3 citations · 5 across the 4 of their papers we have counts for
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Scaling Laws for Fine-Grained Mixture of Experts
Jakub Krajewski, Jan Ludziejewski, Kamil Adamczewski +9
Mixture of Experts (MoE) models have emerged as a primary solution for reducing the computational cost of Large Language Models. In this work, we analyze their scaling properties,…
Lidar Line Selection with Spatially-Aware Shapley Value for Cost-Efficient Depth Completion
Kamil Adamczewski, Christos Sakaridis, Vaishakh Patil +1
Lidar is a vital sensor for estimating the depth of a scene. Typical spinning lidars emit pulses arranged in several horizontal lines and the monetary cost of the sensor increases…
Differential Privacy Meets Neural Network Pruning
Kamil Adamczewski, Mijung Park
A major challenge in applying differential privacy to training deep neural network models is scalability.The widely-used training algorithm, differentially private stochastic gradi…