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Online evaluation of machine learning models is typically conducted through A/B experiments. Sequential statistical tests are valuable tools for analysing these experiments, as they enable researchers to stop data collection early without…

Methodology · Statistics 2025-10-08 Alexey Kurennoy , Majed Dodin , Tural Gurbanov , Ana Peleteiro Ramallo

We consider a quantum system that is being continuously monitored, giving rise to a measurement signal. From such a stream of data, information needs to be inferred about the underlying system's dynamics. Here we focus on hypothesis testing…

Quantum Physics · Physics 2024-03-27 Giulio Gasbarri , Matias Bilkis , Elisabet Roda-Salichs , John Calsamiglia

The determination of the number of mixture components (the order) of a finite mixture model has been an enduring problem in statistical inference. We prove that the closed testing principle leads to a sequential testing procedure (STP) that…

Methodology · Statistics 2022-09-27 Hien D Nguyen , Daniel Fryer , Geoffrey McLachlan

With the rapid advancement of information technology, the complexity of applications continues to increase, and the cybersecurity challenges we face are also escalating. This paper aims to investigate the methods and practices of system…

Cryptography and Security · Computer Science 2026-02-02 Chunyi Zhang , Jin Zeng , Xiaoqi Li

In most prediction and estimation situations, scientists consider various statistical models for the same problem, and naturally want to select amongst the best. Hansen et al. (2011) provide a powerful solution to this problem by the…

Methodology · Statistics 2026-01-23 Sebastian Arnold , Georgios Gavrilopoulos , Benedikt Schulz , Johanna Ziegel

We revisit the problem of statistical sequence matching initiated by Unnikrishnan (TIT 2015) and derive theoretical performance guarantees for sequential tests that have bounded expected stopping times. Specifically, in this problem, one is…

Information Theory · Computer Science 2025-06-05 Lin Zhou , Qianyun Wang , Yun Wei , Jingjing Wang

We present a sequential testing method to identify a practically significant effect. We build on the existing mixture sequential probability ratio test (mSPRT) that can sequentially test for a non-zero treatment effect by using a truncated…

Methodology · Statistics 2025-09-10 Kyu Min Shim

Text Style Transfer (TST) evaluation is, in practice, inconsistent. Therefore, we conduct a meta-analysis on human and automated TST evaluation and experimentation that thoroughly examines existing literature in the field. The meta-analysis…

Machine Learning · Computer Science 2023-06-02 Phil Ostheimer , Mayank Nagda , Marius Kloft , Sophie Fellenz

This work takes the first steps towards solving the "phaseless subspace tracking" (PST) problem. PST involves recovering a time sequence of signals (or images) from phaseless linear projections of each signal under the following structural…

Machine Learning · Computer Science 2018-09-13 Seyedehsara Nayer , Namrata Vaswani

We propose a new approach to sequential testing which is an adaptive (on-line) extension of the (off-line) framework developed in [10]. It relies upon testing of pairs of hypotheses in the case where each hypothesis states that the vector…

Statistics Theory · Mathematics 2017-02-27 Anatoli Juditsky , Arkadi Nemirovski

The sequential multiple testing problem is considered under two generalized error metrics. Under the first one, the probability of at least $k$ mistakes, of any kind, is controlled. Under the second, the probabilities of at least $k_1$…

Statistics Theory · Mathematics 2019-02-18 Yanglei Song , Georgios Fellouris

Regression testing is an essential activity to assure that software code changes do not adversely affect existing functionalities. With the wide adoption of Continuous Integration (CI) in software projects, which increases the frequency of…

Software Engineering · Computer Science 2022-09-07 Rongqi Pan , Mojtaba Bagherzadeh , Taher A. Ghaleb , Lionel Briand

The emerging topic of sequential recommender systems has attracted increasing attention in recent years.Different from the conventional recommender systems including collaborative filtering and content-based filtering, SRSs try to…

Information Retrieval · Computer Science 2020-01-15 Shoujin Wang , Liang Hu , Yan Wang , Longbing Cao , Quan Z. Sheng , Mehmet Orgun

System-level test, or SLT, is an increasingly important process step in today's integrated circuit testing flows. Broadly speaking, SLT aims at executing functional workloads in operational modes. In this paper, we consolidate available…

The paper contains a discussion on a number of open problems in queueing theory. Some of them are known for decades, some are more recent. They relate to stability and to rare events. There is an idea to prepare a special issue of QUESTA on…

Probability · Mathematics 2009-09-03 Sergey Foss

New testing and development procedures and methods are needed to address topics like power system stability, operation and control in the context of grid integration of rapidly developing smart grid technologies. In this context, individual…

The main objective of this survey is to present the important theoretical and experimental results contributed till date in the area of online algorithms for the self organizing sequential search problem, also popularly known as the List…

Data Structures and Algorithms · Computer Science 2009-09-02 Rakesh Mohanty , N. S. Narayanaswamy

The growing need for synthetic time series, due to data augmentation or privacy regulations, has led to numerous generative models, frameworks, and evaluation measures alike. Objectively comparing these measures on a large scale remains an…

Machine Learning · Computer Science 2025-05-28 Michael Stenger , Robert Leppich , André Bauer , Samuel Kounev

The stylistic properties of text have intrigued computational linguistics researchers in recent years. Specifically, researchers have investigated the Text Style Transfer (TST) task, which aims to change the stylistic properties of the text…

Computation and Language · Computer Science 2023-01-03 Zhiqiang Hu , Roy Ka-Wei Lee , Charu C. Aggarwal , Aston Zhang

Tech companies (e.g., Google or Facebook) often use randomized online experiments and/or A/B testing primarily based on the average treatment effects to compare their new product with an old one. However, it is also critically important to…

Methodology · Statistics 2021-11-09 Chengchun Shi , Shikai Luo , Hongtu Zhu , Rui Song
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