We introduce two-scale loss functions for use in various gradient descent algorithms applied to classification problems via deep neural networks. This new method is generic in the sense that it can be applied to a wide range of machine learning architectures, from deep neural networks to support ...
aI'm really really in trouble now because United Arab Emirates company where i used to buy anti marine Chemicals don't have Chemicals said by my agent, and my deadline with Saudi Arabia with Saudi Arabia company is coming soon,[translate] ...
The problem of indecisiveness is integral part in each scientific research. However, it is still not a certainty whether this problem has an objective nature. In this paper we will extend the analysis of the sources and causes of indecisiveness and define the new categories that are a stumbling...
The primary contribution of this work includes the introduction of a machine learning-based ranker that strategically guides the search for new columns in the column generation process. The master problem solution is analyzed by the ranker, which then suggests an order for solving the pricing ...
In this post, we will look at some ideas for datasets that you could use to motivate and even accelerate your journey into applied machine learning. Problems with Impact We have looked before at the need to work on problems that have an impact. The problems that have the biggest impact are...
This diagnostic study develops a machine learning model using data from wearable digital devices to detect attention-deficit/hyperactivity disorder (ADHD)
开个天坑,121页的论文,联邦学习综述Advances and Open Problems in Federated Learning。 我还是得摒弃之前的阅读笔记模式,之前写篇阅读笔记太费时费力wwwwww,我会加油改进提炼要点的能力的(立志成为科研高手…
In recent years, it has been revealed that machine learning models can produce discriminatory predictions. Hence, fairness protection has come to play a pi
Expressivity,Trainability,and Generalization in Machine Learning 人工智能 When I read Machine Learning papers, I ask myself whether the contributions of the paper fall under improvements to 1) Expressivity 2) Trainability, and/or 3) Generalization. I learned this categorization from my colleague Jascha...
Machine Learning, 20:3, 273–297. Google Scholar Dietterich, G. B. T. G. (1999). Achieving high-accuracy text-to-speech with machine learning. In Data mining in speech synthesis. Dietterich, T. G., & Bakiri, G. (1995). Solving multiclass learning problems via error-correcting output...