5 citations · 5 across the 7 of their papers we have counts for
7 papers
Local Maxima of the Entrywise Norm on the Orthogonal Group
Dian Jin
We classify the local maximizers of the entrywise fourth-power objective \[ Q\longmapsto \lVert Q\rVert_4^4 =\sum_{i,j=1}^r q_{ij}^4 \] over the real orthogonal group $\mathcal O(r…
Cost-optimal Sequential Testing via Doubly Robust Q-learning
Doudou Zhou, Yiran Zhang, Dian Jin +3
Clinical decision-making often involves selecting tests that are costly, invasive, or time-consuming, motivating individualized, sequential strategies for what to measure and when…
On the sensitivity of the subspace predictor to behavioral perturbations
Dian Jin, Jeremy Coulson
Behavioral systems define discrete-time LTI systems in terms of a set of trajectories, which forms a linear subspace. This subspace underlies the subspace predictor used in data-dr…
Federated Independent Component Analysis via Spectral Alignment and Robust Aggregation
Dian Jin, Xin Bing, Yuqian Zhang
This paper studies robust estimation for Independent Component Analysis (ICA) in the federated learning setting, where data are locally distributed across clients and may exhibit s…
Community Detection for Contextual-LSBM: Theoretical Limitations of Misclassification Rate and Efficient Algorithms
Dian Jin, Yuqian Zhang, Qiaosheng Zhang
The integration of network information and node attribute information has recently gained significant attention in the community detection literature. In this work, we consider com…
Optimal vintage factor analysis with deflation varimax
Xin Bing, Xin He, Dian Jin +1
Vintage factor analysis is one important type of factor analysis that aims to first find a low-dimensional representation of the original data, and then to seek a rotation such tha…
Unique sparse decomposition of low rank matrices
Dian Jin, Xin Bing, Yuqian Zhang
The problem of finding the unique low dimensional decomposition of a given matrix has been a fundamental and recurrent problem in many areas. In this paper, we study the problem of…