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Rehabilitating Homeless: Dataset and Key Insights
Proceedings of the AAAI Conference on Artificial Intelligence. 2023. P. 14136–14143.
Bykova A., Filippov N., Yamshchikov I. P.
This paper presents a large anonymized dataset of homelessness alongside insights into the data-driven rehabilitation of homeless people. The dataset was gathered by a large non- profit organization working on rehabilitating the homeless for twenty years. This is the first dataset that we know of that contains rich information on thousands of homeless individuals seeking rehabilitation. We show how data analysis can help to make the rehabilitation of homeless people more effective and successful. Thus, we hope this paper alerts the data science community to the problem of homelessness.
Language:
English
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Added: September 7, 2026
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Added: September 2, 2026
IEEE, 2026.
On behalf of the Organizing Committee, it is my great pleasure to extend a warm
welcome to all participants of the Fourth International IEEE Conference on
Distributed Computing and High-Performance Computing (DCHPC 2026), held
in Tehran from May 10–11, 2026. This conference is jointly organized by the
School of Computer Science at the Institute for Research in Fundamental
Sciences (IPM) ...
Added: September 2, 2026
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The spheres of the miraculous and monstrous are older than science, and perhaps even older than conceptual language. They belong to the reality of metaphors, or even deep emotions, therefore, in relation to science, their use, at first glance, seems evaluative and superfluous, because they do not refer to specific objects, labels and categories, but ...
Added: August 30, 2026
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Added: August 30, 2026
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ficult communicative task. Against the backdrop of growing sales and persistent consumer am
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renegotiate the legitimacy of Chinese automobile brands in online ...
Added: August 28, 2026
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The cardinality-constrained Markowitz problem is NP-hard and traditionally solved with commercial MIQP solvers. Following the 2022 export restrictions that rendered both commercial MIQP software and cloud quantum platforms (IBM Quantum, D-Wave Leap) inaccessible from the Russian Federation, practitioners require open-source alternatives. This paper systematically compares three solver families for the discrete mean-variance problem: two open-source ...
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Kharlamov A. A., Pilgun M., , in: Special Issue Sensing Technology for Smart Cities: Data, Analytics, and VisualizationsVol. 24. Issue 15.: [б.и.], 2024.
The analysis of large volumes of data collected from heterogeneous sources is increasingly important for the development of megacities, the advancement of smart city technologies, and ensuring a high quality of life for citizens. This study aimed to develop algorithms for analyzing and interpreting social media data to assess citizens’ opinions in real time and ...
Added: February 22, 2026
[б.и.], 2024.
Nowadays a huge portion of population lives in urban areas, and projections indicate that most cities are going to be confronted with a growing urban population in the next few years. This undoubtably poses new challenges that must be addressed by city councils and stakeholders to guarantee citizens’ high quality of life. Mobility, pollution, climate ...
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Morychev G., Sizykh D., Sizykh N., IEEE Access 2025 Vol. 13 P. 213194–213210
One of the main tools for analyzing large volumes of financial data is the use of clustering methods and models, which allow the identification of various patterns. This study examines the problem of clustering time series that reflect the behavior of prices, yields, modes, trends, and a number of related stock indicators. The relevance and ...
Added: February 3, 2026