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Computational complexity is a key limitation of genomic analyses. Thus, over the last 30 years, researchers have proposed numerous fast heuristic methods that provide computational relief. Comparing genomic sequences is one of the most…

Change point analysis has applications in a wide variety of fields. The general problem concerns the inference of a change in distribution for a set of time-ordered observations. Sequential detection is an online version in which new data…

Methodology · Statistics 2013-10-16 David S. Matteson , Nicholas A. James

We consider the problem of automatically generating textual paraphrases with modified attributes or properties, focusing on the setting without parallel data (Hu et al., 2017; Shen et al., 2017). This setting poses challenges for…

Computation and Language · Computer Science 2019-10-01 Richard Yuanzhe Pang , Kevin Gimpel

In this paper, direction-of-arrival (DOA) estimation using non-coherent processing for partly calibrated arrays composed of multiple subarrays is considered. The subarrays are assumed to compute locally the sample covariance matrices of…

Applications · Statistics 2017-04-21 Wassim Suleiman , Pouyan Parvazi , Marius Pesavento , Abdelhak M. Zoubir

Cohort studies of the onset of a disease often encounter left-truncation on the event time of interest in addition to right-censoring due to variable enrollment times of study participants. Analysis of such event time data can be biased if…

Methodology · Statistics 2025-04-11 Spencer Matthews , Bin Nan

An important problem in many domains is to predict how a system will respond to interventions. This task is inherently linked to estimating the system's underlying causal structure. To this end, Invariant Causal Prediction (ICP) (Peters et…

Methodology · Statistics 2018-09-21 Christina Heinze-Deml , Jonas Peters , Nicolai Meinshausen

We present a nonparametric framework to model a short sequence of probability distributions that vary both due to underlying effects of sequential progression and confounding noise. To distinguish between these two types of variation and…

Methodology · Statistics 2019-02-08 Jonas Mueller , Tommi Jaakkola , David Gifford

In typical medical image classification problems, labeled data is scarce while unlabeled data is more available. Semi-supervised learning and self-supervised learning are two different research directions that can improve accuracy by…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Zhe Huang , Ruijie Jiang , Shuchin Aeron , Michael C. Hughes

Coreference Resolution is a well studied problem in NLP. While widely studied for English and other resource-rich languages, research on coreference resolution in Bengali largely remains unexplored due to the absence of relevant datasets.…

Computation and Language · Computer Science 2023-07-06 Shadman Rohan , Mojammel Hossain , Mohammad Mamun Or Rashid , Nabeel Mohammed

Clinical and epidemiological studies encode participant information in multivariate vectors with mixed type variables on continuous, truncated, ordinal, and binary scales. Semiparametric Gaussian Copula (SGC) assumes that observed data is…

Methodology · Statistics 2026-03-19 Debangan Dey , Vadim Zipunnikov

Given a dataset of careers and incomes, how large a difference of income between any pair of careers would be? Given a dataset of travel time records, how long do we need to spend more when choosing a public transportation mode $A$ instead…

We present a semi-supervised method for panoptic segmentation based on ConsInstancy regularisation, a novel strategy for semi-supervised learning. It leverages completely unlabelled data by enforcing consistency between predicted instance…

Computer Vision and Pattern Recognition · Computer Science 2022-07-06 Max Coenen , Tobias Schack , Dries Beyer , Christian Heipke , Michael Haist

Since the introduction of the Kolmogorov complexity of binary sequences in the 1960s, there have been significant advancements in the topic of complexity measures for randomness assessment, which are of fundamental importance in theoretical…

Cryptography and Security · Computer Science 2026-04-14 Chunlei Li

Classification is an important task in many fields including biomedical research and machine learning. Traditionally, a classification rule is constructed based a bunch of labeled data. Recently, due to technological innovation and…

Methodology · Statistics 2014-06-19 Jing Wang , Eunsik Park , Yuan-chin Ivan Chang

There has been growing interests in recent years from both practical and research perspectives for session-based recommendation tasks as long-term user profiles do not often exist in many real-life recommendation applications. In this case,…

Information Retrieval · Computer Science 2018-06-12 Fei Mi , Boi Faltings

In health-related experiments, treatment effects can be identified using paired data that consist of pre- and post-treatment measurements. In this framework, sequential testing strategies are widely accepted statistical tools in practice.…

Methodology · Statistics 2018-12-24 Li Zou , Albert Vexler , Jihnhee Yu , Hongzhi Wan

Increased access to reliable health information is essential for non-English-speaking populations, yet resources in Bangla for disease prediction remain limited. This study addresses this gap by developing a comprehensive Bangla…

Computation and Language · Computer Science 2026-01-21 Rowzatul Zannat , Abdullah Al Shafi , Abdul Muntakim

In recent years there has been growing interest in solutions for the delivery of clinical care for the elderly, due to the large increase in aging population. Monitoring a patient in his home environment is necessary to ensure continuity of…

Artificial Intelligence · Computer Science 2010-06-30 A. Mileo , D. Merico , R. Bisiani

Scribble annotations significantly reduce the cost and labor required for dense labeling in large medical datasets with complex anatomical structures. However, current scribble-supervised learning methods are limited in their ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Luyi Qiu , Tristan Till , Xiaobao Guo , Adams Wai-Kin Kong

As the world marked the midterm of the Sendai Framework for Disaster Risk Reduction 2015-2030, many countries are still struggling to monitor their climate and disaster risk because of the expensive large-scale survey of the distribution of…

Machine Learning · Computer Science 2024-04-03 Joshua Dimasaka , Christian Geiß , Emily So
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