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Electronic Colloquium on Computational Complexity

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Reports tagged with distribution learning:
TR15-010 | 19th January 2015
Maciej Li\'skiewicz, Rüdiger Reischuk, Ulrich Wölfel

Security Levels in Steganography -- Insecurity does not Imply Detectability

This paper takes a fresh look at security notions for steganography --
the art of encoding secret messages into unsuspicious covertexts
such that an adversary cannot distinguish the resulting stegotexts from original covertexts.
Stegosystems that fulfill the security notion used so far, however, are quite inefficient.
This ... more >>>

TR16-177 | 11th November 2016
Ilias Diakonikolas, Daniel Kane, Alistair Stewart

Statistical Query Lower Bounds for Robust Estimation of High-dimensional Gaussians and Gaussian Mixtures

Revisions: 1

We prove the first {\em Statistical Query lower bounds} for two fundamental high-dimensional learning problems involving Gaussian distributions: (1) learning Gaussian mixture models (GMMs), and (2) robust (agnostic) learning of a single unknown mean Gaussian. In particular, we show a {\em super-polynomial gap} between the (information-theoretic) sample complexity and the ... more >>>

TR18-079 | 19th April 2018
Jayadev Acharya, Clement Canonne, Himanshu Tyagi

Distributed Simulation and Distributed Inference

Revisions: 1

Independent samples from an unknown probability distribution $\mathbf{p}$ on a domain of size $k$ are distributed across $n$ players, with each player holding one sample. Each player can communicate $\ell$ bits to a central referee in a simultaneous message passing (SMP) model of communication to help the referee infer a ... more >>>

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