Igor T. Podolak — accepted AI-conference papers

2025

LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection

Łukasz Struski, Michal B. Bednarczyk, Igor T. Podolak, Jacek Tabor

ICML 2025poster

We present a novel technique for constructing differentiable order-type operations, including soft ranking, soft top-k selection, and soft permutations. Our approach leverages an efficient closed-form formula for the inverse of the function LapSum, defined as the sum of Laplace distributions. This f…

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2021

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks

Maciej Wolczyk, Bartosz Wójcik, Klaudia Bałazy, Igor T. Podolak, Jacek Tabor, Marek Śmieja +1

NeurIPS 2021poster

The problem of reducing processing time of large deep learning models is a fundamental challenge in many real-world applications. Early exit methods strive towards this goal by attaching additional Internal Classifiers (ICs) to intermediate layers of a neural network. ICs can quickly return predicti…

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