Sangkyun Lee

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Libra-CAM: An Activation-Based Attribution Based on the Linear Approximation of Deep Neural Nets and Threshold Calibration.

[BibT_eX]

[DOI]

Sungmin Han

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Improving the Robustness of Model Compression by On-Manifold Adversarial Training.

[BibT_eX]

[DOI]

Junhyung Kwon

Future Internet, 2021

Data Quality Measures and Efficient Evaluation Algorithms for Large-Scale High-Dimensional Data.

[BibT_eX]

[DOI]

Hyeongmin Cho

CoRR, 2021

Hunt for Unseen Intrusion: Multi-Head Self-Attention Neural Detector.

[BibT_eX]

[DOI]

IEEE Access, 2021

2019

Structure Learning of Gaussian Markov Random Fields with False Discovery Rate Control.

[BibT_eX]

[DOI]

Piotr Sobczyk

Malgorzata Bogdan

Symmetry, 2019

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems.

[BibT_eX]

[DOI]

Jeonghyun Lee

CoRR, 2019

2016

Integer undirected graphical models for resource-constrained systems.

[BibT_eX]

[DOI]

Nico Piatkowski

Neurocomputing, 2016

Knowledge Discovery from Complex High Dimensional Data.

[BibT_eX]

[DOI]

Andreas Holzinger

Proceedings of the Solving Large Scale Learning Tasks. Challenges and Algorithms, 2016

Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm.

[BibT_eX]

[DOI]

Damian Brzyski

Malgorzata Bogdan

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

2015

Signature Selection for Grouped Features with a Case Study on Exon Microarrays.

[BibT_eX]

[DOI]

Proceedings of the Feature Selection for Data and Pattern Recognition, 2015

2014

Sparse Inverse Covariance Estimation for Graph Representation of Feature Structure.

[BibT_eX]

[DOI]

Proceedings of the Interactive Knowledge Discovery and Data Mining in Biomedical Informatics, 2014

The Integer Approximation of Undirected Graphical Models.

[BibT_eX]

[DOI]

Nico Piatkowski

Proceedings of the ICPRAM 2014, 2014

Kernel Completion for Learning Consensus Support Vector Machines in Bandwidth-limited Sensor Networks.

[BibT_eX]

[DOI]

Christian Pölitz

Proceedings of the ICPRAM 2014, 2014

Kernel Matrix Completion for Learning Nearly Consensus Support Vector Machines.

[BibT_eX]

[DOI]

Christian Pölitz

Proceedings of the Pattern Recognition Applications and Methods, 2014

Characterization of Subgroup Patterns from Graphical Representation of Genomic Data.

[BibT_eX]

[DOI]

Proceedings of the Brain Informatics and Health - International Conference, 2014

2013

Spatio-temporal random fields: compressible representation and distributed estimation.

[BibT_eX]

[DOI]

Nico Piatkowski

Mach. Learn., 2013

2012

Manifold Identification in Dual Averaging for Regularized Stochastic Online Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2012

Separable Approximate Optimization of Support Vector Machines for Distributed Sensing.

[BibT_eX]

[DOI]

Marco Stolpe

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

Improving Confidence of Dual Averaging Stochastic Online Learning via Aggregation.

[BibT_eX]

[DOI]

Proceedings of the KI 2012: Advances in Artificial Intelligence, 2012

ASSET: Approximate Stochastic Subgradient Estimation Training for Support Vector Machines.

[BibT_eX]

Proceedings of the ICPRAM 2012, 2012

2011

Approximate Stochastic Subgradient Estimation Training for Support Vector Machines

[BibT_eX]

[DOI]

CoRR, 2011

Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning.

[BibT_eX]

[DOI]

Proceedings of the 28th International Conference on Machine Learning, 2011

2009

Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines.

[BibT_eX]

[DOI]