Timezone: »
Talk
Efficient Regret Minimization in Non-Convex Games
Elad Hazan · Karan Singh · Cyril Zhang
We consider regret minimization in repeated games with non-convex loss functions. Minimizing the standard notion of regret is computationally intractable. Thus, we define a natural notion of regret which permits efficient optimization and generalizes offline guarantees for convergence to an approximate local optimum. We give gradient-based methods that achieve optimal regret, which in turn guarantee convergence to equilibrium in this framework.
Summary/NotesAuthor Information
Elad Hazan (Princeton University)
Karan Singh (Princeton University)
Cyril Zhang (Princeton University)
Related Events (a corresponding poster, oral, or spotlight)
-
2017 Poster: Efficient Regret Minimization in Non-Convex Games »
Mon. Aug 7th 08:30 AM -- 12:00 PM Room Gallery #45
More from the Same Authors
-
2021 : Robust online control with model misspecification »
Xinyi Chen · Udaya Ghai · Elad Hazan · Alexandre Megretsky -
2021 : A Boosting Approach to Reinforcement Learning »
Nataly Brukhim · Elad Hazan · Karan Singh -
2022 : Non-convex online learning via algorithmic equivalence »
Udaya Ghai · Zhou Lu · Elad Hazan -
2022 Poster: A Regret Minimization Approach to Multi-Agent Control »
Udaya Ghai · Udari Madhuhshani · Naomi Leonard · Elad Hazan -
2022 Spotlight: A Regret Minimization Approach to Multi-Agent Control »
Udaya Ghai · Udari Madhuhshani · Naomi Leonard · Elad Hazan -
2021 Poster: Boosting for Online Convex Optimization »
Elad Hazan · Karan Singh -
2021 Spotlight: Boosting for Online Convex Optimization »
Elad Hazan · Karan Singh -
2021 Poster: A Regret Minimization Approach to Iterative Learning Control »
Naman Agarwal · Elad Hazan · Anirudha Majumdar · Karan Singh -
2021 Spotlight: A Regret Minimization Approach to Iterative Learning Control »
Naman Agarwal · Elad Hazan · Anirudha Majumdar · Karan Singh -
2021 Tutorial: Online and non-stochastic control »
Elad Hazan · Karan Singh -
2021 : Online and non-stochastic control »
Elad Hazan -
2020 Poster: Calibration, Entropy Rates, and Memory in Language Models »
Mark Braverman · Xinyi Chen · Sham Kakade · Karthik Narasimhan · Cyril Zhang · Yi Zhang -
2020 Poster: Boosting for Control of Dynamical Systems »
Naman Agarwal · Nataly Brukhim · Elad Hazan · Zhou Lu -
2019 Poster: Efficient Full-Matrix Adaptive Regularization »
Naman Agarwal · Brian Bullins · Xinyi Chen · Elad Hazan · Karan Singh · Cyril Zhang · Yi Zhang -
2019 Poster: Online Control with Adversarial Disturbances »
Naman Agarwal · Brian Bullins · Elad Hazan · Sham Kakade · Karan Singh -
2019 Oral: Efficient Full-Matrix Adaptive Regularization »
Naman Agarwal · Brian Bullins · Xinyi Chen · Elad Hazan · Karan Singh · Cyril Zhang · Yi Zhang -
2019 Oral: Online Control with Adversarial Disturbances »
Naman Agarwal · Brian Bullins · Elad Hazan · Sham Kakade · Karan Singh -
2019 Poster: Provably Efficient Maximum Entropy Exploration »
Elad Hazan · Sham Kakade · Karan Singh · Abby Van Soest -
2019 Oral: Provably Efficient Maximum Entropy Exploration »
Elad Hazan · Sham Kakade · Karan Singh · Abby Van Soest -
2018 Poster: On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization »
Sanjeev Arora · Nadav Cohen · Elad Hazan -
2018 Oral: On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization »
Sanjeev Arora · Nadav Cohen · Elad Hazan -
2017 Poster: The Price of Differential Privacy For Online Learning »
Naman Agarwal · Karan Singh -
2017 Talk: The Price of Differential Privacy For Online Learning »
Naman Agarwal · Karan Singh