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A general problem of optimal information acquisition for its use in decision making problems is considered. This motivates the need for developing quantitative measures of information sources' capabilities for supplying accurate information…

Data Analysis, Statistics and Probability · Physics 2013-02-15 Eugene Perevalov , David Grace

When additional information sources are available in decision making problems that allow stochastic optimization formulations, an important question is how to optimally use the information the sources are capable of providing. A framework…

Data Analysis, Statistics and Probability · Physics 2013-02-04 Eugene Perevalov , David Grace

When additional information sources are available, an important question for an agent solving a certain problem is how to optimally use the information the sources are capable of providing. A framework that relates information accuracy on…

Data Analysis, Statistics and Probability · Physics 2013-01-11 Eugene Perevalov , David Grace

There are many potential benefits to news readers accessing diverse sources. Modern news aggregators do the hard work of organizing the news, offering readers a plethora of source options, but choosing which source to read remains…

Computation and Language · Computer Science 2022-11-10 Philippe Laban , Chien-Sheng Wu , Lidiya Murakhovs'ka , Xiang 'Anthony' Chen , Caiming Xiong

A large body of work in psycholinguistics has focused on the idea that online language comprehension can be shallow or `good enough': given constraints on time or available computation, comprehenders may form interpretations of their input…

Computation and Language · Computer Science 2024-05-15 Jiaxuan Li , Richard Futrell

Determining whether a provided context contains sufficient information to answer a question is a critical challenge for building reliable question-answering systems. While simple prompting strategies have shown success on factual questions,…

Computation and Language · Computer Science 2026-03-24 Akriti Jain , Aparna Garimella

We introduce derivation depth-a computable metric of the reasoning effort needed to answer a query based on a given set of premises. We model information as a two-layered structure linking abstract knowledge with physical carriers, and…

Information Theory · Computer Science 2026-02-24 Jianfeng Xu

News articles are driven by the informational sources journalists use in reporting. Modeling when, how and why sources get used together in stories can help us better understand the information we consume and even help journalists with the…

Computation and Language · Computer Science 2023-05-25 Alexander Spangher , Nanyun Peng , Jonathan May , Emilio Ferrara

In Big data era, information integration often requires abundant data extracted from massive data sources. Due to a large number of data sources, data source selection plays a crucial role in information integration, since it is costly and…

Databases · Computer Science 2016-11-01 Yiming Lin , Hongzhi Wang , Jianzhong Li , Hong Gao

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Robin A. A. Ince , Simon R. Schultz , Stefano Panzeri

Model selection in clustering requires (i) to specify a suitable clustering principle and (ii) to control the model order complexity by choosing an appropriate number of clusters depending on the noise level in the data. We advocate an…

Information Theory · Computer Science 2010-06-03 Joachim M. Buhmann

Open-ended question answering requires models to find appropriate evidence to form wellreasoned, comprehensive and helpful answers. In practical applications, models also need to engage in extended discussions on potential scenarios closely…

Computation and Language · Computer Science 2024-12-17 Mingxu Tao , Dongyan Zhao , Yansong Feng

A general notion of information-related complexity applicable to both natural and man-made systems is proposed. The overall approach is to explicitly consider a rational agent performing a certain task with a quantifiable degree of success.…

Data Analysis, Statistics and Probability · Physics 2013-01-18 Eugene Perevalov , David Grace

Ensuring the usefulness of electronic data sources while providing necessary privacy guarantees is an important unsolved problem. This problem drives the need for an overarching analytical framework that can quantify the safety of…

Information Theory · Computer Science 2010-10-04 Lalitha Sankar , S. Raj Rajagopalan , H. Vincent Poor

Resolving knowledge conflicts is a crucial challenge in Question Answering (QA) tasks, as the internet contains numerous conflicting facts and opinions. While some research has made progress in tackling ambiguous settings where multiple…

Computation and Language · Computer Science 2024-10-30 Sagi Shaier , Ari Kobren , Philip Ogren

The problem of selection, storage, search and analysis of information about the state, functioning and interaction of elements of complex hierarchical network systems is considered. The principles of construction of information models of…

Physics and Society · Physics 2021-06-17 Olexandr Polishchuk , Mykhailo Yadzhak

The increasing reliance on digital information necessitates advancements in conversational search systems, particularly in terms of information transparency. While prior research in conversational information-seeking has concentrated on…

Information Retrieval · Computer Science 2024-05-07 Weronika Łajewska , Damiano Spina , Johanne Trippas , Krisztian Balog

Data integration systems allow users to access data sitting in multiple sources by means of queries over a global schema, related to the sources via mappings. Data sources often contain sensitive information, and thus an analysis is needed…

Logic in Computer Science · Computer Science 2020-12-15 Michael Benedikt , Pierre Bourhis , Louis Jachiet , Michaël Thomazo

We introduce an information-theoretic framework that views learning as universal prediction under log loss, characterized through regret bounds. Central to the framework is an effective notion of architecture-based model complexity, defined…

Machine Learning · Computer Science 2025-11-04 Meir Feder , Ruediger Urbanke , Yaniv Fogel

Simulations offer opportunities in the examination of manufacturing processes. They represent various aspects of the production process and the associated production systems. However, often a single simulation does not suffice to provide a…

Software Engineering · Computer Science 2024-11-26 Jonathan Reif , Tom Jeleniewski , Aljosha Köcher , Tim Frerich , Felix Gehlhoff , Alexander Fay
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