activity
20042025
most citedPareto-depth for Multiple-query Image Retrieval

24 citations · 27 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2025

A Multiscale Geometric Method for Capturing Relational Topic Alignment

Conrad D. Hougen, Karl T. Pazdernik, Alfred O. Hero

Interpretable topic modeling is essential for tracking how research interests evolve within co-author communities. In scientific corpora, where novelty is prized, identifying under…

eess.SP2023★ 1 cited

Community Detection in High-Dimensional Graph Ensembles

Robert Malinas, Dogyoon Song, Alfred O. Hero

Detecting communities in high-dimensional graphs can be achieved by applying random matrix theory where the adjacency matrix of the graph is modeled by a Stochastic Block Model (SB…

math.ST2021

A unified framework for correlation mining in ultra-high dimension

Yun Wei, Bala Rajaratnam, Alfred O. Hero

Many applications benefit from theory relevant to the identification of variables having large correlations or partial correlations in high dimension. Recently there has been progr…

cs.IR2014★ 24 cited

Pareto-depth for Multiple-query Image Retrieval

Ko-Jen Hsiao, Jeff Calder, Alfred O. Hero

Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this pa…

quant-ph2004★ 2 cited

Electron spin detection in the frequency domain under the interrupted Oscillating Cantilever-driven Adiabatic Reversal (iOSCAR) Protocol

M. Ting, A. O. Hero, D. Rugar +2

Magnetic Resonance Force Microscopy (MRFM) is an emergent technology for measuring spin-induced attonewton forces using a micromachined cantilever. In the interrupted Oscillating C…