19 citations · 23 across the 5 of their papers we have counts for
6 papers
Learning from Noisy Labels with Noise Modeling Network
Zhuolin Jiang, Jan Silovsky, Man-Hung Siu +3
Multi-label image classification has generated significant interest in recent years and the performance of such systems often suffers from the not so infrequent occurrence of incor…
Learning Spatiotemporal Features for Infrared Action Recognition with 3D Convolutional Neural Networks
Zhuolin Jiang, Viktor Rozgic, Sancar Adali
Infrared (IR) imaging has the potential to enable more robust action recognition systems compared to visible spectrum cameras due to lower sensitivity to lighting conditions and ap…
Seeded Graph Matching Via Joint Optimization of Fidelity and Commensurability
Heather Patsolic, Sancar Adali, Joshua T. Vogelstein +4
We present a novel approximate graph matching algorithm that incorporates seeded data into the graph matching paradigm. Our Joint Optimization of Fidelity and Commensurability (JOF…
Fidelity-Commensurability Tradeoff in Joint Embedding of Disparate Dissimilarities
Sancar Adali, Carey E. Priebe
In various data settings, it is necessary to compare observations from disparate data sources. We assume the data is in the dissimilarity representation and investigate a joint emb…
Seeded Graph Matching
Donniell E. Fishkind, Sancar Adali, Heather G. Patsolic +4
Given two graphs, the graph matching problem is to align the two vertex sets so as to minimize the number of adjacency disagreements between the two graphs. The seeded graph matchi…
Manifold Matching: Joint Optimization of Fidelity and Commensurability
Carey E. Priebe, David J. Marchette, Zhiliang Ma +1
Fusion and inference from multiple and massive disparate data sources - the requirement for our most challenging data analysis problems and the goal of our most ambitious statistic…