Conference paper
COUNTERFACTUAL CONCEPT BOTTLENECK MODELS
Gabriele Dominici, Pietro Barbiero, et al.
ICLR 2025
A universal data compression algorithm is described which is capable of compressing long strings generated by a “finitely generated” source, with a near optimum per symbol length without prior knowledge of the source. This class of sources may be viewed as a generalization of Markov sources to random fields. Moreover, the algorithm does not require a working storage much larger than that needed to describe the source generating parameters. © 1983 IEEE
Gabriele Dominici, Pietro Barbiero, et al.
ICLR 2025
Joel L. Wolf, Mark S. Squillante, et al.
IEEE Transactions on Knowledge and Data Engineering
Robert G. Farrell, Catalina M. Danis, et al.
RecSys 2012
Robert C. Durbeck
IEEE TACON