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Recovery from the Flint Water Crisis has been hindered by uncertainty in both the water testing process and the causes of contamination. In this work, we develop an ensemble of predictive models to assess the risk of lead contamination in…

The analysis of data arising from environmental health studies which collect a large number of measures of exposure can benefit from using latent variable models to summarize exposure information. However, difficulties with estimation of…

Applications · Statistics 2009-08-21 Brisa N. Sánchez , Esben Budtz-Jørgensen , Louise M. Ryan

This paper studies the evaluation of methods for targeting the allocation of limited resources to a high-risk subpopulation. We consider a randomized controlled trial to measure the difference in efficiency between two targeting methods and…

Applications · Statistics 2018-04-04 Eric Potash

Mapping near-field pollutant concentration is essential to track accidental toxic plume dispersion in urban areas. By solving a large part of the turbulence spectrum, large-eddy simulations (LES) have the potential to accurately represent…

Machine Learning · Statistics 2022-08-03 Bastien X Nony , Mélanie Rochoux , Thomas Jaravel , Didier Lucor

Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined…

Machine Learning · Computer Science 2020-11-30 Leili Zhang , Giacomo Domeniconi , Chih-Chieh Yang , Seung-gu Kang , Ruhong Zhou , Guojing Cong

The degradation of sewer pipes poses significant economical, environmental and health concerns. The maintenance of such assets requires structured plans to perform inspections, which are more efficient when structural and environmental…

Machine Learning · Computer Science 2023-07-14 Fidae El Morer , Stefan Wittek , Andreas Rausch

Lead is a naturally-occurring element. It has been known to man for a long time, and it is one of the longest established poisons. The current consensus is that no level of lead exposure should be deemed "safe." New evidence regarding the…

Quantitative Methods · Quantitative Biology 2019-02-19 Anca Radulescu , Steven Lundgren

When the residents of Flint learned that lead had contaminated their water system, the local government made water-testing kits available to them free of charge. The city government published the results of these tests, creating a valuable…

Machine Learning · Computer Science 2017-07-07 Alex Chojnacki , Chengyu Dai , Arya Farahi , Guangsha Shi , Jared Webb , Daniel T. Zhang , Jacob Abernethy , Eric Schwartz

We detail our ongoing work in Flint, Michigan to detect pipes made of lead and other hazardous metals. After elevated levels of lead were detected in residents' drinking water, followed by an increase in blood lead levels in area children,…

Machine Learning · Computer Science 2018-08-20 Jacob Abernethy , Alex Chojnacki , Arya Farahi , Eric Schwartz , Jared Webb

The complexity-performance trade-off is a fundamental aspect of the design of low-density parity-check (LDPC) codes. In this paper, we consider LDPC codes for the binary erasure channel (BEC), use code rate for performance metric, and…

Information Theory · Computer Science 2016-11-17 Vahid Jamali , Yasser Karimian , Johannes Huber , Mahmoud Ahmadian

Iterative rounding and relaxation have arguably become the method of choice in dealing with unconstrained and constrained network design problems. In this paper we extend the scope of the iterative relaxation method in two directions: (1)…

Data Structures and Algorithms · Computer Science 2015-05-18 Nikhil Bansal , Rohit Khandekar , Jochen Konemann , Viswanath Nagarajan , Britta Peis

Linear-parametric optimization, where multiple objectives are combined into a single objective using linear combinations with parameters as coefficients, has numerous links to other fields in optimization and a wide range of application…

Optimization and Control · Mathematics 2025-01-22 Levin Nemesch , Stefan Ruzika , Clemens Thielen , Alina Wittmann

Industrially relevant constrained optimization problems, such as portfolio optimization and portfolio rebalancing, are often intractable or difficult to solve exactly. In this work, we propose and benchmark a decomposition pipeline…

This paper presents an efficient 51 lines Matlab code to solve topology optimization problems. By the fact that the presented code is based on an hard 0-1 optimization method that handles the integer part of the optimization in a simple…

Optimization and Control · Mathematics 2019-02-05 Vittorio Latorre

We introduce Noise Recycling, a method that enhances decoding performance of channels subject to correlated noise without joint decoding. The method can be used with any combination of codes, code-rates and decoding techniques. In the…

Information Theory · Computer Science 2020-10-16 Alejandro Cohen , Amit Solomon , Ken R. Duffy , Muriel Médard

The min-knapsack problem with compactness constraints extends the classical knapsack problem, in the case of ordered items, by introducing a restriction ensuring that they cannot be too far apart. This problem has applications in…

Optimization and Control · Mathematics 2025-04-28 Hubert Villuendas , Mathieu Besançon , Jérôme Malick

We prove new lower bounds for suitable competitive ratio measures of two relaxed online packing problems: online removable multiple knapsack, and a recently introduced online minimum peak appointment scheduling problem. The high level…

Data Structures and Algorithms · Computer Science 2022-01-19 János Balogh , György Dósa , Leah Epstein , Łukasz Jeż

Drug discovery is a highly complicated process, and it is unfeasible to fully commit it to the recently developed molecular generation methods. Deep learning-based lead optimization takes expert knowledge as a starting point, learning from…

The paper focuses on a new class of combinatorial problems which consists in restructuring of solutions (as sets/structures) in combinatorial optimization. Two main features of the restructuring process are examined: (i) a cost of the…

Artificial Intelligence · Computer Science 2015-12-22 Mark Sh. Levin

We study optimal policy learning under combined budget and minimum coverage constraints. We show that the problem admits a knapsack-type structure and that the optimal policy can be characterized by an affine threshold rule involving both…

Machine Learning · Statistics 2026-05-13 Giovanni Cerulli
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