Kamil Adamczewski

Yawei Li

Luc Van Gool

CoRR, 2024

Joint or Disjoint: Mixing Training Regimes for Early-Exit Models.

[BibT_eX]

[DOI]

Bartlomiej Krzepkowski

CoRR, 2024

Scaling Laws for Fine-Grained Mixture of Experts.

[BibT_eX]

[DOI]

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

AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

Zero-Waste Machine Learning.

[BibT_eX]

[DOI]

Tomasz Trzcinski

Bartlomiej Twardowski

Bartosz Zielinski

Bartosz Wójcik

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Less is More: Discovering Redundancies in Data and Neural Network Models for Improved Efficiency, Intrerpretability and Privacy.

[BibT_eX]

[DOI]

PhD thesis, 2023

Pre-Pruning and Gradient-Dropping Improve Differentially Private Image Classification.

[BibT_eX]

[DOI]

Yingchen He

CoRR, 2023

Differential Privacy Meets Neural Network Pruning.

[BibT_eX]

[DOI]

CoRR, 2023

Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Hermite Polynomial Features for Private Data Generation.

[BibT_eX]

[DOI]

Margarita Vinaroz

Mohammad-Amin Charusaie

Proceedings of the International Conference on Machine Learning, 2022

Revisiting Random Channel Pruning for Neural Network Compression.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completion.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2022

2021

DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation.

[BibT_eX]

[DOI]

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

Dirichlet Pruning for Convolutional Neural Networks.

[BibT_eX]

[DOI]

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

2020

Dirichlet Pruning for Neural Network Compression.

[BibT_eX]

[DOI]

CoRR, 2020

Q-FIT: The Quantifiable Feature Importance Technique for Explainable Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Differentially Private Mean Embeddings with Random Features (DP-MERF) for Simple & Practical Synthetic Data Generation.

[BibT_eX]

[DOI]

CoRR, 2020

Radial and Directional Posteriors for Bayesian Deep Learning.

[BibT_eX]

[DOI]

ChangYong Oh

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

2019

Neuron ranking - an informed way to condense convolutional neural networks architecture.

[BibT_eX]

[DOI]

CoRR, 2019

Radial and Directional Posteriors for Bayesian Neural Networks.

[BibT_eX]

[DOI]

ChangYong Oh

CoRR, 2019

2015

The Smoothed Pólya-Vinogradov Inequality.

[BibT_eX]

[DOI]

Enrique Treviño

Integers, 2015

Discrete Tabu Search for Graph Matching.

[BibT_eX]

[DOI]

Yumin Suh

Kyoung Mu Lee

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Subgraph matching using compactness prior for robust feature correspondence.

[BibT_eX]

[DOI]

Yumin Suh

Kyoung Mu Lee

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

How good is the Shapley value-based approach to the influence maximization problem?

[BibT_eX]

[DOI]