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While it is well known that high levels of prenatal alcohol exposure (PAE) result in significant cognitive deficits in children, the exact nature of the dose response is less well understood. In particular, there is a pressing need to…

This survey presents studies that investigated non-spatial (sequential) and spatial information retrieval systems in parallel during a battery of information-seeking tasks with respect to user navigational behaviors, incidental learning,…

Human-Computer Interaction · Computer Science 2019-11-05 Michael Segundo Ortz

Model-based Reinforcement Learning (RL) integrates learning and planning and has received increasing attention in recent years. However, learning the model can incur a significant cost (in terms of sample complexity), due to the need to…

Machine Learning · Computer Science 2023-03-17 Jiajun Shen , Kananart Kuwaranancharoen , Raid Ayoub , Pietro Mercati , Shreyas Sundaram

The continuous growth in the XML information repositories has been matched by increasing efforts in development of XML retrieval systems, in large parts aiming at supporting content-oriented XML retrieval. These systems exploit the…

Information Retrieval · Computer Science 2011-11-29 Awny Sayed

In many instances, information on engineering systems can be obtained through measurements, monitoring or direct observations of system performances and can be used to update the system reliability estimate. In structural reliability…

Methodology · Statistics 2012-03-27 Daniel Straub

One of the key components of designing usable and useful collaborative information retrieval systems is to understand the needs of the users of these systems. Our research team has been exploring collaborative information behavior in a…

Information Retrieval · Computer Science 2009-08-07 Madhu Reddy , Bernard J. Jansen

The problem of Information Retrieval is, given a set of documents D and a query q, providing an algorithm for retrieving all documents in D relevant to q. However, retrieval should depend and be updated whenever the user is able to provide…

Information Retrieval · Computer Science 2007-05-23 Gianni Amati , Konstantinos Georgatos

Reasoning-Intensive Retrieval (RIR) targets retrieval settings where relevance is mediated by latent inferential links between a query and supporting evidence, rather than semantic similarity. Motivated by the emergent reasoning abilities…

Information Retrieval · Computer Science 2026-05-04 Yiyang Wei , Tingyu Song , Siyue Zhang , Yilun Zhao

Recently, interpretable models called self-explaining models (SEMs) have been proposed with the goal of providing interpretability robustness. We evaluate the interpretability robustness of SEMs and show that explanations provided by SEMs…

Machine Learning · Computer Science 2020-07-03 Haizhong Zheng , Earlence Fernandes , Atul Prakash

This chapter presents a theoretical framework for evaluating next generation search engines. We focus on search engines whose results presentation is enriched with additional information and does not merely present the usual list of 10 blue…

Information Retrieval · Computer Science 2015-11-19 Dirk Lewandowski

Four-dimensional scanning transmission electron microscopy (4D-STEM) is one of the most rapidly growing modes of electron microscopy imaging. The advent of fast pixelated cameras and the associated data infrastructure have greatly…

Applications · Statistics 2019-08-27 Xin Li , Ondrej Dyck , Stephen Jesse , Andrew R. Lupini , Sergei V. Kalinin , Mark P. Oxley

Symbolic regression is a powerful system identification technique in industrial scenarios where no prior knowledge on model structure is available. Such scenarios often require specific model properties such as interpretability, robustness,…

Information retrieval systems are usually measured by labeling the relevance of results corresponding to a sample of user queries. In practical search engines, such measurement needs to be performed continuously, such as daily or weekly.…

Information Retrieval · Computer Science 2022-03-04 Nikita Astrakhantsev , Deepak Chittajallu , Nabeel Kaushal , Vladislav Mokeev

The number of studies for the analysis of remote sensing images has been growing exponentially in the last decades. Many studies, however, only report results---in the form of certain performance metrics---by a few selected algorithms on a…

Applications · Statistics 2020-01-07 Donghui Yan , Congcong Li , Na Cong , Le Yu , Peng Gong

This paper highlights the growing importance of information retrieval (IR) engines in the scientific community, addressing the inefficiency of traditional keyword-based search engines due to the rising volume of publications. The proposed…

Information Retrieval · Computer Science 2024-10-24 Mahsa Shamsabadi , Jennifer D'Souza

Identifying dependencies among variables in a complex system is an important problem in network science. Structural equation models (SEM) have been used widely in many fields for topology inference, because they are tractable and…

Signal Processing · Electrical Eng. & Systems 2020-03-20 Bakht Zaman , Luis Miguel Lopez Ramos , Baltasar Beferull-Lozano

Ranking models are the main components of information retrieval systems. Several approaches to ranking are based on traditional machine learning algorithms using a set of hand-crafted features. Recently, researchers have leveraged deep…

Information Retrieval · Computer Science 2021-11-03 Mohamed Trabelsi , Zhiyu Chen , Brian D. Davison , Jeff Heflin

As data from monitored structures become increasingly available, the demand grows for it to be used efficiently to add value to structural operation and management. One way in which this can be achieved is to use structural response…

Applications · Statistics 2025-05-14 Nicholas E. Silionis , Konstantinos N. Anyfantis

Reranking is a critical stage in contemporary information retrieval (IR) systems, improving the relevance of the user-presented final results by honing initial candidate sets. This paper is a thorough guide to examine the changing reranker…

Information Retrieval · Computer Science 2025-12-19 Tejul Pandit , Sakshi Mahendru , Meet Raval , Dhvani Upadhyay

Formula retrieval is an important topic in Mathematical Information Retrieval. We propose SSEmb, a novel embedding framework capable of capturing both structural and semantic features of mathematical formulas. Structurally, we employ Graph…

Information Retrieval · Computer Science 2025-08-08 Ruyin Li , Xiaoyu Chen
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