2 citations · 3 across the 5 of their papers we have counts for
5 papers
Stronger Lower Bounds for (Non-)Anytime Acceleration of Gradient Descent
Minchan Jung, Hanseul Cho, Chulhee Yun
The rate-optimal convergence rate of gradient descent (GD) with a fixed step-size is well known to be for -Lipschitz smooth convex objectives in the prior art in con…
Deep-Unfolded Coordination
Hunter Kuperman, Minchan Jung, Rahul V. Ghosh +2
Distributed optimization is a highly scalable and structurally transparent technique to solve multi-agent robotics problems; however, such methods often suffer from the need for hi…
Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control
Yuichiro Aoyama, Minchan Jung, Akash Ratheesh +1
This paper investigates the optimization mechanisms of non-convex Model Predictive Control (MPC) using the Maximum Entropy Differential Dynamic Programming (ME-DDP) framework. Navi…
BiC-MPPI: Goal-Pursuing, Sampling-Based Bidirectional Rollout Clustering Path Integral for Trajectory Optimization
Minchan Jung, Kwangki Kim
This paper introduces the Bidirectional Clustered MPPI (BiC-MPPI) algorithm, a novel trajectory optimization method aimed at enhancing goal-directed guidance within the Model Predi…
MPPI-IPDDP: Hybrid Method of Collision-Free Smooth Trajectory Generation for Autonomous Robots
Min-Gyeom Kim, Minchan Jung, JunGee Hong +1
This paper presents a hybrid trajectory optimization method designed to generate collision-free, smooth trajectories for autonomous mobile robots. By combining sampling-based Model…