Madeline Navarro

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 22

Top Topics

Graphical Models

Network Topology

Joint Inference

Top Venues

IEEE Trans. Signal Process.

J. Mach. Learn. Res.

Publications

Madeline Navarro, Santiago Segarra
SC-MAD: Mixtures of Higher-Order Networks for Data Augmentation. ICASSP (2024)
Victor M. Tenorio, Madeline Navarro, Santiago Segarra, Antonio G. Marques
Recovering Missing Node Features with Local Structure-Based Embeddings. ICASSP (2024)
Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra
Joint Network Topology Inference in the Presence of Hidden Nodes. IEEE Trans. Signal Process. 72 (2024)
Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra
Data Augmentation via Subgroup Mixup for Improving Fairness. ICASSP (2024)
Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra
Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior. CoRR (2024)
Madeline Navarro, Santiago Segarra
Graphmad: Graph Mixup for Data Augmentation Using Data-Driven Convex Clustering. ICASSP (2023)
Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra
Data Augmentation via Subgroup Mixup for Improving Fairness. CoRR (2023)
Victor M. Tenorio, Madeline Navarro, Santiago Segarra, Antonio G. Marques
Recovering Missing Node Features with Local Structure-based Embeddings. CoRR (2023)
Madeline Navarro, Santiago Segarra
SC-MAD: Mixtures of Higher-order Networks for Data Augmentation. CoRR (2023)
Samuel Rey, Madeline Navarro, Andrei Buciulea, Santiago Segarra, Antonio G. Marques
Joint graph learning from Gaussian observations in the presence of hidden nodes. CoRR (2022)
Madeline Navarro, Santiago Segarra
Joint Network Topology Inference via a Shared Graphon Model. CoRR (2022)
Madeline Navarro, Santiago Segarra
GraphMAD: Graph Mixup for Data Augmentation using Data-Driven Convex Clustering. CoRR (2022)
Samuel Rey, Madeline Navarro, Andrei Buciulea, Santiago Segarra, Antonio G. Marques
Joint graph learning from Gaussian observations in the presence of hidden nodes. IEEECONF (2022)
Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra
Joint Inference of Multiple Graphs from Matrix Polynomials. J. Mach. Learn. Res. 23 (2022)
Samuel Rey, Andrei Buciulea, Madeline Navarro, Santiago Segarra, Antonio G. Marques
Joint Inference of Multiple Graphs with Hidden Variables from Stationary Graph Signals. ICASSP (2022)
Madeline Navarro, Santiago Segarra
Graphon-Aided Joint Estimation of Multiple Graphs. ICASSP (2022)
Madeline Navarro, Santiago Segarra
Joint Network Topology Inference Via a Shared Graphon Model. IEEE Trans. Signal Process. 70 (2022)
Madeline Navarro, Santiago Segarra
Graphon-aided Joint Estimation of Multiple Graphs. CoRR (2022)
Samuel Rey, Andrei Buciulea, Madeline Navarro, Santiago Segarra, Antonio G. Marques
Joint inference of multiple graphs with hidden variables from stationary graph signals. CoRR (2021)
Madeline Navarro, Genevera I. Allen, Michael Weylandt
Network Clustering for Latent State and Changepoint Detection. CoRR (2021)
T. Mitchell Roddenberry, Madeline Navarro, Santiago Segarra
Network Topology Inference with Graphon Spectral Penalties. ICASSP (2021)
Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra
Joint Inference of Multiple Graphs from Matrix Polynomials. CoRR (2020)