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It is frequently of interest to jointly analyze multiple sequences of multiple tests in order to identify simultaneous signals, defined as features tested in multiple studies whose test statistics are non-null in each. In many problems,…

Methodology · Statistics 2019-01-16 Sihai Dave Zhao , Yet Tien Nguyen

Self-mixing interferometry is a measurement approach in which a laser beam is re-injected into the emitting laser itself after reflection on a target. Information about the position of the target can be obtained from monitoring the voltage…

Instrumentation and Detectors · Physics 2024-05-07 Pierre-Emmanuel Novac , Laurent Rodriguez , Stéphane Barland

We consider the problem of reconstructing rank-one matrices from random linear measurements, a task that appears in a variety of problems in signal processing, statistics, and machine learning. In this paper, we focus on the Alternating…

Machine Learning · Computer Science 2022-04-26 Kiryung Lee , Dominik Stöger

The ASVspoof 2021 benchmark, a widely-used evaluation framework for anti-spoofing, consists of two subsets: Logical Access (LA) and Deepfake (DF), featuring samples with varied coding characteristics and compression artifacts. Notably, the…

Audio and Speech Processing · Electrical Eng. & Systems 2024-09-24 Hieu-Thi Luong , Duc-Tuan Truong , Kong Aik Lee , Eng Siong Chng

The Legendre Pseudorandom Function (PRF) is a highly efficient cryptographic primitive built upon the Legendre symbol, valued for its low multiplicative complexity in Multi-Party Computation (MPC) and Zero-Knowledge Proof (ZKP) protocols.…

Cryptography and Security · Computer Science 2026-05-25 Daksh Pandey

Machine learning (ML) research strongly relies on benchmarks in order to determine the relative effectiveness of newly proposed models. Recently, a number of prominent research effort argued that a number of models that improve the…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Utku Ozbulak , Esla Timothy Anzaku , Solha Kang , Wesley De Neve , Joris Vankerschaver

Self-training (ST), or pseudo-labeling has sparked significant interest in the automatic speech recognition (ASR) community recently because of its success in harnessing unlabeled data. Unlike prior semi-supervised learning approaches that…

Machine Learning · Computer Science 2023-04-11 Dan Berrebbi , Ronan Collobert , Samy Bengio , Navdeep Jaitly , Tatiana Likhomanenko

In this work, we conducted a study on building an automated testing system for deep learning systems based on differential behavior criteria. The automated testing goals were achieved by jointly optimizing two objective functions:…

Machine Learning · Computer Science 2020-01-01 Yuan Gao , Yiqiang Han

For large-scale testing with graph-associated data, we present an empirical Bayes mixture technique to score local false discovery rates. Compared to empirical Bayes procedures that ignore the graph, the proposed method gains power in…

Methodology · Statistics 2019-11-26 TIen Vo , Vamsi Ithapu , Vikas Singh , Michael A. Newton

Traditional inference in cointegrating regressions requires tuning parameter choices to estimate a long-run variance parameter. Even in case these choices are "optimal", the tests are severely size distorted. We propose a novel…

Econometrics · Economics 2025-10-10 Karsten Reichold , Carsten Jentsch

Network reconstruction of dynamical continuous-time (CT) systems is motivated by applications in many fields. Due to experimental limitations, especially in biology, data could be sampled at low frequencies, leading to significant…

Systems and Control · Computer Science 2018-10-30 Zuogon Yue , Johan Thunberg , Lennart Ljung , Ye Yuan , Jorge Goncalves

After being trained, classifiers must often operate on data that has been corrupted by noise. In this paper, we consider the impact of such noise on the features of binary classifiers. Inspired by tools for classifier robustness, we…

Machine Learning · Statistics 2017-03-09 Frederic Sala , Shahroze Kabir , Guy Van den Broeck , Lara Dolecek

$ \newcommand{\ie}{i.\,e.} $We introduce a hitting set generator for Polynomial Identity Testing based on evaluations of low-degree univariate rational functions at abscissas associated with the variables. We establish an equivalence up to…

Computational Complexity · Computer Science 2025-01-06 Ivan Hu , Dieter van Melkebeek , Andrew Morgan

This research deals with massive multiple hypothesis testing. First regarding multiple tests as an estimation problem under a proper population model, an error measurement called Erroneous Rejection Ratio (ERR) is introduced and related to…

Statistics Theory · Mathematics 2007-06-13 Cheng Cheng

The ever-increasing need for random numbers is clear in many areas of computer science, from neural networks to optimization. As such, most common programming language provide easy access to Pseudorandom Number Generators. However, these…

Programming Languages · Computer Science 2021-09-28 Nils van den Honert , Diederick Vermetten , Anna V. Kononova

Handwriting verification has stood as a steadfast identity authentication method for decades. However, this technique risks potential privacy breaches due to the inclusion of personal information in handwritten biometrics such as…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Peirong Zhang , Yuliang Liu , Songxuan Lai , Hongliang Li , Lianwen Jin

In the last few years, NICER data has enabled mass and radius inferences for various pulsars, and thus shed light on the equation of state for dense nuclear matter. This is achieved through a technique called pulse profile modeling. The…

High Energy Astrophysical Phenomena · Physics 2026-03-25 Mariska Hoogkamer , Yves Kini , Tuomo Salmi , Anna L. Watts , Johannes Buchner

In this paper, we analyze the symbol error rate (SER) performance of the simultaneous wireless information and power transfer (SWIPT) enabled three-node differential decode-and-forward (DDF) relay networks, which adopt the power splitting…

Signal Processing · Electrical Eng. & Systems 2020-08-06 Yuxin Lu , Wai Ho Mow

We present a hybrid quantum-classical framework for simulating generic matrix functions more amenable to early fault-tolerant quantum hardware than standard quantum singular-value transformations. The method is based on randomization over…

Quantum Physics · Physics 2024-11-28 Allan Tosta , Thais de Lima Silva , Giancarlo Camilo , Leandro Aolita

We present an iterative approach to constructing pseudorandom generators, based on the repeated application of mild pseudorandom restrictions. We use this template to construct pseudorandom generators for combinatorial rectangles and…

Computational Complexity · Computer Science 2012-10-02 Parikshit Gopalan , Raghu Meka , Omer Reingold , Luca Trevisan , Salil Vadhan