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Santiago Segarra
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2020 – today
- 2024
- [j52]Kristen D. Curry, Feiqiao Brian Yu
, Summer E. Vance, Santiago Segarra, Devaki Bhaya, Rayan Chikhi, Eduardo P. C. Rocha, Todd J. Treangen:
Reference-free structural variant detection in microbiomes via long-read co-assembly graphs. Bioinform. 40(Supplement_1): i58-i67 (2024) - [j51]Lisa O'Bryan, Tim Oxendahl, Xu Chen, Daniel McDuff, Santiago Segarra
, Matthew A. Wettergreen
, Margaret E. Beier, Ashutosh Sabharwal:
Objective Communication Patterns Associated With Team Member Effectiveness in Real-World Virtual Teams. Hum. Factors 66(5): 1414-1430 (2024) - [j50]Gunnar E. Carlsson, Santiago Segarra:
Data science for graphs. J. Appl. Comput. Topol. 8(5): 1099-1100 (2024) - [j49]Cameron R. Wolfe
, Jingkang Yang, Fangshuo Liao, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis:
GIST: distributed training for large-scale graph convolutional networks. J. Appl. Comput. Topol. 8(5): 1363-1415 (2024) - [j48]Gabriel Egan, Mark Eisen, Alejandro Ribeiro, Santiago Segarra:
A reply to Pervez Rizvi's letter. Digit. Scholarsh. Humanit. 39(1): 3-4 (2024) - [j47]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: 2710-2725 (2024) - [j46]Elvin Isufi
, Fernando Gama
, David I Shuman
, Santiago Segarra
:
Graph Filters for Signal Processing and Machine Learning on Graphs. IEEE Trans. Signal Process. 72: 4745-4781 (2024) - [j45]Arindam Chowdhury
, Gunjan Verma, Ananthram Swami, Santiago Segarra
:
Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks. IEEE Trans. Wirel. Commun. 23(5): 4889-4903 (2024) - [j44]Boning Li
, Jake B. Perazzone
, Ananthram Swami, Santiago Segarra
:
Learning to Transmit With Provable Guarantees in Wireless Federated Learning. IEEE Trans. Wirel. Commun. 23(7): 7439-7455 (2024) - [c111]Martin Sevilla, Antonio G. Marques, Santiago Segarra:
Estimation of partially known Gaussian graphical models with score-based structural priors. AISTATS 2024: 1558-1566 - [c110]T. Mitchell Roddenberry, Yu Zhu, Santiago Segarra:
An Impossibility Theorem for Node Embedding. AISTATS 2024: 2422-2430 - [c109]Carlos A. Taveras, Santiago Segarra, César A. Uribe:
Efficient Path Planning with Soft Homology Constraints. CCTA 2024: 657-662 - [c108]Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra:
Mitigating Subpopulation Bias for Fair Network Topology Inference. EUSIPCO 2024: 822-826 - [c107]Pantea Karimi
, Solal Pirelli
, Siva Kesava Reddy Kakarla
, Ryan Beckett
, Santiago Segarra
, Beibin Li
, Pooria Namyar
, Behnaz Arzani
:
Towards Safer Heuristics With XPlain. HotNets 2024: 68-76 - [c106]Pooria Namyar
, Michael Schapira
, Ramesh Govindan
, Santiago Segarra
, Ryan Beckett
, Siva Kesava Reddy Kakarla
, Behnaz Arzani
:
End-to-End Performance Analysis of Learning-enabled Systems. HotNets 2024: 86-94 - [c105]Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra:
Data Augmentation via Subgroup Mixup for Improving Fairness. ICASSP 2024: 7350-7354 - [c104]Zhongyuan Zhao, Jake B. Perazzone, Gunjan Verma, Santiago Segarra:
Congestion-Aware Distributed Task Offloading in Wireless Multi-Hop Networks Using Graph Neural Networks. ICASSP 2024: 8951-8955 - [c103]Benjamin Cox, Sara Pérez-Vieites, Nicolas Zilberstein, Martin Sevilla, Santiago Segarra, Víctor Elvira:
End-to-End Learning of Gaussian Mixture Proposals Using Differentiable Particle Filters and Neural Networks. ICASSP 2024: 9701-9705 - [c102]Martin Sevilla, Santiago Segarra:
Bayesian Topology Inference on Partially Known Networks from Input-Output Pairs. ICASSP 2024: 9721-9725 - [c101]Victor M. Tenorio, Madeline Navarro, Santiago Segarra, Antonio G. Marques:
Recovering Missing Node Features with Local Structure-Based Embeddings. ICASSP 2024: 9931-9935 - [c100]Nicolas Zilberstein, Ananthram Swami, Santiago Segarra:
Joint Channel Estimation and Data Detection in Massive Mimo Systems Based on Diffusion Models. ICASSP 2024: 13291-13295 - [c99]Madeline Navarro, Santiago Segarra:
SC-MAD: Mixtures of Higher-Order Networks for Data Augmentation. ICASSP 2024: 13446-13450 - [c98]Negar Erfaniantaghvayi, Zhongyuan Zhao, Kevin S. Chan, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Ant Backpressure Routing for Wireless Multi-hop Networks with Mixed Traffic Patterns. MILCOM 2024: 1174-1179 - [c97]Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra:
Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior. NeurIPS 2024 - [c96]Kevin Hsieh, Mike Wong, Santiago Segarra, Sathiya Kumaran Mani, Trevor Eberl, Anatoliy Panasyuk, Ravi Netravali, Ranveer Chandra, Srikanth Kandula:
NetVigil: Robust and Low-Cost Anomaly Detection for East-West Data Center Security. NSDI 2024 - [c95]Pooria Namyar, Behnaz Arzani, Ryan Beckett, Santiago Segarra, Himanshu Raj, Umesh Krishnaswamy, Ramesh Govindan, Srikanth Kandula:
Finding Adversarial Inputs for Heuristics using Multi-level Optimization. NSDI 2024 - [c94]Pooria Namyar, Behnaz Arzani, Srikanth Kandula, Santiago Segarra, Daniel Crankshaw, Umesh Krishnaswamy, Ramesh Govindan, Himanshu Raj:
Solving Max-Min Fair Resource Allocations Quickly on Large Graphs. NSDI 2024 - [c93]Ali Azizpour, Advait Balaji, Todd J. Treangen, Santiago Segarra:
GraSSRep: Graph-Based Self-supervised Learning for Repeat Detection in Metagenomic Assembly. RECOMB 2024: 372-376 - [i107]Arindam Chowdhury, Santiago Paternain, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Learning Non-myopic Power Allocation in Constrained Scenarios. CoRR abs/2401.10297 (2024) - [i106]Martin Sevilla, Antonio Garcia Marques, Santiago Segarra:
Estimation of partially known Gaussian graphical models with score-based structural priors. CoRR abs/2401.14340 (2024) - [i105]Ali Azizpour, Advait Balaji, Todd J. Treangen, Santiago Segarra:
GraSSRep: Graph-Based Self-Supervised Learning for Repeat Detection in Metagenomic Assembly. CoRR abs/2402.09381 (2024) - [i104]Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G. Marques, Santiago Segarra:
Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior. CoRR abs/2406.09513 (2024) - [i103]Nicolas Zilberstein, Morteza Mardani, Santiago Segarra:
Repulsive Score Distillation for Diverse Sampling of Diffusion Models. CoRR abs/2406.16683 (2024) - [i102]Carlos A. Taveras, Santiago Segarra, César A. Uribe:
Efficient Path Planning with Soft Homology Constraints. CoRR abs/2406.19551 (2024) - [i101]Zhongyuan Zhao, Bojan Radojicic, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Biased Backpressure Routing Using Link Features and Graph Neural Networks. CoRR abs/2407.09753 (2024) - [i100]Boning Li, Gunjan Verma, Timofey Efimov, Abhishek Kumar, Santiago Segarra:
GLANCE: Graph-based Learnable Digital Twin for Communication Networks. CoRR abs/2408.09040 (2024) - [i99]Negar Erfaniantaghvayi, Zhongyuan Zhao, Kevin S. Chan, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Ant Backpressure Routing for Wireless Multi-hop Networks with Mixed Traffic Patterns. CoRR abs/2408.12702 (2024) - [i98]Andrea Cavallo, Madeline Navarro, Santiago Segarra, Elvin Isufi:
Fair CoVariance Neural Networks. CoRR abs/2409.08558 (2024) - [i97]Samuel Rey, Madeline Navarro, Victor M. Tenorio, Santiago Segarra, Antonio G. Marques:
Redesigning graph filter-based GNNs to relax the homophily assumption. CoRR abs/2409.08676 (2024) - [i96]Andrei Buciulea, Madeline Navarro, Samuel Rey, Santiago Segarra, Antonio G. Marques:
Online Network Inference from Graph-Stationary Signals with Hidden Nodes. CoRR abs/2409.08760 (2024) - [i95]Pantea Karimi, Solal Pirelli, Siva Kesava Reddy Kakarla, Ryan Beckett, Santiago Segarra, Beibin Li, Pooria Namyar, Behnaz Arzani:
Towards Safer Heuristics With XPlain. CoRR abs/2410.15086 (2024) - [i94]Ali Azizpour, Nicolas Zilberstein, Santiago Segarra:
Scalable Implicit Graphon Learning. CoRR abs/2410.17464 (2024) - [i93]Madeline Navarro, Sergio Rozada, Antonio G. Marques, Santiago Segarra:
Low-Rank Tensors for Multi-Dimensional Markov Models. CoRR abs/2411.02098 (2024) - [i92]Lisa O'Bryan, Madeline Navarro, Juan Segundo Hevia, Santiago Segarra:
ML-SPEAK: A Theory-Guided Machine Learning Method for Studying and Predicting Conversational Turn-taking Patterns. CoRR abs/2411.15405 (2024) - [i91]Benjamin Cox, Santiago Segarra, Victor Elvira:
Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks. CoRR abs/2411.15638 (2024) - [i90]Victor M. Tenorio, Madeline Navarro, Samuel Rey, Santiago Segarra, Antonio G. Marques:
Structure-Guided Input Graph for GNNs facing Heterophily. CoRR abs/2412.01757 (2024) - [i89]Rostyslav Olshevskyi, Zhongyuan Zhao, Kevin S. Chan, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Fully Distributed Online Training of Graph Neural Networks in Networked Systems. CoRR abs/2412.06105 (2024) - [i88]Zhongyuan Zhao, Jake B. Perazzone, Gunjan Verma, Kevin S. Chan, Ananthram Swami, Santiago Segarra:
Joint Task Offloading and Routing in Wireless Multi-hop Networks Using Biased Backpressure Algorithm. CoRR abs/2412.15385 (2024) - 2023
- [j43]Lechuan Li
, Ruth Dannenfelser
, Yu Zhu, Nathaniel Hejduk, Santiago Segarra, Vicky Yao:
Joint embedding of biological networks for cross-species functional alignment. Bioinform. 39(9) (2023) - [j42]Yu Zhu, Santiago Segarra:
Hypergraphs with edge-dependent vertex weights: p-Laplacians and spectral clustering. Frontiers Big Data 6 (2023) - [j41]T. Mitchell Roddenberry, Santiago Segarra:
Limits of Dense Simplicial Complexes. J. Mach. Learn. Res. 24: 225:1-225:42 (2023) - [j40]Gabriel Egan, Mark Eisen, Alejandro Ribeiro, Santiago Segarra:
"I would I had that corporal soundness": Pervez Rizvi's Analysis of the Word Adjacency Network Method of Authorship Attribution. Digit. Scholarsh. Humanit. 38(4): 1494-1507 (2023) - [j39]Yu Zhu
, Ananthram Swami, Santiago Segarra
:
Free Energy Node Embedding via Generalized Skip-Gram With Negative Sampling. IEEE Trans. Knowl. Data Eng. 35(8): 8024-8036 (2023) - [j38]Samuel Rey
, T. Mitchell Roddenberry
, Santiago Segarra
, Antonio G. Marques
:
Enhanced Graph-Learning Schemes Driven by Similar Distributions of Motifs. IEEE Trans. Signal Process. 71: 3014-3027 (2023) - [j37]Fernando Gama
, Nicolas Zilberstein
, Martin Sevilla
, Richard G. Baraniuk
, Santiago Segarra
:
Unsupervised Learning of Sampling Distributions for Particle Filters. IEEE Trans. Signal Process. 71: 3852-3866 (2023) - [j36]Boning Li
, Gunjan Verma, Santiago Segarra
:
Graph-Based Algorithm Unfolding for Energy-Aware Power Allocation in Wireless Networks. IEEE Trans. Wirel. Commun. 22(2): 1359-1373 (2023) - [j35]Nicolas Zilberstein
, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal
, Santiago Segarra
:
Annealed Langevin Dynamics for Massive MIMO Detection. IEEE Trans. Wirel. Commun. 22(6): 3762-3776 (2023) - [j34]Zhongyuan Zhao
, Gunjan Verma, Chirag Rao, Ananthram Swami, Santiago Segarra
:
Link Scheduling Using Graph Neural Networks. IEEE Trans. Wirel. Commun. 22(6): 3997-4012 (2023) - [c92]Qing An, Mehdi Zafari
, Chris Dick, Santiago Segarra, Ashutosh Sabharwal, Rahman Doost-Mohammady:
ML-Based Feedback-Free Adaptive MCS Selection for Massive Multi-User MIMO. ACSSC 2023: 157-161 - [c91]Arindam Chowdhury, Santiago Paternain, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Learning Non-myopic Power Allocation in Constrained Scenarios. ACSSC 2023: 804-808 - [c90]Martin Sevilla, Nicolas Zilberstein, Benjamin Cox, Sara Pérez-Vieites, Víctor Elvira, Santiago Segarra:
State and Dynamics Estimation with the Kalman-Langevin filter. ACSSC 2023: 1372-1376 - [c89]Zhongyuan Zhao, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Enhanced Backpressure Routing Using Wireless Link Features. CAMSAP 2023: 271-275 - [c88]Sathiya Kumaran Mani
, Yajie Zhou
, Kevin Hsieh
, Santiago Segarra
, Trevor Eberl
, Eliran Azulai
, Ido Frizler
, Ranveer Chandra
, Srikanth Kandula
:
Enhancing Network Management Using Code Generated by Large Language Models. HotNets 2023: 196-204 - [c87]Sathiya Kumaran Mani
, Kevin Hsieh
, Santiago Segarra
, Trevor Eberl
, Ranveer Chandra
, Eliran Azulai
, Narayan Annamalai
, Deepak Bansal
, Srikanth Kandula
:
Securing Public Clouds using Dynamic Communication Graphs. HotNets 2023: 272-279 - [c86]Nicholas Glaze, Artun Bayer, Xiaoqian Jiang, Sean I. Savitz, Santiago Segarra:
Graph Representation Learning For Stroke Recurrence Prediction. ICASSP 2023: 1-5 - [c85]Madeline Navarro, Santiago Segarra:
Graphmad: Graph Mixup for Data Augmentation Using Data-Driven Convex Clustering. ICASSP 2023: 1-5 - [c84]T. Mitchell Roddenberry, Vincent P. Grande, Florian Frantzen
, Michael T. Schaub, Santiago Segarra:
Signal Processing On Product Spaces. ICASSP 2023: 1-5 - [c83]T. Mitchell Roddenberry, Santiago Segarra:
Windowed Fourier Analysis for Signal Processing on Graph Bundles. ICASSP 2023: 1-5 - [c82]Zhongyuan Zhao, Bojan Radojicic, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Delay-Aware Backpressure Routing Using Graph Neural Networks. ICASSP 2023: 1-5 - [c81]Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra:
Accelerated Massive MIMO Detector Based on Annealed Underdamped Langevin Dynamics. ICASSP 2023: 1-5 - [c80]Zhongyuan Zhao
, Ananthram Swami, Santiago Segarra:
Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems. ICLR 2023 - [c79]Boning Li, Timofey Efimov, Abhishek Kumar, Jose Cortes, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Learnable Digital Twin for Efficient Wireless Network Evaluation. MILCOM 2023: 661-666 - [i87]Lisa O'Bryan, Santiago Segarra, Jensine Paoletti, Stephanie Zajac, Margaret E. Beier, Ashutosh Sabharwal, Matthew A. Wettergreen, Eduardo Salas
:
Conversational Turn-taking as a Stochastic Process on Networks. CoRR abs/2301.04030 (2023) - [i86]Qing An, Santiago Segarra, Chris Dick, Ashutosh Sabharwal, Rahman Doost-Mohammady:
A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks. CoRR abs/2303.00958 (2023) - [i85]Arindam Chowdhury, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks. CoRR abs/2304.00446 (2023) - [i84]Boning Li, Jake B. Perazzone, Ananthram Swami, Santiago Segarra:
Learning to Transmit with Provable Guarantees in Wireless Federated Learning. CoRR abs/2304.09329 (2023) - [i83]Yu Zhu, Boning Li, Santiago Segarra:
Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering based on the 1-Laplacian. CoRR abs/2305.00462 (2023) - [i82]Boning Li, Timofey Efimov, Abhishek Kumar, Jose Cortes, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Learnable Digital Twin for Efficient Wireless Network Evaluation. CoRR abs/2306.06574 (2023) - [i81]Boning Li, Gojko Cutura, Ananthram Swami, Santiago Segarra:
Deep Demixing: Reconstructing the Evolution of Network Epidemics. CoRR abs/2306.07938 (2023) - [i80]Sathiya Kumaran Mani, Yajie Zhou, Kevin Hsieh, Santiago Segarra, Ranveer Chandra, Srikanth Kandula:
Enhancing Network Management Using Code Generated by Large Language Models. CoRR abs/2308.06261 (2023) - [i79]Madeline Navarro, Camille Olivia Little, Genevera I. Allen, Santiago Segarra:
Data Augmentation via Subgroup Mixup for Improving Fairness. CoRR abs/2309.07110 (2023) - [i78]Madeline Navarro, Santiago Segarra:
SC-MAD: Mixtures of Higher-order Networks for Data Augmentation. CoRR abs/2309.07453 (2023) - [i77]Victor M. Tenorio, Madeline Navarro, Santiago Segarra, Antonio G. Marques:
Recovering Missing Node Features with Local Structure-based Embeddings. CoRR abs/2309.09068 (2023) - [i76]Zhongyuan Zhao, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Enhanced Backpressure Routing Using Wireless Link Features. CoRR abs/2310.04364 (2023) - [i75]Pooria Namyar, Behnaz Arzani, Srikanth Kandula, Santiago Segarra, Daniel Crankshaw, Umesh Krishnaswamy, Ramesh Govindan, Himanshu Raj:
Solving Max-Min Fair Resource Allocations Quickly on Large Graphs. CoRR abs/2310.09699 (2023) - [i74]Pooria Namyar, Behnaz Arzani, Ryan Beckett, Santiago Segarra, Himanshu Raj, Umesh Krishnaswamy, Ramesh Govindan, Srikanth Kandula:
Finding Adversarial Inputs for Heuristics using Multi-level Optimization. CoRR abs/2311.12779 (2023) - [i73]Zhongyuan Zhao, Jake B. Perazzone, Gunjan Verma, Santiago Segarra:
Congestion-aware Distributed Task Offloading in Wireless Multi-hop Networks Using Graph Neural Networks. CoRR abs/2312.02471 (2023) - 2022
- [j33]Yu Zhu, Santiago Segarra
:
Hypergraph cuts with edge-dependent vertex weights. Appl. Netw. Sci. 7(1): 45 (2022) - [j32]Madeline Navarro, Yuhao Wang, Antonio G. Marques, Caroline Uhler, Santiago Segarra:
Joint Inference of Multiple Graphs from Matrix Polynomials. J. Mach. Learn. Res. 23: 76:1-76:35 (2022) - [j31]Paul Brown, Mark Eisen, Santiago Segarra
, Alejandro Ribeiro
, Gabriel Egan:
How the Word Adjacency Network (WAN) works. Digit. Scholarsh. Humanit. 37(2): 321-335 (2022) - [j30]Madeline Navarro
, Santiago Segarra
:
Joint Network Topology Inference Via a Shared Graphon Model. IEEE Trans. Signal Process. 70: 5549-5563 (2022) - [j29]T. Mitchell Roddenberry
, Fernando Gama
, Richard G. Baraniuk
, Santiago Segarra
:
On Local Distributions in Graph Signal Processing. IEEE Trans. Signal Process. 70: 5564-5577 (2022) - [j28]Samuel Rey
, Santiago Segarra
, Reinhard Heckel
, Antonio G. Marques
:
Untrained Graph Neural Networks for Denoising. IEEE Trans. Signal Process. 70: 5708-5723 (2022) - [c78]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: 53-57 - [c77]Yu Zhu, Boning Li, Santiago Segarra:
Hypergraph 1-Spectral Clustering with General Submodular Weights. IEEECONF 2022: 935-939 - [c76]Lisa O'Bryan, Santiago Segarra, Jensine Paoletti, Stephanie Zajac, Margaret E. Beier, Ashutosh Sabharwal, Matthew A. Wettergreen, Eduardo Salas
:
Conversational Turn-taking as a Stochastic Process on Networks. IEEECONF 2022: 1243-1247 - [c75]Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra:
Robust MIMO Detection using Hypernetworks with Learned Regularizers. EUSIPCO 2022: 1626-1630 - [c74]Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra:
Detection by Sampling: Massive MIMO Detector based on Langevin Dynamics. EUSIPCO 2022: 1651-1655 - [c73]Pooria Namyar, Behnaz Arzani, Ryan Beckett, Santiago Segarra
, Himanshu Raj, Srikanth Kandula:
Minding the gap between fast heuristics and their optimal counterparts. HotNets 2022: 138-144 - [c72]Boning Li, Ananthram Swami, Santiago Segarra
:
Power Allocation for Wireless Federated Learning Using Graph Neural Networks. ICASSP 2022: 5243-5247 - [c71]Arindam Chowdhury, Fernando Gama, Santiago Segarra
:
Stability Analysis of Unfolded WMMSE for Power Allocation. ICASSP 2022: 5298-5302 - [c70]Zhongyuan Zhao
, Ananthram Swami, Santiago Segarra
:
Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks. ICASSP 2022: 5308-5312 - [c69]Madeline Navarro, Santiago Segarra
:
Graphon-Aided Joint Estimation of Multiple Graphs. ICASSP 2022: 5458-5462 - [c68]Artun Bayer, Arindam Chowdhury, Santiago Segarra
:
Label Propagation Across Graphs: Node Classification Using Graph Neural Tangent Kernels. ICASSP 2022: 5483-5487 - [c67]Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra
:
Unrolling Particles: Unsupervised Learning of Sampling Distributions. ICASSP 2022: 5498-5502 - [c66]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: 5817-5821 - [c65]T. Mitchell Roddenberry, Florian Frantzen
, Michael T. Schaub, Santiago Segarra
:
Hodgelets: Localized Spectral Representations of Flows On Simplicial Complexes. ICASSP 2022: 5922-5926 - [c64]Yu Zhu, Boning Li, Santiago Segarra
:
Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering Based on the 1-Laplacian. ICASSP 2022: 8837-8841 - [c63]Zhongyuan Zhao
, Gunjan Verma, Ananthram Swami, Santiago Segarra
:
Delay-Oriented Distributed Scheduling Using Graph Neural Networks. ICASSP 2022: 8902-8906 - [c62]Benjamin Coleman, Santiago Segarra, Alexander J. Smola, Anshumali Shrivastava:
Graph Reordering for Cache-Efficient Near Neighbor Search. NeurIPS 2022 - [i72]Yu Zhu, Santiago Segarra:
Hypergraph Cuts with Edge-Dependent Vertex Weights. CoRR abs/2201.06084 (2022) - [i71]Boning Li, Gunjan Verma, Santiago Segarra:
Graph-based Algorithm Unfolding for Energy-aware Power Allocation in Wireless Networks. CoRR abs/2201.11799 (2022) - [i70]Madeline Navarro, Santiago Segarra:
Graphon-aided Joint Estimation of Multiple Graphs. CoRR abs/2202.05686 (2022) - [i69]T. Mitchell Roddenberry, Fernando Gama, Richard G. Baraniuk, Santiago Segarra:
On Local Distributions in Graph Signal Processing. CoRR abs/2202.10649 (2022) - [i68]Zhongyuan Zhao, Ananthram Swami, Santiago Segarra:
Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks. CoRR abs/2203.14339 (2022) - [i67]Yu Zhu, Santiago Segarra
:
Hypergraphs with Edge-Dependent Vertex Weights: p-Laplacians and Spectral Clustering. CoRR abs/2208.07457 (2022) - [i66]Madeline Navarro, Santiago Segarra
:
Joint Network Topology Inference via a Shared Graphon Model. CoRR abs/2209.08223 (2022) - [i65]Madeline Navarro, Santiago Segarra
:
GraphMAD: Graph Mixup for Data Augmentation using Data-Driven Convex Clustering. CoRR abs/2210.15721 (2022) - [i64]