3 citations · 3 across the 4 of their papers we have counts for
5 papers
Principled and Scalable Diversity-Aware Retrieval via Cardinality-Constrained Binary Quadratic Programming
Qiheng Lu, Nicholas D. Sidiropoulos
Diversity-aware retrieval is essential for Retrieval-Augmented Generation (RAG), yet existing methods lack theoretical guarantees and face scalability issues as the number of retri…
Subspace Clustering of Subspaces: Unifying Canonical Correlation Analysis and Subspace Clustering
Paris A. Karakasis, Nicholas D. Sidiropoulos
We introduce a novel framework for clustering a collection of tall matrices based on their column spaces, a problem we term Subspace Clustering of Subspaces (SCoS). Unlike traditio…
The Vertex-Attribute-Constrained Densest -Subgraph Problem
Qiheng Lu, Nicholas D. Sidiropoulos, Aritra Konar
Dense subgraph mining is a fundamental technique in graph mining, commonly applied in fraud detection, community detection, product recommendation, and document summarization. In s…
On Densest -Subgraph Mining and Diagonal Loading: Optimization Landscape and Finite-Step Exact Convergence Analysis
Qiheng Lu, Nicholas D. Sidiropoulos, Aritra Konar
The Densest -Subgraph (DS) is a fundamental combinatorial problem known for its theoretical hardness and breadth of applications. Recently, Lu et al. (AAAI 2025) introduced a…
Revisiting Deep Generalized Canonical Correlation Analysis
Paris A. Karakasis, Nicholas D. Sidiropoulos
Canonical correlation analysis (CCA) is a classic statistical method for discovering latent co-variation that underpins two or more observed random vectors. Several extensions and…