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Kamil Adamczewski
Kamil Adamczewski
Max Planck Institute for Intelligent Systems
Bestätigte E-Mail-Adresse bei ideas-ncbr.pl
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Zitiert von
Zitiert von
Jahr
Revisiting random channel pruning for neural network compression
Y Li, K Adamczewski, W Li, S Gu, R Timofte, L Van Gool
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
1152022
Dp-merf: Differentially private mean embeddings with randomfeatures for practical privacy-preserving data generation
F Harder, K Adamczewski, M Park
International conference on artificial intelligence and statistics, 1819-1827, 2021
1042021
Discrete tabu search for graph matching
K Adamczewski, Y Suh, K Mu Lee
Proceedings of the IEEE international conference on computer vision, 109-117, 2015
552015
Subgraph matching using compactness prior for robust feature correspondence
Y Suh, K Adamczewski, K Mu Lee
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
292015
Scaling laws for fine-grained mixture of experts
J Krajewski, J Ludziejewski, K Adamczewski, M Pióro, M Krutul, ...
arXiv preprint arXiv:2402.07871, 2024
262024
Radial and directional posteriors for bayesian deep learning
C Oh, K Adamczewski, M Park
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5298-5305, 2020
26*2020
Hermite polynomial features for private data generation
M Vinaroz, MA Charusaie, F Harder, K Adamczewski, MJ Park
International Conference on Machine Learning, 22300-22324, 2022
222022
Differentially private neural tangent kernels for privacy-preserving data generation
Y Yang, K Adamczewski, DJ Sutherland, X Li, M Park
arXiv preprint arXiv:2303.01687, 2023
102023
Dirichlet pruning for convolutional neural networks
K Adamczewski, M Park
International Conference on Artificial Intelligence and Statistics, 3637-3645, 2021
9*2021
How good is the Shapley value-based approach to the influence maximization problem?
K Adamczewski, S Matejczyk, TP Michalak
arXiv preprint arXiv:1409.7830, 2014
8*2014
Adaglimpse: Active visual exploration with arbitrary glimpse position and scale
A Pardyl, M Wronka, M Wołczyk, K Adamczewski, T Trzciński, B Zieliński
European Conference on Computer Vision, 112-129, 2025
32025
Differential privacy meets neural network pruning
K Adamczewski, M Park
arXiv preprint arXiv:2303.04612, 2023
32023
Bayesian importance of features (bif)
K Adamczewski, F Harder, M Park
arXiv preprint arXiv:2010.13872, 2020
32020
The Smoothed Pólya-Vinogradov Inequality.
K Adamczewski, E Trevino
Integers 15, A20, 2015
22015
SADMoE: Exploiting Activation Sparsity with Dynamic-k Gating
F Szatkowski, B Wójcik, M Piórczyński, K Adamczewski
arXiv e-prints, arXiv: 2310.04361, 2023
12023
Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completion
K Adamczewski, C Sakaridis, V Patil, L Van Gool
Conference on Robot Learning, 561-570, 2023
12023
Neuron ranking--an informed way to condense convolutional neural networks architecture
K Adamczewski, M Park
arXiv preprint arXiv:1907.02519, 2019
12019
Differentially Private Neural Tangent Kernels (DP-NTK) for Privacy-Preserving Data Generation
Y Yang, K Adamczewski, X Li, DJ Sutherland, M Park
Journal of Artificial Intelligence Research 81, 683-700, 2024
2024
Shapley Pruning for Neural Network Compression
K Adamczewski, Y Li, L van Gool
arXiv preprint arXiv:2407.15875, 2024
2024
Joint or Disjoint: Mixing Training Regimes for Early-Exit Models
B Krzepkowski, M Michaluk, F Szarwacki, P Kubaty, J Pomponi, ...
arXiv preprint arXiv:2407.14320, 2024
2024
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