Kamil Adamczewski

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 20

Top Topics

Subgraph Matching

Pruning Methods

Top Venues

Publications

Bartlomiej Krzepkowski, Monika Michaluk, Franciszek Szarwacki, Piotr Kubaty, Jary Pomponi, Tomasz Trzcinski, Bartosz Wójcik, Kamil Adamczewski
Joint or Disjoint: Mixing Training Regimes for Early-Exit Models. CoRR (2024)
Adam Pardyl, Michal Wronka, Maciej Wolczyk, Kamil Adamczewski, Tomasz Trzcinski, Bartosz Zielinski
AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale. CoRR (2024)
Kamil Adamczewski, Yawei Li, Luc Van Gool
Shapley Pruning for Neural Network Compression. CoRR (2024)
Jakub Krajewski, Jan Ludziejewski, Kamil Adamczewski, Maciej Pióro, Michal Krutul, Szymon Antoniak, Kamil Ciebiera, Krystian Król, Tomasz Odrzygózdz, Piotr Sankowski, Marek Cygan, Sebastian Jaszczur
Scaling Laws for Fine-Grained Mixture of Experts. CoRR (2024)
Yilin Yang, Kamil Adamczewski, Danica J. Sutherland, Xiaoxiao Li, Mijung Park
Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation. CoRR (2023)
Kamil Adamczewski, Christos Sakaridis, Vaishakh Patil, Luc Van Gool
Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completion. CoRR (2023)
Kamil Adamczewski, Mijung Park
Differential Privacy Meets Neural Network Pruning. CoRR (2023)
Kamil Adamczewski, Yingchen He, Mijung Park
Pre-Pruning and Gradient-Dropping Improve Differentially Private Image Classification. CoRR (2023)
Kamil Adamczewski, Christos Sakaridis, Vaishakh Patil, Luc Van Gool
Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completion. CoRL (2022)
Margarita Vinaroz, Mohammad-Amin Charusaie, Frederik Harder, Kamil Adamczewski, Mijung Park
Hermite Polynomial Features for Private Data Generation. ICML (2022)
Yawei Li, Kamil Adamczewski, Wen Li, Shuhang Gu, Radu Timofte, Luc Van Gool
Revisiting Random Channel Pruning for Neural Network Compression. CVPR (2022)
Yawei Li, Kamil Adamczewski, Wen Li, Shuhang Gu, Radu Timofte, Luc Van Gool
Revisiting Random Channel Pruning for Neural Network Compression. CoRR (2022)
Frederik Harder, Kamil Adamczewski, Mijung Park
DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation. AISTATS (2021)
Kamil Adamczewski, Mijung Park
Dirichlet Pruning for Convolutional Neural Networks. AISTATS (2021)
Frederik Harder, Kamil Adamczewski, Mijung Park
Differentially Private Mean Embeddings with Random Features (DP-MERF) for Simple & Practical Synthetic Data Generation. CoRR (2020)
Kamil Adamczewski, Frederik Harder, Mijung Park
Q-FIT: The Quantifiable Feature Importance Technique for Explainable Machine Learning. CoRR (2020)
ChangYong Oh, Kamil Adamczewski, Mijung Park
Radial and Directional Posteriors for Bayesian Deep Learning. AAAI (2020)
Kamil Adamczewski, Mijung Park
Dirichlet Pruning for Neural Network Compression. CoRR (2020)
ChangYong Oh, Kamil Adamczewski, Mijung Park
Radial and Directional Posteriors for Bayesian Neural Networks. CoRR (2019)
Kamil Adamczewski, Mijung Park
Neuron ranking - an informed way to condense convolutional neural networks architecture. CoRR (2019)
Kamil Adamczewski, Enrique Treviño
The Smoothed Pólya-Vinogradov Inequality. Integers 15 (2015)
Yumin Suh, Kamil Adamczewski, Kyoung Mu Lee
Subgraph matching using compactness prior for robust feature correspondence. CVPR (2015)
Kamil Adamczewski, Yumin Suh, Kyoung Mu Lee
Discrete Tabu Search for Graph Matching. ICCV (2015)
Kamil Adamczewski, Szymon Matejczyk, Tomasz P. Michalak
How good is the Shapley value-based approach to the influence maximization problem? CoRR (2014)
Kamil Adamczewski, Szymon Matejczyk, Tomasz P. Michalak
How good is the Shapley value-based approach to the influence maximization problem? ECAI (2014)