How good is the Shapley value-based approach to the influence maximization problem? - Kamil Adamczewski; Szymon Matejczyk; Tomasz P. Michalak (ECAI, 2014)

Subgraph matching using compactness prior for robust feature correspondence. - Yumin Suh; Kamil Adamczewski; Kyoung Mu Lee (CVPR, 2015)

Discrete Tabu Search for Graph Matching. - Kamil Adamczewski; Yumin Suh; Kyoung Mu Lee (ICCV, 2015)

The Smoothed Pólya-Vinogradov Inequality. - Kamil Adamczewski; Enrique Treviño (Integers, 2015)

Radial and Directional Posteriors for Bayesian Neural Networks. - ChangYong Oh; Kamil Adamczewski; Mijung Park (CoRR, 2019)

Neuron ranking - an informed way to condense convolutional neural networks architecture. - Kamil Adamczewski; Mijung Park (CoRR, 2019)

Radial and Directional Posteriors for Bayesian Deep Learning. - ChangYong Oh; Kamil Adamczewski; Mijung Park (AAAI, 2020)

Differentially Private Mean Embeddings with Random Features (DP-MERF) for Simple & Practical Synthetic Data Generation. - Frederik Harder; Kamil Adamczewski; Mijung Park (CoRR, 2020)

Q-FIT: The Quantifiable Feature Importance Technique for Explainable Machine Learning. - Kamil Adamczewski; Frederik Harder; Mijung Park (CoRR, 2020)

Dirichlet Pruning for Neural Network Compression. - Kamil Adamczewski; Mijung Park (CoRR, 2020)

Dirichlet Pruning for Convolutional Neural Networks. - Kamil Adamczewski; Mijung Park (AISTATS, 2021)

DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation. - Frederik Harder; Kamil Adamczewski; Mijung Park (AISTATS, 2021)

Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completion. - Kamil Adamczewski; Christos Sakaridis; Vaishakh Patil; Luc Van Gool (CoRL, 2022)

Revisiting Random Channel Pruning for Neural Network Compression. - Yawei Li 001; Kamil Adamczewski; Wen Li 001; Shuhang Gu; Radu Timofte; Luc Van Gool (CVPR, 2022)

Hermite Polynomial Features for Private Data Generation. - Margarita Vinaroz; Mohammad-Amin Charusaie; Frederik Harder; Kamil Adamczewski; Mijung Park (ICML, 2022)

Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation. - Yilin Yang; Kamil Adamczewski; Danica J. Sutherland; Xiaoxiao Li; Mijung Park (CoRR, 2023)

Differential Privacy Meets Neural Network Pruning. - Kamil Adamczewski; Mijung Park (CoRR, 2023)

Pre-Pruning and Gradient-Dropping Improve Differentially Private Image Classification. - Kamil Adamczewski; Yingchen He; Mijung Park (CoRR, 2023)

Less is More: Discovering Redundancies in Data and Neural Network Models for Improved Efficiency, Intrerpretability and Privacy. - Kamil Adamczewski (2023)

Zero-Waste Machine Learning. - Tomasz Trzcinski; Bartlomiej Twardowski; Bartosz Zielinski 001; Kamil Adamczewski; Bartosz Wójcik (ECAI, 2024)

AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale. - Adam Pardyl; Michal Wronka; Maciej Wolczyk; Kamil Adamczewski; Tomasz Trzcinski; Bartosz Zielinski 001 (ECCV (21), 2024)

Scaling Laws for Fine-Grained Mixture of Experts. - Jan Ludziejewski; Jakub Krajewski; Kamil Adamczewski; Maciej Pióro; Michal Krutul; Szymon Antoniak; Kamil Ciebiera; Krystian Król; Tomasz Odrzygózdz; Piotr Sankowski; Marek Cygan; Sebastian Jaszczur (ICML, 2024)

Joint or Disjoint: Mixing Training Regimes for Early-Exit Models. - Bartlomiej Krzepkowski; Monika Michaluk; Franciszek Szarwacki; Piotr Kubaty; Jary Pomponi; Tomasz Trzcinski; Bartosz Wójcik; Kamil Adamczewski (CoRR, 2024)

Shapley Pruning for Neural Network Compression. - Kamil Adamczewski; Yawei Li 001; Luc Van Gool (CoRR, 2024)

Differentially Private Neural Tangent Kernels (DP-NTK) for Privacy-Preserving Data Generation. - Yi Yang 001; Kamil Adamczewski; Xiaoxiao Li; Danica J. Sutherland; Mijung Park (J. Artif. Intell. Res., 2024)

Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient. - Jan Ludziejewski; Maciej Pióro; Jakub Krajewski; Maciej Stefaniak; Michal Krutul; Jan Malasnicki; Marek Cygan; Piotr Sankowski; Kamil Adamczewski; Piotr Milos; Sebastian Jaszczur (CoRR, 2025)

Projected Compression: Trainable Projection for Efficient Transformer Compression. - Maciej Stefaniak; Michal Krutul; Jan Malasnicki; Maciej Pióro; Jakub Krajewski; Sebastian Jaszczur; Marek Cygan; Kamil Adamczewski; Jan Ludziejewski (CoRR, 2025)

Decoupled Relative Learning Rate Schedules. - Jan Ludziejewski; Jan Malasnicki; Maciej Pióro; Michal Krutul; Kamil Ciebiera; Maciej Stefaniak; Jakub Krajewski; Piotr Sankowski; Marek Cygan; Kamil Adamczewski; Sebastian Jaszczur (CoRR, 2025)

μ-Parametrization for Mixture of Experts. - Jan Malasnicki; Kamil Ciebiera; Mateusz Borun; Maciej Pióro; Jan Ludziejewski; Maciej Stefaniak; Michal Krutul; Sebastian Jaszczur; Marek Cygan; Kamil Adamczewski; Jakub Krajewski (CoRR, 2025)