Results 1 to 10 of about 644,711 (25)

Rethinking Cost-sensitive Classification in Deep Learning via Adversarial Data Augmentation [PDF]

INFORMS Journal on Data Science, 2024, 2022
Cost-sensitive classification is critical in applications where misclassification errors widely vary in cost. However, over-parameterization poses fundamental challenges to the cost-sensitive modeling of deep neural networks (DNNs). The ability of a DNN to fully interpolate a training dataset can render a DNN, evaluated purely on the training set ...
arxiv   +1 more source

Scaling ML Products At Startups: A Practitioner's Guide [PDF]

arXiv, 2023
How do you scale a machine learning product at a startup? In particular, how do you serve a greater volume, velocity, and variety of queries cost-effectively? We break down costs into variable costs-the cost of serving the model and performant-and fixed costs-the cost of developing and training new models.
arxiv  

BCEA: An R Package for Cost-Effectiveness Analysis [PDF]

arXiv, 2022
We describe in detail how to perform health economic cost-effectiveness analyses (CEA) using the R package $\textbf{BCEA}$ (Bayesian Cost-Effectiveness Analysis). CEA consist of analytic approaches for combining costs and health consequences of intervention(s).
arxiv  

Identifying optimally cost-effective dynamic treatment regimes with a Q-learning approach [PDF]

arXiv, 2021
Health policy decisions regarding patient treatment strategies require consideration of both treatment effectiveness and cost. Optimizing treatment rules with respect to effectiveness may result in prohibitively expensive strategies; on the other hand, optimizing with respect to costs may result in poor patient outcomes.
arxiv  

An Optimal Trade-off between Content Freshness and Refresh Cost [PDF]

J. Appl. Probab. 41 (2004) 721-734, 2010
Caching is an effective mechanism for reducing bandwidth usage and alleviating server load. However, the use of caching entails a compromise between content freshness and refresh cost. An excessive refresh allows a high degree of content freshness at a greater cost of system resource. Conversely, a deficient refresh inhibits content freshness but saves
arxiv   +1 more source

The mechanism of individual time cost heterogeneity promotes cooperation in snowdrift game [PDF]

arXiv, 2020
Cost of time passing plays an important role when investigate the collective behaviour in real world. Each rational individual can get a more reasonable strategy by comprehensively considering the time cost. Motivated by the fact, we here propose a mechanism with individual time cost heterogeneity whose core lies in two aspects: 1.
arxiv  

Implications on Feature Detection when using the Benefit-Cost Ratio [PDF]

arXiv, 2020
In many practical machine learning applications, there are two objectives: one is to maximize predictive accuracy and the other is to minimize costs of the resulting model. These costs of individual features may be financial costs, but can also refer to other aspects, like for example evaluation time.
arxiv  

Injecting Abstract Interpretations into Linear Cost Models [PDF]

EPTCS 28, 2010, pp. 64-81, 2010
We present a semantics based framework for analysing the quantitative behaviour of programs with regard to resource usage. We start from an operational semantics equipped with costs. The dioid structure of the set of costs allows for defining the quantitative semantics as a linear operator.
arxiv   +1 more source

Cost-aware Bayesian Optimization [PDF]

arXiv, 2020
Bayesian optimization (BO) is a class of global optimization algorithms, suitable for minimizing an expensive objective function in as few function evaluations as possible. While BO budgets are typically given in iterations, this implicitly measures convergence in terms of iteration count and assumes each evaluation has identical cost.
arxiv  

A cost-effective rumor-containing strategy [PDF]

, 2017
This paper addresses the issue of suppressing a rumor using the truth in a cost-effective way. First, an individual-level dynamical model capturing the rumor-truth mixed spreading processes is proposed. On this basis, the cost-effective rumor-containing problem is modeled as an optimization problem.
arxiv   +1 more source