15 citations · 22 across the 2 of their papers we have counts for
5 papers
On the Global Optimality of Model-Agnostic Meta-Learning
Lingxiao Wang, Qi Cai, Zhuoran Yang +1
Model-agnostic meta-learning (MAML) formulates meta-learning as a bilevel optimization problem, where the inner level solves each subtask based on a shared prior, while the outer l…
Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate
Yufeng Zhang, Qi Cai, Zhuoran Yang +1
Generative adversarial imitation learning (GAIL) demonstrates tremendous success in practice, especially when combined with neural networks. Different from reinforcement learning,…
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence
Lingxiao Wang, Qi Cai, Zhuoran Yang +1
Policy gradient methods with actor-critic schemes demonstrate tremendous empirical successes, especially when the actors and critics are parameterized by neural networks. However,…
Neural Temporal-Difference and Q-Learning Provably Converge to Global Optima
Qi Cai, Zhuoran Yang, Jason D. Lee +1
Temporal-difference learning (TD), coupled with neural networks, is among the most fundamental building blocks of deep reinforcement learning. However, due to the nonlinearity in v…
On the Global Convergence of Imitation Learning: A Case for Linear Quadratic Regulator
Qi Cai, Mingyi Hong, Yongxin Chen +1
We study the global convergence of generative adversarial imitation learning for linear quadratic regulators, which is posed as minimax optimization. To address the challenges aris…