Machine Learning algorithms are becoming widely deployed in real world decision-making. Ensuring fairness in algorithmic decision-making is a crucial policy …
Links Category: Machine Learning
Machine Learning Model Governance
Machine learning (ML) models need governance just like other models, only more so. This is particularly true of ML models designed to improve automatically …
Combining Supervised and Unsupervised Machine Learning
Executive Summary. Darktrace is a research and development-led company that first applied unsupervised machine learning to the challenge of detecting …
Xilinx Machine Learning Strategies For Edge
NIPS 2015: Top conference in neural information processing. FPGA 2016 & 2017: Top academic conference in FPGA. ICLR 2016 : Top academic conference in …
Machine Learning Systems are Stuck in a Rut – ACM Digital …
Abstract. In this paper we argue that systems for numerical com- puting are stuck in a local basin of performance and programmability.
The Seven Tools of Causal Inference with Reflections on …
The dramatic success in machine learning has led to an explosion of. AI applications and increasing expectations for autonomous systems.
Machine Learning for Databases – VLDB Endowment
ABSTRACT. Machine learning techniques have been proposed to optimize the databases. For example, traditional empirical database optimiza-.
Machine Learning Moves to the Edge – The Linley Group
Embedded systems at the edge of the network are at the beginning of a revolution. These devices will increasingly use machine learning (ML) to deliver new …
A Brief Survey of Machine Learning Methods and their Sensor …
Abstract—This paper provides a brief survey of the basic concepts and algorithms used for Machine Learning and its applications. We begin with a broader …
Soul and Machine (Learning) – Harvard Business School
Business, Harvard Business School, MIT Sloan School of Management, Duke Fuqua School of Business, CMU. Tepper School of Business, Independent, …