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cs.LG2025

Learning Distributions over Permutations and Rankings with Factorized Representations

Daniel Severo, Brian Karrer, Niklas Nolte

Learning distributions over permutations is a fundamental problem in machine learning, with applications in ranking, combinatorial optimization, structured prediction, and data ass…

cs.LG2024

Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective

Neta Shaul, Itai Gat, Marton Havasi +6

The design space of discrete-space diffusion or flow generative models are significantly less well-understood than their continuous-space counterparts, with many works focusing onl…

cs.LG2024

Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding

Daniel Severo, Ashish Khisti, Alireza Makhzani

We present an optimal method for encoding cluster assignments of arbitrary data sets. Our method, Random Cycle Coding (RCC), encodes data sequentially and sends assignment informat…

cs.LG2024

Entropy Coding of Unordered Data Structures

Julius Kunze, Daniel Severo, Giulio Zani +2

We present shuffle coding, a general method for optimal compression of sequences of unordered objects using bits-back coding. Data structures that can be compressed using shuffle c…

cs.LG2023

Random Edge Coding: One-Shot Bits-Back Coding of Large Labeled Graphs

Daniel Severo, James Townsend, Ashish Khisti +1

We present a one-shot method for compressing large labeled graphs called Random Edge Coding. When paired with a parameter-free model based on Pólya's Urn, the worst-case computatio…