Variable Length Codes for Degraded Broadcast Channels

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We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

We consider optimal regimes for algorithm-assisted human decision-making. Such regimes are decision functions of measured pre-treatment variables and, by leveraging natural treatment values, enjoy a superoptimality property whereby they are guaranteed to o ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

We introduce contextual stochastic bilevel optimization (CSBO) -- a stochastic bilevel optimization framework with the lower-level problem minimizing an expectation conditioned on some contextual information and the upper-level decision variable. This fram ...

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The reduction of energy consumption in the residential building stock and cement industry is a substantial component of the Swiss Energy Strategy 2050. Therefore, it is vital to identify the potential for EEI in these two sectors. In this study, a new meth ...

The Byzantine consensus problem involves.. processes, out of which t < n could be faulty and behave arbitrarily. Three properties characterize consensus: (1) termination, requiring correct (nonfaulty) processes to eventually reach a decision, (2) agreement ...

Risk management has become an essential element in the functioning of modern society. Correct risk identification and assessment are undoubtedly crucial to improving overall safety; nevertheless, often, it is accompanied by the wrong selection of correctiv ...

A shift from fossil-based energy and products to more sustainable alternatives is essential to reduce greenhouse gas emissions and associated climate change impacts. Biomass represents a promising alternative for providing fuels and carbon-based products w ...

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Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

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Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We im ...

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The reuse of structural components in new buildings has great potential to reduce the environmental impacts of the construction sector but remains uncommon practice. An obstacle to its wider implementation is the lack of robust assessment methods and decis ...

Variable Length Codes for Degraded Broadcast Channels

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A Pareto Dominance Principle for Data-Driven Optimization

Optimal regimes for algorithm-assisted human decision-making

Reliable data-driven decision-making through optimal transport

Contextual Stochastic Bilevel Optimization

Relatively Robust Decisions

Endogenous Energy Efficiency Improvement in Housing and Cement Sectors in Switzerland

On the Validity of Consensus

Safety risk management in University laboratories

Decision support for the design of integrated biorefineries

Safety Decision-Making for Laboratory Processes in Academia

A Functional Perspective on Information Measures

Overcoming decision paralysis—A digital twin for decision making in energy system design

Relaxed Locally Correctable Codes With Nearly-Linear Block Length And Constant Query Complexity

Symmetry in design and decoding of polar-like codes

A conceptual construct on value for infrastructure asset management

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Use of space analog missions as an educational tool in primary schools

Decision Learning and Adaptation Over Multi-Task Networks

Modeling infectious disease dynamics towards informed public health interventions, with applications on COVID-19 and cholera

Decision Framework to Balance Environmental, Technical, Logistical, and Economic Criteria When Designing Structures With Reused Components