Zobrazeno 1 - 10
of 205
pro vyhledávání: '"Linder, Tamás"'
In the classical lossy source coding problem, one encodes long blocks of source symbols that enables the distortion to approach the ultimate Shannon limit. Such a block-coding approach introduces large delays, which is undesirable in many delay-sensi
Externí odkaz:
http://arxiv.org/abs/2311.12609
We study the problem of lossless feature selection for a $d$-dimensional feature vector $X=(X^{(1)},\dots ,X^{(d)})$ and label $Y$ for binary classification as well as nonparametric regression. For an index set $S\subset \{1,\dots ,d\}$, consider the
Externí odkaz:
http://arxiv.org/abs/2311.05033
We study the excess minimum risk in statistical inference, defined as the difference between the minimum expected loss in estimating a random variable from an observed feature vector and the minimum expected loss in estimating the same random variabl
Externí odkaz:
http://arxiv.org/abs/2307.16735
The problem of regret minimization for online adaptive control of linear-quadratic systems is studied. In this problem, the true system transition parameters (matrices $A$ and $B$) are unknown, and the objective is to design and analyze algorithms th
Externí odkaz:
http://arxiv.org/abs/2210.16303
Publikováno v:
Entropy, Vol. 24, Issue, 10, October 2022
Two R\'{e}nyi-type generalizations of the Shannon cross-entropy, the R\'{e}nyi cross-entropy and the Natural R\'{e}nyi cross-entropy, were recently used as loss functions for the improved design of deep learning generative adversarial networks. In th
Externí odkaz:
http://arxiv.org/abs/2208.06983
The R\'{e}nyi cross-entropy measure between two distributions, a generalization of the Shannon cross-entropy, was recently used as a loss function for the improved design of deep learning generative adversarial networks. In this work, we examine the
Externí odkaz:
http://arxiv.org/abs/2206.14329
It is known that under fixed-rate information constraints, adaptive quantizers can be used to stabilize an open-loop-unstable linear system on $\mathbb{R}^n$ driven by unbounded noise. These adaptive schemes can be designed so that they have near-opt
Externí odkaz:
http://arxiv.org/abs/2202.02841
Optimal zero-delay coding (quantization) of $\mathbb{R}^d$-valued linearly generated Markov sources is studied under quadratic distortion. The structure and existence of deterministic and stationary coding policies that are optimal for the infinite h
Externí odkaz:
http://arxiv.org/abs/2103.10810
This paper considers an information bottleneck problem with the objective of obtaining a most informative representation of a hidden feature subject to a R\'enyi entropy complexity constraint. The optimal bottleneck trade-off between relevance (measu
Externí odkaz:
http://arxiv.org/abs/2101.12564
We investigate the equilibrium behavior for the decentralized cheap talk problem for real random variables and quadratic cost criteria in which an encoder and a decoder have misaligned objective functions. In prior work, it has been shown that the nu
Externí odkaz:
http://arxiv.org/abs/2012.08265