Anastasios Kyrillidis

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Volkan CevherAssociate Professor, LIONS, EPFL. Amazon Scholar.Dirección de correo verificada de epfl.ch
Sujay SanghaviAssociate Professor, Electrical and Computer Engineering, University of Texas, AustinDirección de correo verificada de mail.utexas.edu
Cameron WolfePhD Student, Rice UniversityDirección de correo verificada de rice.edu
Constantine CaramanisProfessor of Electrical and Computer Engineering, UT AustinDirección de correo verificada de utexas.edu
Chen DunPh.D, Rice UniversityDirección de correo verificada de rice.edu
Dohyung ParkThe University of Texas at AustinDirección de correo verificada de utexas.edu
Quoc Tran-DinhDepartment of Statistics and Operations Research, UNCDirección de correo verificada de email.unc.edu
Srinadh BhojanapalliResearch Scientist, Google ResearchDirección de correo verificada de google.com
John ChenRice UniversityDirección de correo verificada de rice.edu
Fangshuo LiaoPh.D. Student, Rice UniversityDirección de correo verificada de rice.edu
Chris JermaineAssociate Professor of Computer Science, Rice UniversityDirección de correo verificada de cs.rice.edu
Amir KalevInformation Sciences Institute, University of Southern CaliforniaDirección de correo verificada de isi.edu
Junhyung Lyle KimPh.D. Student, Computer Science Department, Rice UniversityDirección de correo verificada de rice.edu
Stephen BeckerAssociate Professor at University of ColoradoDirección de correo verificada de colorado.edu
Megasthenis AsterisUniversity of Texas at AustinDirección de correo verificada de utexas.edu
Richard BaraniukC. Sidney Burrus Professor, Electrical & Computer Engineering, Rice UniversityDirección de correo verificada de rice.edu
Dimitris PapailiopoulosAssociate Professor, University of Wisconsin-MadisonDirección de correo verificada de papail.io
Vatsal ShahAmazonDirección de correo verificada de utexas.edu
Christoph KochProfessor of Computer Science, EPFLDirección de correo verificada de epfl.ch
Rajiv KhannaAssistant Prof, PurdueCSDirección de correo verificada de purdue.edu

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Anastasios Kyrillidis

Assistant Professor, Computer Science Department, Rice University

Dirección de correo verificada de rice.edu - Página principal

Optimization Nonconvex optimization Large scale optimization


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach D Park, A Kyrillidis, C Caramanis, S Sanghavi Artificial Intelligence and Statistics, pp. 65-74, 2016	183	2016
Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016	183	2016
Multi-way compressed sensing for sparse low-rank tensors ND Sidiropoulos, A Kyrillidis IEEE Signal Processing Letters, 1-1, 2012	162	2012
Finding low-rank solutions via non-convex matrix factorization, efficiently and provably D Park, A Kyrillidis, C Caramanis, S Sanghavi SIAM Journal on Imaging Sciences 11 (4), 2165–2204, 2018	153*	2018
Current progress and open challenges for applying deep learning across the biosciences N Sapoval, A Aghazadeh, MG Nute, DA Antunes, A Balaji, R Baraniuk, ... Nature Communications 13 (1), 1728, 2022	146	2022
Sparse projections onto the simplex A Kyrillidis, S Becker, V Cevher, C Koch Proceedings of The 30th International Conference on Machine Learning 28, 235–243, 2012	108*	2012
Composite self-concordant minimization. Q Tran-Dinh, A Kyrillidis, V Cevher J. Mach. Learn. Res. 16 (1), 371-416, 2015	101	2015
Provable deterministic leverage score sampling D Papailiopoulos, A Kyrillidis, C Boutsidis Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	95	2014
Matrix recipes for hard thresholding methods A Kyrillidis, V Cevher Journal of Mathematical Imaging and Vision, 2012	85	2012
Provable compressed sensing quantum state tomography via non-convex methods A Kyrillidis, A Kalev, D Park, S Bhojanapalli, C Caramanis, S Sanghavi npj Quantum Information 4 (1), 36, 2018	73*	2018
Recipes on hard thresholding methods A Kyrillidis, V Cevher 2011 4th IEEE International Workshop on Computational Advances in Multi …, 2011	54	2011
PipeGCN: Efficient full-graph training of graph convolutional networks with pipelined feature communication C Wan, Y Li, CR Wolfe, A Kyrillidis, NS Kim, Y Lin arXiv preprint arXiv:2203.10428, 2022	52	2022
Statistical inference using SGD T Li, L Liu, A Kyrillidis, C Caramanis Thirty-Second AAAI Conference on Artificial Intelligence, 3571-3578, 2017	49	2017
Combinatorial selection and least absolute shrinkage via the CLASH algorithm A Kyrillidis, V Cevher 2012 IEEE International Symposium on Information Theory Proceedings, 2216-2220, 2012	48*	2012
Distributed learning of fully connected neural networks using independent subnet training B Yuan, CR Wolfe, C Dun, Y Tang, A Kyrillidis, C Jermaine Proceedings of the VLDB Endowment 15 (8), 2022	46*	2022
Mlsys: The new frontier of machine learning systems A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ... arXiv preprint arXiv:1904.03257, 2019	45	2019
Group-sparse model selection: Hardness and relaxations L Baldassarre, N Bhan, V Cevher, A Kyrillidis, S Satpathi IEEE Transactions on Information Theory 62 (11), 6508-6534, 2016	38	2016
IHT dies hard: Provable accelerated iterative hard thresholding R Khanna, A Kyrillidis Proceedings of the Twenty-First International Conference on Artificial …, 2017	37	2017
Sparse PCA via Bipartite Matchings M Asteris, D Papailiopoulos, A Kyrillidis, A Dimakis Neural Information Processing Systems 2015 28, 1-9, 2015	37	2015
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions QT Dinh, A Kyrillidis, V Cevher Proceedings of The 30th International Conference on Machine Learning 28, 271–279, 2013	36	2013

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