Anastasios Kyrillidis

According to our database, Anastasios Kyrillidis authored at least 113 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

GIST: distributed training for large-scale graph convolutional networks.

Cameron R. Wolfe, Jingkang Yang, Fangshuo Liao, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis

J. Appl. Comput. Topol., October, 2024

Better schedules for low precision training of deep neural networks.

Cameron R. Wolfe, Anastasios Kyrillidis

Mach. Learn., June, 2024

How Much Pre-training Is Enough to Discover a Good Subnetwork?

Cameron R. Wolfe, Fangshuo Liao, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis

Trans. Mach. Learn. Res., 2024

When is Momentum Extragradient Optimal? A Polynomial-Based Analysis.

Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa

Trans. Mach. Learn. Res., 2024

A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm.

Junhyung Lyle Kim, Nai-Hui Chia, Anastasios Kyrillidis

CoRR, 2024

Fast FixMatch: Faster Semi-Supervised Learning with Curriculum Batch Size.

John Chen, Chen Dun, Anastasios Kyrillidis

Proceedings of the IEEE International Symposium on Information Theory, 2024

Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty.

Carlos Quintero-Peña, Wil Thomason, Zachary K. Kingston, Anastasios Kyrillidis, Lydia E. Kavraki

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

On the Error-Propagation of Inexact Hotelling's Deflation for Principal Component Analysis.

Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum, Anastasios Kyrillidis

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adaptive Federated Learning with Auto-Tuned Clients.

Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks.

Fangshuo Liao, Anastasios Kyrillidis

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography.

Junhyung Lyle Kim, Mohammad Taha Toghani, César A. Uribe, Anastasios Kyrillidis

IEEE Control. Syst. Lett., 2023

On the Error-Propagation of Inexact Deflation for Principal Component Analysis.

Fangshuo Liao, Junhyung Lyle Kim, Cruz Barnum, Anastasios Kyrillidis

CoRR, 2023

CrysFormer: Protein Structure Prediction via 3d Patterson Maps and Partial Structure Attention.

Chen Dun, Qiutai Pan, Shikai Jin, Ria Stevens, Mitchell D. Miller, George N. Phillips Jr., Anastasios Kyrillidis

CoRR, 2023

Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation.

Chen Dun, Mirian Hipolito Garcia, Guoqing Zheng, Ahmed Hassan Awadallah, Anastasios Kyrillidis, Robert Sim

CoRR, 2023

Fed-ZERO: Efficient Zero-shot Personalization with Federated Mixture of Experts.

Chen Dun, Mirian Hipolito Garcia, Guoqing Zheng, Ahmed Hassan Awadallah, Robert Sim, Anastasios Kyrillidis, Dimitrios Dimitriadis

CoRR, 2023

Accelerated Convergence of Nesterov's Momentum for Deep Neural Networks under Partial Strong Convexity.

Fangshuo Liao, Anastasios Kyrillidis

CoRR, 2023

Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time.

Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Using non-convex optimization in quantum process tomography: Factored gradient descent is tough to beat.

David A. Quiroga, Anastasios Kyrillidis

Proceedings of the IEEE International Conference on Rebooting Computing, 2023

Optimal Grasps and Placements for Task and Motion Planning in Clutter.

Carlos Quintero-Peña, Zachary K. Kingston, Tianyang Pan, Rahul Shome, Anastasios Kyrillidis, Lydia E. Kavraki

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Federated Learning Over Images: Vertical Decompositions and Pre-Trained Backbones Are Difficult to Beat.

Erdong Hu, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Strong Lottery Ticket Hypothesis with ε-perturbation.

Zheyang Xiong, Fangshuo Liao, Anastasios Kyrillidis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

LOFT: Finding Lottery Tickets through Filter-wise Training.

Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine, Anastasios Kyrillidis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Efficient and Light-Weight Federated Learning via Asynchronous Distributed Dropout.

Chen Dun, Mirian Hipolito Garcia, Chris Jermaine, Dimitrios Dimitriadis, Anastasios Kyrillidis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons.

Fangshuo Liao, Anastasios Kyrillidis

Trans. Mach. Learn. Res., 2022

Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training.

Binhang Yuan, Cameron R. Wolfe, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine

Proc. VLDB Endow., 2022

Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum.

Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa

CoRR, 2022

Cold Start Streaming Learning for Deep Networks.

Cameron R. Wolfe, Anastasios Kyrillidis

CoRR, 2022

DPMS: An ADD-Based Symbolic Approach for Generalized MaxSAT Solving.

Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang

CoRR, 2022

ResIST: Layer-wise decomposition of ResNets for distributed training.

Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Stackmix: a complementary mix algorithm.

John Chen, Samarth Sinha, Anastasios Kyrillidis

Proceedings of the Uncertainty in Artificial Intelligence, 2022

REX: Revisiting Budgeted Training with an Improved Schedule.

John Chen, Cameron R. Wolfe, Tasos Kyrillidis

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery.

Cameron R. Wolfe, Anastasios Kyrillidis

Proceedings of the Learning for Dynamics and Control Conference, 2022

Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum.

Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis

Proceedings of the Learning for Dynamics and Control Conference, 2022

PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication.

Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin

Proceedings of the Tenth International Conference on Learning Representations, 2022

No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds.

Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk

Proceedings of the IEEE International Conference on Acoustics, 2022

Demon: Improved Neural Network Training With Momentum Decay.

John Chen, Cameron R. Wolfe, Zhao Li, Anastasios Kyrillidis

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks.

Zhenwei Dai, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Anshumali Shrivastava

CoRR, 2021

Provably Efficient Lottery Ticket Discovery.

Cameron R. Wolfe, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis

CoRR, 2021

Momentum-inspired Low-Rank Coordinate Descent for Diagonally Constrained SDPs.

Junhyung Lyle Kim, Jose Antonio Lara Benitez, Mohammad Taha Toghani, Cameron R. Wolfe, Zhiwei Zhang, Anastasios Kyrillidis

CoRR, 2021

Fast quantum state reconstruction via accelerated non-convex programming.

Junhyung Lyle Kim, George Kollias, Amir Kalev, Ken X. Wei, Anastasios Kyrillidis

CoRR, 2021

GIST: Distributed Training for Large-Scale Graph Convolutional Networks.

Cameron R. Wolfe, Jingkang Yang, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis

CoRR, 2021

Solving hybrid Boolean constraints in continuous space via multilinear Fourier expansions.

Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang

Artif. Intell., 2021

Robust Optimization-based Motion Planning for high-DOF Robots under Sensing Uncertainty.

Carlos Quintero-Peña, Anastasios Kyrillidis, Lydia E. Kavraki

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Mitigating Deep Double Descent by Concatenating Inputs.

John Chen, Qihan Wang, Anastasios Kyrillidis

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective.

Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

On Continuous Local BDD-Based Search for Hybrid SAT Solving.

Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets.

T. Mitchell Roddenberry, Santiago Segarra, Anastasios Kyrillidis

CoRR, 2020

On Generalization of Adaptive Methods for Over-parameterized Linear Regression.

Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi

CoRR, 2020

ImCLR: Implicit Contrastive Learning for Image Classification.

John Chen, Samarth Sinha, Anastasios Kyrillidis

CoRR, 2020

Bayesian Coresets: An Optimization Perspective.

Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo

CoRR, 2020

Negative Sampling in Semi-Supervised learning.

John Chen, Vatsal Shah, Anastasios Kyrillidis

Proceedings of the 37th International Conference on Machine Learning, 2020

Low-rank regularization and solution uniqueness in over-parameterized matrix sensing.

Kelly Geyer, Anastasios Kyrillidis, Amir Kalev

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints.

Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Optimal Mini-Batch Size Selection for Fast Gradient Descent.

Michael P. Perrone, Haidar Khan, Changhoan Kim, Anastasios Kyrillidis, Jerry Quinn, Valentina Salapura

CoRR, 2019

Decaying momentum helps neural network training.

John Chen, Anastasios Kyrillidis

CoRR, 2019

Distributed Learning of Deep Neural Networks using Independent Subnet Training.

Binhang Yuan, Anastasios Kyrillidis, Christopher M. Jermaine

CoRR, 2019

SysML: The New Frontier of Machine Learning Systems.

Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar

CoRR, 2019

Learning Sparse Distributions using Iterative Hard Thresholding.

Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Compressing Gradient Optimizers via Count-Sketches.

Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

A Non-Euclidean Gradient Descent Framework for Non-Convex Matrix Factorization.

Ya-Ping Hsieh, Yu-Chun Kao, Rabeeh Karimi Mahabadi, Alp Yurtsever, Anastasios Kyrillidis, Volkan Cevher

IEEE Trans. Signal Process., 2018

Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

SIAM J. Imaging Sci., 2018

A Single-Phase, Proximal Path-Following Framework.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

Math. Oper. Res., 2018

Implicit regularization and solution uniqueness in over-parameterized matrix sensing.

Anastasios Kyrillidis, Amir Kalev

CoRR, 2018

Run Procrustes, Run! On the convergence of accelerated Procrustes Flow.

Anastasios Kyrillidis, Shashanka Ubaru, Georgios Kollias, Kristofer E. Bouchard

CoRR, 2018

Approximate Newton-based statistical inference using only stochastic gradients.

Tianyang Li, Anastasios Kyrillidis, Liu Liu, Constantine Caramanis

CoRR, 2018

Simple and practical algorithms for 𝓁_p-norm low-rank approximation.

Anastasios Kyrillidis

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

IHT dies hard: Provable accelerated Iterative Hard Thresholding.

Rajiv Khanna, Anastasios Kyrillidis

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Statistical Inference Using SGD.

Tianyang Li, Liu Liu, Anastasios Kyrillidis, Constantine Caramanis

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Provable quantum state tomography via non-convex methods.

Anastasios Kyrillidis, Amir Kalev, Dohyung Park, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi

CoRR, 2017

Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Location Estimation Using Crowdsourced Spatial Relations.

Georgios Skoumas, Dieter Pfoser, Anastasios Kyrillidis, Timos Sellis

ACM Trans. Spatial Algorithms Syst., 2016

Group-Sparse Model Selection: Hardness and Relaxations.

Luca Baldassarre, Nirav Bhan, Volkan Cevher, Anastasios Kyrillidis, Siddhartha Satpathi

IEEE Trans. Inf. Theory, 2016

Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions.

Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause

CoRR, 2016

Trading-off variance and complexity in stochastic gradient descent.

Vatsal Shah, Megasthenis Asteris, Anastasios Kyrillidis, Sujay Sanghavi

CoRR, 2016

Finding Low-rank Solutions to Matrix Problems, Efficiently and Provably.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

CoRR, 2016

Provable non-convex projected gradient descent for a class of constrained matrix optimization problems.

Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli, Constantine Caramanis, Sujay Sanghavi

CoRR, 2016

A Simple and Provable Algorithm for Sparse Diagonal CCA.

Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo, Russell A. Poldrack

Proceedings of the 33nd International Conference on Machine Learning, 2016

Dropping Convexity for Faster Semi-definite Optimization.

Srinadh Bhojanapalli, Anastasios Kyrillidis, Sujay Sanghavi

Proceedings of the 29th Conference on Learning Theory, 2016

Finding low-rank solutions to smooth convex problems via the Burer-Monteiro approach.

Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis, Sujay Sanghavi

Proceedings of the 54th Annual Allerton Conference on Communication, 2016

Learning Sparse Additive Models with Interactions in High Dimensions.

Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Convex Block-sparse Linear Regression with Expanders - Provably.

Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad, Quoc Tran-Dinh, Luca Baldassarre, Volkan Cevher

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Bipartite Correlation Clustering: Maximizing Agreements.

Megasthenis Asteris, Anastasios Kyrillidis, Dimitris S. Papailiopoulos, Alexandros G. Dimakis

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Compressive mining: fast and optimal data mining in the compressed domain.

Michail Vlachos, Nikolaos M. Freris, Anastasios Kyrillidis

VLDB J., 2015

Composite self-concordant minimization.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

J. Mach. Learn. Res., 2015

Structured Sparsity: Discrete and Convex approaches.

Anastasios Kyrillidis, Luca Baldassarre, Marwa El Halabi, Quoc Tran-Dinh, Volkan Cevher

CoRR, 2015

Linear Inverse Problems with Norm and Sparsity Constraints.

Volkan Cevher, Sina Jafarpour, Anastasios Kyrillidis

CoRR, 2015

Sparse PCA via Bipartite Matchings.

Megasthenis Asteris, Dimitris S. Papailiopoulos, Anastasios Kyrillidis, Alexandros G. Dimakis

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Stay on path: PCA along graph paths.

Megasthenis Asteris, Anastasios Kyrillidis, Alexandros G. Dimakis, Han-Gyol Yi, Bharath Chandrasekaran

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences.

Anastasios Kyrillidis

PhD thesis, 2014

Fixed-Rank Rayleigh Quotient Maximization by an MPSK Sequence.

Anastasios Kyrillidis, George N. Karystinos

IEEE Trans. Commun., 2014

An Inexact Proximal Path-Following Algorithm for Constrained Convex Minimization.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

SIAM J. Optim., 2014

Matrix Recipes for Hard Thresholding Methods.

Anastasios Kyrillidis, Volkan Cevher

J. Math. Imaging Vis., 2014

Location Estimation Using Crowdsourced Geospatial Narratives.

Georgios Skoumas, Dieter Pfoser, Anastasios Kyrillidis

CoRR, 2014

Fixed-rank Rayleigh Quotient Maximization by an $M$PSK Sequence.

Anastasios Kyrillidis, George N. Karystinos

CoRR, 2014

Provable deterministic leverage score sampling.

Dimitris S. Papailiopoulos, Anastasios Kyrillidis, Christos Boutsidis

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Approximate matrix multiplication with application to linear embeddings.

Anastasios Kyrillidis, Michail Vlachos, Anastasios Zouzias

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Non-uniform feature sampling for decision tree ensembles.

Anastasios Kyrillidis, Anastasios Zouzias

Proceedings of the IEEE International Conference on Acoustics, 2014

Improving Co-Cluster Quality with Application to Product Recommendations.

Michail Vlachos, Francesco Fusco, Charalampos Mavroforakis, Anastasios Kyrillidis, Vassilios G. Vassiliadis

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Scalable Sparse Covariance Estimation via Self-Concordance.

Anastasios Kyrillidis, Rabeeh Karimi Mahabadi, Quoc Tran-Dinh, Volkan Cevher

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Group-Sparse Model Selection: Hardness and Relaxations

Luca Baldassarre, Nirav Bhan, Volkan Cevher, Anastasios Kyrillidis

CoRR, 2013

Randomized Low-Memory Singular Value Projection

Stephen Becker, Volkan Cevher, Anastasios Kyrillidis

CoRR, 2013

A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions.

Quoc Tran-Dinh, Anastasios Kyrillidis, Volkan Cevher

Proceedings of the 30th International Conference on Machine Learning, 2013

Sparse projections onto the simplex.

Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch

Proceedings of the 30th International Conference on Machine Learning, 2013

Fast proximal algorithms for Self-concordant function minimization with application to sparse graph selection.

Anastasios Kyrillidis, Volkan Cevher

Proceedings of the IEEE International Conference on Acoustics, 2013

Sparse simplex projections for portfolio optimization.

Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch

Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

On quantifying qualitative geospatial data: a probabilistic approach.

Georgios Skoumas, Dieter Pfoser, Anastasios Kyrillidis

Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information, 2013

2012

Multi-Way Compressed Sensing for Sparse Low-Rank Tensors.

Nicholas D. Sidiropoulos, Anastasios Kyrillidis

IEEE Signal Process. Lett., 2012

Sparse projections onto the simplex

Anastasios Kyrillidis, Stephen Becker, Volkan Cevher

CoRR, 2012

MATRIX ALPS: Accelerated low rank and sparse matrix reconstruction.

Anastasios Kyrillidis, Volkan Cevher

Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Combinatorial selection and least absolute shrinkage via the Clash algorithm.

Anastasios Kyrillidis, Volkan Cevher

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

Hard thresholding with norm constraints.

Anastasios Kyrillidis, Gilles Puy, Volkan Cevher

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Rank-deficient quadratic-form maximization over M-phase alphabet: Polynomial-complexity solvability and algorithmic developments.

Anastasios Kyrillidis, George N. Karystinos

Proceedings of the IEEE International Conference on Acoustics, 2011

Recipes on hard thresholding methods.

Anastasios Kyrillidis, Volkan Cevher

Proceedings of the 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2011