8 accepted papers
The human hand is capable of executing a wide range of complex movements due to its biomechanical structure and skin sensing system. Designing an anthropomorphic hand that mimics the biomechanical structure of the human and incorporates skin sensing, presents a long-term challenge in the field of ro
In recent years, Transformers have been widely applied in human pose estimation by converting image features into token forms as inputs. However, redundant information in images burdens the network and can even negatively impact training as noise. Thus, we propose a coarse-to-fine Transformer called…
Pipeline inspections are crucial to ensure the reliability of the transmission system. However, with the growing complexity and aging of the pipe system, traditional pipeline inspection robots struggle to adapt to complex environments with obstacles, cracks, changing cross-section, and other challen
In this work, we consider the problem of matrix sensing over graphs (MSoG). As a general case of matrix completion and matrix sensing problems, the MSoG problem has not been analyzed in the literature and the existing results cannot be directly applied to the MSoG problem. This work provides the fir…
Burer-Monteiro (B-M) factorization approach can efficiently solve low-rank matrix optimization problems under the Restricted Isometry Property (RIP) condition. It is natural to ask whether B-M factorization-based methods can succeed on any low-rank matrix optimization problems with low information-t…
We study the convergence rate of gradient-based local search methods for solving low-rank matrix recovery problems with general objectives in both symmetric and asymmetric cases, under the assumption of the restricted isometry property. First, we develop a new technique to verify the Polyak-Lojasiew…
This paper considers the global geometry of general low-rank minimization problems via the Burer-Monterio factorization approach. For the rank-$1$ case, we prove that there is no spurious second-order critical point for both symmetric and asymmetric problems if the rank-$2$ RIP constant $\delta$ is…
We study an extension of the stochastic submodular minimization problem, namely, the stochastic $L^\natural$-convex minimization problem. We develop the first polynomial-time algorithms that return a near-optimal solution with high probability. We design a novel truncation operation to further reduc…