Bo-Han Wu

This paper proposes a robust functional ECO engine, which applies SAT proof minimization and interpolation techniques to automate patch construction to make old implementation and golden specification functionally equivalent. Expand

We provide a preprocessing technique to analyze solution space by adaptively splitting ranges of variables and prove the feasibility of each subspace to enhance pattern generation speed and ensure the desired distribution. Expand

We propose a novel Range-Splitting heuristic and a Solution-Density Estimation technique (RSSDE) to partition sample space to generate a high-throughput and evenly-distributed constrained random pattern generator. Expand

We propose a novel range-splitting heuristic and a solution-density estimation technique to conquer the challenges of random pattern generators proposed in the recent literature. Expand

Generative Attention Learning (GenerAL) is a framework for high-DOF multi-fingered grasping that is not only robust to dense clutter and novel objects but also effective with a variety of different parallel-jaw and multi-fingerered robot hands. Expand

A scalable and experimentally viable architecture for generating timefrequency-multiplexed 3D CV cluster states and utilizing them for large-scale quantum computing. Expand

In this paper, a new decoding algorithm using adaptive sliding window is proposed. Expand

We propose a technique to preprocess the solution space under each constraint set under Constrained Random Verification (CRV) to accelerate pattern generation under multiple constraint sets. Expand