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In this paper, we study the problem of uncertainty estimation and calibration for LLMs. We begin by formulating the uncertainty estimation problem, a relevant yet underexplored area in existing literature. We then propose a supervised…

Machine Learning · Computer Science 2024-10-24 Linyu Liu , Yu Pan , Xiaocheng Li , Guanting Chen

This paper considers the optimal modification of the likelihood ratio test (LRT) for the equality of two high-dimensional covariance matrices. The classical LRT is not well defined when the dimensions are larger than or equal to one of the…

Statistics Theory · Mathematics 2018-04-06 Qiuyan Zhang , Jiang Hu , Zhidong Bai

Various problems in Engineering and Statistics require the computation of the likelihood ratio function of two probability densities. In classical approaches the two densities are assumed known or to belong to some known parametric family.…

Signal Processing · Electrical Eng. & Systems 2019-11-06 George V. Moustakides , Kalliopi Basioti

For finite samples with binary outcomes penalized logistic regression such as ridge logistic regression (RR) has the potential of achieving smaller mean squared errors (MSE) of coefficients and predictions than maximum likelihood…

Methodology · Statistics 2021-01-28 Hana Šinkovec , Georg Heinze , Rok Blagus , Angelika Geroldinger

Non-Gaussian likelihoods are essential for modelling complex real-world observations but pose significant computational challenges in learning and inference. Even with Gaussian priors, non-Gaussian likelihoods often lead to analytically…

Machine Learning · Statistics 2024-10-29 Thang D. Bui

We present a new set of accurate formulae for the computation of random errors in the measurement of atomic and molecular indices. The new expressions are in excellent agreement with numerical simulations. We have found that, in some cases,…

Astrophysics · Physics 2009-10-30 N. Cardiel , J. Gorgas , J. Cenarro , J. J. Gonzalez

Label smoothing (LS) adopts smoothed targets in classification tasks. For example, in binary classification, instead of the one-hot target $(1,0)^\top$ used in conventional logistic regression (LR), LR with LS (LSLR) uses the smoothed…

Machine Learning · Statistics 2023-05-16 Ryoya Yamasaki , Toshiyuki Tanaka

Log-symmetric regression models are particularly useful when the response variable is continuous, strictly positive and asymmetric. In this paper, we proposed a class of log-symmetric regression models in the context of correlated errors.…

Methodology · Statistics 2018-10-22 Helton Saulo , Roberto Vila

We provide estimates of the rate of strong approximation and bounds for probabilities of moderate deviations in the CLT for the $L_1$-norm of the kernel density estimator without any assumptions on the density and assuming that the kernel…

Probability · Mathematics 2014-02-07 Andrei Yu. Zaitsev

Faster likelihood evaluation enhances the efficiency of gravitational wave signal analysis. We present Mode-by-mode Relative Binning (MRB), a new method designed for obtaining fast and accurate likelihoods for advanced waveform models that…

Instrumentation and Methods for Astrophysics · Physics 2022-01-05 Nathaniel Leslie , Liang Dai , Geraint Pratten

Most existing works of polar codes focus on the analysis of block error probability. However, in many scenarios, bit error probability is also important for evaluating the performance of channel codes. In this paper, we establish a new…

Information Theory · Computer Science 2022-04-18 Bolin Wu , Kai Niu , Jincheng Dai

Low-rank regularization (LRR) has been widely applied in various machine learning tasks, but the associated optimization is challenging. Directly optimizing the rank function under constraints is NP-hard in general. To overcome this…

Machine Learning · Computer Science 2025-05-22 Naiqi Li , Yuqiu Xie , Peiyuan Liu , Tao Dai , Yong Jiang , Shu-Tao Xia

Quantifying the difference between two probability density functions, $p$ and $q$, using available data, is a fundamental problem in Statistics and Machine Learning. A usual approach for addressing this problem is the likelihood-ratio…

Machine Learning · Statistics 2023-11-06 Alejandro de la Concha , Nicolas Vayatis , Argyris Kalogeratos

In this paper, we investigate performance improvements of low-power long-range (LoRa) modulation when a gateway is equipped with multiple antennas. We derive the optimal decision rules for both coherent and non-coherent detections when…

Signal Processing · Electrical Eng. & Systems 2021-06-23 The Khai Nguyen , Ha H. Nguyen , Ebrahim Bedeer

This work considers optimizing LDPC codes in the physical-layer network coded two-way relay channel using noncoherent FSK modulation. The error-rate performance of channel decoding at the relay node during the multiple-access phase was…

Information Theory · Computer Science 2015-02-23 Terry Ferrett , Matthew C. Valenti

We consider explicit polar constructions of blocklength $n\rightarrow\infty$ for the two extreme cases of code rates $R\rightarrow1$ and $R\rightarrow0.$ For code rates $R\rightarrow1,$ we design codes with complexity order of $n\log n$ in…

Information Theory · Computer Science 2017-02-17 Ilya Dumer

Ternary channels can be used to model the behavior of some memory devices, where information is stored in three different levels. In this paper, error correcting coding for a ternary channel where some of the error transitions are not…

Information Theory · Computer Science 2011-05-31 Nicolas Bitouze , Alexandre Graell i Amat , Eirik Rosnes

Recently, a generalization of the double-Rayleigh with line-of-sight channel fading model taking into account shadowing of the line-of-sight component has been proposed. In this research, a closed-form analysis of the average bit error rate…

Information Theory · Computer Science 2022-06-23 Aleksey S. Gvozdarev

We study tight bounds and fast algorithms for LCLMs of several linear differential operators with polynomial coefficients. We analyze the arithmetic complexity of existing algorithms for LCLMs, as well as the size of their outputs. We…

Symbolic Computation · Computer Science 2013-06-19 Alin Bostan , Frédéric Chyzak , Ziming Li , Bruno Salvy

Extremely large-scale antenna arrays (ELAAs) enable high spatial resolution and multiplexing, especially for user equipments (UEs) in the radiative near-field. To reduce hardware cost, modular ELAA architectures with distributed baseband…

Signal Processing · Electrical Eng. & Systems 2025-09-23 Özlem Tuğfe Demir , Emil Björnson