Zhaoran Wang

Generative Adversarial Imitation Learning with Neural Networks: Global Optimality and Convergence Rate

2020 · arXiv (Cornell University)

Generative adversarial imitation learning (GAIL) demonstrates tremendous success in practice, especially when combined with neural networks. Different from reinforcement learning, GAIL learns both policy and reward function from expert (human) demonstration. Despite its empirical success, …

On the Global Optimality of Model-Agnostic Meta-Learning

2020 · arXiv (Cornell University)

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 level searches for the optimal shared prior by optimizing its …

Point process models for sequence detection in high-dimensional neural spike trains

2020 · PubMed

Sparse sequences of neural spikes are posited to underlie aspects of working memory [1], motor production [2], and learning [3, 4]. Discovering these sequences in an unsupervised manner is a longstanding problem in statistical neuroscience …

Design-while-verify

2022

In the current control design of safety-critical cyber-physical systems, formal verification techniques are typically applied after the controller is designed to evaluate whether the required properties (e.g., safety) are satisfied. However, due to the increasing …

Human-Instruction-Free LLM Self-Alignment with Limited Samples

2024 · arXiv (Cornell University)

Aligning large language models (LLMs) with human values is a vital task for LLM practitioners. Current alignment techniques have several limitations: (1) requiring a large amount of annotated data; (2) demanding heavy human involvement; (3) …