Decision Making with A.I.

We are looking for talented graduate students and postdocs with strong mathematical background and interests in optimization and machine learning. Check our Current Openings!

• 2023-02

  Congratulations to Xiang Li for receiving the ETH medal for his outstanding Master's thesis! See news here .

• 2023-02

  Two papers accepted to AISTATS 2023 . Our paper on TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization is accepted to ICLR 2023 .

• 2023-01

  Niao visited University of Vienna in January and gave a lecture series on reinforcement learning at Vienna Graduate School on Computational Optimization .

• 2023-01

  Two journal papers accepted: our paper on Sample Complexity and Overparameterization Bounds for Temporal Difference Learning with Neural Network Approximation is accepted to IEEE Transactions on Automatic Control ; our paper on A discrete-time switching system analysis of Q-learning is accepted to SIAM Journal on Control and Optimization .

• 2022-12

  Niao gave a talk on Adaptive Min-Max Optimization at NeurIPS Workshop on Optimization for Maching Learning at New Orleans, USA, and at NUS Workshop on Optimization in the Big Data Era, National University of Singapore.

• 2022-10

  Congratulations to ODI members, Junchi, Jiawei, Giorgia, and Siqi for being rated as top reviewers for NeurIPS 2022!

• 2022-10

  Niao gave a talk on Nonconvex min-max optimization: fundamental limits, acceleration, and adaptivity at The Mathematics of Machine Learning Workshop at Bilbao, Spain.

• 2022-09

  Several papers from the group members are accepted for NeurIPS 2022.
  - Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization. J. YANG, X. Li, N. He.
  - Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality. I. Fatkhullin, J. Etesami, N. He, N. Kiyavash.
  - Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization. L. Zhang, K. Thekumparampil, S. Oh, N. He.
  - Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions. A. Terpin, N. Lanzetti, A. B. Yardim, G. Ramponi, F. Dorfler.
  - Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret. J. Huang et.al.
  - Stochastic Second-Order Methods Provably Beat SGD For Gradient-Dominated Functions. M. Masiha, S. Salehkaleybar, N. He, N. Kiyavash, P. Thiran.

• 2022-09

  Niao gave a talk on Complexities of Actor-critic Methods for Regularized MDPs and POMDPs at the 15th European Workshop on Reinforcement Learning (EWRL 2022) in Milan, Italy and the WiOpt workshop on Reinforcement Learning and Stochastic Control in Queues and Networks.

• 2022-09

  Niao gave a lecture on the Interplay between Optimization and Reinforcement Learning at the Sargent Centre Summer School on Data-Driven Optimisation at Imperial College London, UK.

• 2022-08

  Congratulations for Yifan, Siqi, and Semih for their new journeys. Yifan is starting a postdoc position at EPFL, Switzerland, and Siqi will be a Rufus Isaacs Postdoctoral Fellow at Johns Hopkins University, USA. Semih Cayci will start a faculty position in the Department of Mathematics at RWTH Aachen, Germany.

• 2022-07

  Several group members, Yifan, Anas, and Niao gave talks and organized sessions at the seventh International Conference on Continuous Optimization (ICCOPT) at Lehigh University, USA.

• 2022-06

  Niao gave a talk on nonconvex minimax optimization and Junchi presented a poster at the ELLIS Theory Workshop in Arenzano, Italy.

• 2022-05

  Together with Florian Dorfler, Niao co-organized the NCCR symposium on Systems Theory of Algorithms at ETH Zurich and also gave a talk on Q-learning through the Lens of Dynamical Systems : from asymptotics to non-asymptotics.

• 2022-02

  Niao visited Simons Institute at UC Berkeley for six weeks and participated in the Learning and Games program. During the visit, Niao gave a talk on Universal Acceleration for Minimax Optimization at the visitor seminar series and another talk on single-loop algorithms for unbalanced minimax optimization at the workshop on Adversarial Approaches in Machine Learning.

• 2021-11

  Niao gave a seminar talk on "Three common RL tricks: why and when do they work?" at Machine Learning Genoa Center (MaLGa), Italy and a virtual talk at the Control Seminar series at University of Oxford, UK.

• 2021-08

  Together with Yurii Nesterov, Niao gave week-long lectures at Zinal Summer School: Data Science, Optimization and Operations Research organized by TRANSP-OR from EPFL. Please find the lecture slides on Reinforcement Learning: Optimization and Dynamical Systems Perspectives here.

• 2021-07

  Together with Agarwal, Du, Szepesvári, and Yang, we organized the ICML workshop on Reinforcement Learning Theory, July 24-25, virtual event.

• 2021-06

  Niao (joint with Bo Dai from Google Brain) gave lectures on Reconciling Reinforcement Learning: Optimization, Generalization, and Exploration at the EPFL & ETHZ Summer School on Foundations and Mathematical Guarantees of Data-driven Control. Please find the (8-hour) video recording here.

• 2021-01

  Our group has moved to ETH Zurich, Switzerland!

• 2020-12

  Our group got six papers accepted to NeurIPS 2020! Check papers here.

• 2020-08

  We are exciting to be a part of the USDA-NIFA AI Institute on Next Generation Food Systems (AIFS, a joint effort lead by UC Davis, UC Berkeley, Cornell, and UIUC). Check news here.

• 2020-07

  Yingxiang graduated and started his next position as a research scientist at ByteDance in Seattle.

• 2020-06

  Niao gave a talk at the Virtual Seminar on Theory of RL on Understanding the Convergence of Reinforcement Learning Algorithms from Dynamical Systems Perspectives . Check the slide and video here.

• 2020-03

  Donghwan Lee started a faculty position at KAIST.

• 2020-01

  Niao is elected as the 2020-21 Beckman CAS Fellow by the Center for Avanced Studies at UIUC.