)

Faster Eigenvector Computation via Shift-and-Invert Preconditioning. - Dan Garber; Elad Hazan; Chi Jin 001; Sham M. Kakade; Cameron Musco; Praneeth Netrapalli; Aaron Sidford (ICML, 2016)

Variance-Reduced and Projection-Free Stochastic Optimization. - Elad Hazan; Haipeng Luo (ICML, 2016)

On Graduated Optimization for Stochastic Non-Convex Problems. - Elad Hazan; Kfir Yehuda Levy; Shai Shalev-Shwartz (ICML, 2016)

Variance Reduction for Faster Non-Convex Optimization. - Zeyuan Allen Zhu; Elad Hazan (ICML, 2016)

The Limits of Learning with Missing Data. - Brian Bullins; Elad Hazan; Tomer Koren (NIPS, 2016)

A Non-generative Framework and Convex Relaxations for Unsupervised Learning. - Elad Hazan; Tengyu Ma 001 (NIPS, 2016)

Optimal Black-Box Reductions Between Optimization Objectives. - Zeyuan Allen Zhu; Elad Hazan (NIPS, 2016)

The computational power of optimization in online learning. - Elad Hazan; Tomer Koren (STOC, 2016)

Second Order Stochastic Optimization in Linear Time. - Naman Agarwal; Brian Bullins; Elad Hazan (CoRR, 2016)

Finding Approximate Local Minima for Nonconvex Optimization in Linear Time. - Naman Agarwal; Zeyuan Allen Zhu; Brian Bullins; Elad Hazan; Tengyu Ma 001 (CoRR, 2016)

An optimal algorithm for bandit convex optimization. - Elad Hazan; Yuanzhi Li (CoRR, 2016)

Introduction to Online Convex Optimization. - Elad Hazan (Found. Trends Optim., 2016)

Volumetric Spanners: An Efficient Exploration Basis for Learning. - Elad Hazan; Zohar S. Karnin (J. Mach. Learn. Res., 2016)

Learning rotations with little regret. - Elad Hazan; Satyen Kale; Manfred K. Warmuth (Mach. Learn., 2016)

Sublinear time algorithms for approximate semidefinite programming. - Dan Garber; Elad Hazan (Math. Program., 2016)

A linear-time algorithm for trust region problems. - Elad Hazan; Tomer Koren (Math. Program., 2016)

A Linearly Convergent Variant of the Conditional Gradient Algorithm under Strong Convexity, with Applications to Online and Stochastic Optimization. - Dan Garber; Elad Hazan (SIAM J. Optim., 2016)

Efficient Regret Minimization in Non-Convex Games. - Elad Hazan; Karan Singh; Cyril Zhang (ICML, 2017)

Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls. - Zeyuan Allen-Zhu; Elad Hazan; Wei Hu 014; Yuanzhi Li (NIPS, 2017)

Learning Linear Dynamical Systems via Spectral Filtering. - Elad Hazan; Karan Singh; Cyril Zhang (NIPS, 2017)

Finding approximate local minima faster than gradient descent. - Naman Agarwal; Zeyuan Allen Zhu; Brian Bullins; Elad Hazan; Tengyu Ma 001 (STOC, 2017)

Second-Order Stochastic Optimization for Machine Learning in Linear Time. - Naman Agarwal; Brian Bullins; Elad Hazan (J. Mach. Learn. Res., 2017)

Near-Optimal Algorithms for Online Matrix Prediction. - Elad Hazan; Satyen Kale; Shai Shalev-Shwartz (SIAM J. Comput., 2017)

Lower Bounds for Higher-Order Convex Optimization. - Naman Agarwal; Elad Hazan (COLT, 2018)

Open problem: Improper learning of mixtures of Gaussians. - Elad Hazan; Roi Livni (COLT, 2018)

Towards Provable Control for Unknown Linear Dynamical Systems. - Sanjeev Arora; Elad Hazan; Holden Lee; Karan Singh; Cyril Zhang; Yi Zhang 074 (ICLR (Workshop), 2018)

Hyperparameter optimization: a spectral approach. - Elad Hazan; Adam R. Klivans; Yang Yuan (ICLR (Poster), 2018)

On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization. - Sanjeev Arora; Nadav Cohen; Elad Hazan (ICML, 2018)

Online Learning of Quantum States. - Scott Aaronson; Xinyi Chen 001; Elad Hazan; Satyen Kale; Ashwin Nayak 001 (NeurIPS, 2018)

Online Improper Learning with an Approximation Oracle. - Elad Hazan; Wei Hu 014; Yuanzhi Li; Zhiyuan Li 005 (NeurIPS, 2018)

Spectral Filtering for General Linear Dynamical Systems. - Elad Hazan; Holden Lee; Karan Singh; Cyril Zhang; Yi Zhang 074 (NeurIPS, 2018)

Online Learning of Quantum States. - Scott Aaronson; Xinyi Chen 001; Elad Hazan; Ashwin Nayak 001 (CoRR, 2018)

The Case for Full-Matrix Adaptive Regularization. - Naman Agarwal; Brian Bullins; Xinyi Chen 001; Elad Hazan; Karan Singh; Cyril Zhang; Yi Zhang 074 (CoRR, 2018)

Learning in Non-convex Games with an Optimization Oracle. - Alon Gonen; Elad Hazan (CoRR, 2018)

Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning. - Brian Bullins; Elad Hazan; Adam Kalai; Roi Livni (ALT, 2019)

Learning in Non-convex Games with an Optimization Oracle. - Naman Agarwal; Alon Gonen; Elad Hazan (COLT, 2019)

Efficient Full-Matrix Adaptive Regularization. - Naman Agarwal; Brian Bullins; Xinyi Chen 001; Elad Hazan; Karan Singh; Cyril Zhang; Yi Zhang 074 (ICML, 2019)

Online Control with Adversarial Disturbances. - Naman Agarwal; Brian Bullins; Elad Hazan; Sham M. Kakade; Karan Singh (ICML, 2019)

Provably Efficient Maximum Entropy Exploration. - Elad Hazan; Sham M. Kakade; Karan Singh; Abby Van Soest (ICML, 2019)

Logarithmic Regret for Online Control. - Naman Agarwal; Elad Hazan; Karan Singh (NeurIPS, 2019)

Private Learning Implies Online Learning: An Efficient Reduction. - Alon Gonen; Elad Hazan; Shay Moran (NeurIPS, 2019)

Boosting for Dynamical Systems. - Naman Agarwal; Nataly Brukhim; Elad Hazan; Zhou Lu (CoRR, 2019)

Lecture Notes: Optimization for Machine Learning. - Elad Hazan (CoRR, 2019)

Exponentiated Gradient Meets Gradient Descent. - Udaya Ghai; Elad Hazan; Yoram Singer (ALT, 2020)

The Nonstochastic Control Problem. - Elad Hazan; Sham M. Kakade; Karan Singh (ALT, 2020)

The Gradient Complexity of Linear Regression. - Mark Braverman; Elad Hazan; Max Simchowitz; Blake E. Woodworth (COLT, 2020)

Faster Projection-free Online Learning. - Elad Hazan; Edgar Minasyan (COLT, 2020)

Improper Learning for Non-Stochastic Control. - Max Simchowitz; Karan Singh; Elad Hazan (COLT, 2020)

Extreme Tensoring for Low-Memory Preconditioning. - Xinyi Chen 001; Naman Agarwal; Elad Hazan; Cyril Zhang; Yi Zhang 074 (ICLR, 2020)

Boosting for Control of Dynamical Systems. - Naman Agarwal; Nataly Brukhim; Elad Hazan; Zhou Lu (ICML, 2020)

Online Agnostic Boosting via Regret Minimization. - Nataly Brukhim; Xinyi Chen 001; Elad Hazan; Shay Moran (NeurIPS, 2020)

Non-Stochastic Control with Bandit Feedback. - Paula Gradu; John Hallman; Elad Hazan (NeurIPS, 2020)

Geometric Exploration for Online Control. - Orestis Plevrakis; Elad Hazan (NeurIPS, 2020)

Disentangling Adaptive Gradient Methods from Learning Rates. - Naman Agarwal; Rohan Anil; Elad Hazan; Tomer Koren; Cyril Zhang (CoRR, 2020)

Online Boosting with Bandit Feedback. - Nataly Brukhim; Elad Hazan (ALT, 2021)

Black-Box Control for Linear Dynamical Systems. - Xinyi Chen 001; Elad Hazan (COLT, 2021)

A Regret Minimization Approach to Iterative Learning Control. - Naman Agarwal; Elad Hazan; Anirudha Majumdar; Karan Singh (ICML, 2021)

Boosting for Online Convex Optimization. - Elad Hazan; Karan Singh (ICML, 2021)

Generating Adversarial Disturbances for Controller Verification. - Udaya Ghai; David Snyder; Anirudha Majumdar; Elad Hazan (L4DC, 2021)

Multiclass Boosting and the Cost of Weak Learning. - Nataly Brukhim; Elad Hazan; Shay Moran; Indraneel Mukherjee; Robert E. Schapire (NeurIPS, 2021)

Online Control of Unknown Time-Varying Dynamical Systems. - Edgar Minasyan; Paula Gradu; Max Simchowitz; Elad Hazan (NeurIPS, 2021)

Machine Learning for Mechanical Ventilation Control. - Daniel Suo; Cyril Zhang; Paula Gradu; Udaya Ghai; Xinyi Chen 001; Edgar Minasyan; Naman Agarwal; Karan Singh; Julienne LaChance; Tom Zajdel; Manuel Schottdorf; Daniel J. Cohen; et al. (CoRR, 2021)

Deluca - A Differentiable Control Library: Environments, Methods, and Benchmarking. - Paula Gradu; John Hallman; Daniel Suo; Alex Yu; Naman Agarwal; Udaya Ghai; Karan Singh; Cyril Zhang; Anirudha Majumdar; Elad Hazan (CoRR, 2021)

Provable Regret Bounds for Deep Online Learning and Control. - Xinyi Chen 001; Edgar Minasyan; Jason D. Lee; Elad Hazan (CoRR, 2021)

Machine Learning for Mechanical Ventilation Control (Extended Abstract). - Daniel Suo; Cyril Zhang; Paula Gradu; Udaya Ghai; Xinyi Chen 001; Edgar Minasyan; Naman Agarwal; Karan Singh; Julienne LaChance; Tom Zajdel; Manuel Schottdorf; Daniel J. Cohen; et al. (CoRR, 2021)

A Regret Minimization Approach to Multi-Agent Control. - Udaya Ghai; Udari Madhushani; Naomi Ehrich Leonard; Elad Hazan (ICML, 2022)

Robust Online Control with Model Misspecification. - Udaya Ghai; Xinyi Chen 001; Elad Hazan; Alexandre Megretski (L4DC, 2022)

A Boosting Approach to Reinforcement Learning. - Nataly Brukhim; Elad Hazan; Karan Singh (NeurIPS, 2022)

Non-convex online learning via algorithmic equivalence. - Udaya Ghai; Zhou Lu; Elad Hazan (NeurIPS, 2022)

A Regret Minimization Approach to Multi-Agent Contro. - Udaya Ghai; Udari Madhushani; Naomi Ehrich Leonard; Elad Hazan (CoRR, 2022)

Adaptive Gradient Methods with Local Guarantees. - Zhou Lu; Wenhan Xia; Sanjeev Arora; Elad Hazan (CoRR, 2022)

Efficient Adaptive Regret Minimization. - Zhou Lu; Elad Hazan (CoRR, 2022)

Partial Matrix Completion. - Varun Kanade; Elad Hazan; Adam Tauman Kalai (CoRR, 2022)

Introduction to Online Nonstochastic Control. - Elad Hazan; Karan Singh (CoRR, 2022)

Projection-free Adaptive Regret with Membership Oracles. - Zhou Lu; Nataly Brukhim; Paula Gradu; Elad Hazan (ALT, 2023)

Online Learning for Obstacle Avoidance. - David Snyder; Meghan Booker; Nathaniel Simon; Wenhan Xia; Daniel Suo; Elad Hazan; Anirudha Majumdar (CoRL, 2023)

Regret Guarantees for Online Deep Control. - Xinyi Chen 001; Edgar Minasyan; Jason D. Lee; Elad Hazan (L4DC, 2023)

Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret. - Gautam Goel; Naman Agarwal; Karan Singh; Elad Hazan (L4DC, 2023)

Adaptive Regret for Control of Time-Varying Dynamics. - Paula Gradu; Elad Hazan; Edgar Minasyan (L4DC, 2023)

Online Control for Meta-optimization. - Xinyi Chen 001; Elad Hazan (NeurIPS, 2023)

Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions. - Vladimir Feinberg; Xinyi Chen 001; Y. Jennifer Sun; Rohan Anil; Elad Hazan (NeurIPS, 2023)

Online Nonstochastic Model-Free Reinforcement Learning. - Udaya Ghai; Arushi Gupta; Wenhan Xia; Karan Singh; Elad Hazan (NeurIPS, 2023)

Partial Matrix Completion. - Elad Hazan; Adam Tauman Kalai; Varun Kanade; Clara Mohri; Y. Jennifer Sun (NeurIPS, 2023)

Optimal Rates for Bandit Nonstochastic Control. - Y. Jennifer Sun; Stephen H. Newman; Elad Hazan (NeurIPS, 2023)

A Nonstochastic Control Approach to Optimization. - Xinyi Chen 001; Elad Hazan (CoRR, 2023)

An Efficient Interior-Point Method for Online Convex Optimization. - Elad Hazan; Nimrod Megiddo (CoRR, 2023)

AI safety by debate via regret minimization. - Xinyi Chen 001; Angelica Chen; Dean P. Foster; Elad Hazan (CoRR, 2023)

Spectral State Space Models. - Naman Agarwal; Daniel Suo; Xinyi Chen 001; Elad Hazan (CoRR, 2023)

Boosting Simple Learners. - Noga Alon; Alon Gonen; Elad Hazan; Shay Moran (TheoretiCS, 2023)

Open Problem: Black-Box Reductions and Adaptive Gradient Methods for Nonconvex Optimization. - Xinyi Chen 001; Elad Hazan (COLT, 2024)

Second Order Methods for Bandit Optimization and Control. - Arun Sai Suggala; Y. Jennifer Sun; Praneeth Netrapalli; Elad Hazan (COLT, 2024)

Adaptive Regret for Bandits Made Possible: Two Queries Suffice. - Zhou Lu; Qiuyi Zhang 001; Xinyi Chen 001; Fred Zhang; David P. Woodruff; Elad Hazan (ICLR, 2024)

Online Control in Population Dynamics. - Noah Golowich; Elad Hazan; Zhou Lu; Dhruv Rohatgi; Y. Jennifer Sun (NeurIPS, 2024)

Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning. - Wenhan Xia; Chengwei Qin; Elad Hazan (CoRR, 2024)

Flash STU: Fast Spectral Transform Units. - Y. Isabel Liu; Windsor Nguyen; Yagiz Devre; Evan Dogariu; Anirudha Majumdar; Elad Hazan (CoRR, 2024)

FutureFill: Fast Generation from Convolutional Sequence Models. - Naman Agarwal; Xinyi Chen 001; Evan Dogariu; Vladimir Feinberg; Daniel Suo; Peter L. Bartlett; Elad Hazan (CoRR, 2024)

Provable Length Generalization in Sequence Prediction via Spectral Filtering. - Annie Marsden; Evan Dogariu; Naman Agarwal; Xinyi Chen 001; Daniel Suo; Elad Hazan (CoRR, 2024)

Adaptive Online Learning of Quantum States. - Xinyi Chen 001; Elad Hazan; Tongyang Li; Zhou Lu; Xinzhao Wang; Rui Yang (Quantum, 2024)

Dimension-free Regret for Learning Asymmetric Linear Dynamical Systems. - Annie Marsden; Elad Hazan (CoRR, 2025)

A New Approach to Controlling Linear Dynamical Systems. - Anand Brahmbhatt; Gon Buzaglo; Sofiia Druchyna; Elad Hazan (CoRR, 2025)

SpectraLDS: Provable Distillation for Linear Dynamical Systems. - Devan Shah; Shlomo Fortgang; Sofiia Druchyna; Elad Hazan (CoRR, 2025)

Efficient Spectral Control of Partially Observed Linear Dynamical Systems. - Anand Brahmbhatt; Gon Buzaglo; Sofiia Druchyna; Elad Hazan (CoRR, 2025)

Universal Learning of Nonlinear Dynamics. - Evan Dogariu; Anand Brahmbhatt; Elad Hazan (CoRR, 2025)