131 citations · 397 across the 37 of their papers we have counts for
9 papers · 1 filter
Monte Carlo Tree Descent for Black-Box Optimization
Yaoguang Zhai, Sicun Gao
The key to Black-Box Optimization is to efficiently search through input regions with potentially widely-varying numerical properties, to achieve low-regret descent and fast progre…
Policy Optimization with Advantage Regularization for Long-Term Fairness in Decision Systems
Eric Yang Yu, Zhizhen Qin, Min Kyung Lee +1
Long-term fairness is an important factor of consideration in designing and deploying learning-based decision systems in high-stake decision-making contexts. Recent work has propos…
Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation
Chenning Yu, Hongzhan Yu, Sicun Gao
Deep reinforcement learning in continuous domains focuses on learning control policies that map states to distributions over actions that ideally concentrate on the optimal choices…
Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks
Chenning Yu, Sicun Gao
Sampling-based motion planning is a popular approach in robotics for finding paths in continuous configuration spaces. Checking collision with obstacles is the major computational…
Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding
Ruipeng Zhang, Chenning Yu, Jingkai Chen +2
Learning-based methods have shown promising performance for accelerating motion planning, but mostly in the setting of static environments. For the more challenging problem of plan…
Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions
Zhizhen Qin, Tsui-Wei Weng, Sicun Gao
Path-tracking control of self-driving vehicles can benefit from deep learning for tackling longstanding challenges such as nonlinearity and uncertainty. However, deep neural contro…
SCALE: Online Self-Supervised Lifelong Learning without Prior Knowledge
Xiaofan Yu, Yunhui Guo, Sicun Gao +1
Unsupervised lifelong learning refers to the ability to learn over time while memorizing previous patterns without supervision. Although great progress has been made in this direct…
Everyone's Preference Changes Differently: Weighted Multi-Interest Retrieval Model
Hui Shi, Yupeng Gu, Yitong Zhou +3
User embeddings (vectorized representations of a user) are essential in recommendation systems. Numerous approaches have been proposed to construct a representation for the user in…
Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods
Charles Dawson, Sicun Gao, Chuchu Fan
Learning-enabled control systems have demonstrated impressive empirical performance on challenging control problems in robotics, but this performance comes at the cost of reduced t…