Machine Learning at Microsoft with ML .NET

Machine Learning is transitioning from an art and science into a technology available to every developer. In the near future, every application on every platform will incorporate trained models to encode data-based decisions that would be impossible for developers to author. This presents a significant engineering challenge, since currently data science and modeling are largely decoupled from standard software development processes. This separation makes incorporating machine learning capabilities inside applications unnecessarily costly and difficult, and furthermore discourage developers from embracing ML in first place. In this paper we present ML .NET, a framework developed at Microsoft over the last decade in response to the challenge of making it easy to ship machine learning models in large software applications. We present its architecture, and illuminate the application demands that shaped it. Specifically, we introduce DataView, the core data abstraction of ML .NET which allows it to capture full predictive pipelines efficiently and consistently across training and inference lifecycles. We close the paper with a surprisingly favorable performance study of ML .NET compared to more recent entrants, and a discussion of some lessons learned

Contracting Experts with Unknown Cost Structures

We investigate the problem of a principal contracting an expert to provide a probability forecast for a binary event. Experts can research this event at a cost unknown to the principal. We present a truthful and efficient mechanism for the principal's problem of contracting an expert. This results in the principal contracting the best expert to do work equivalent to having the second best expert in-house. We discuss several extensions to this mechanism. The contracts in [9] are used to generalize our mechanism to non-binary events. We consider how the mechanism is affected when the principal and experts have a maximum acceptable risk and cannot afford to exceed a certain budget. Finally, we discuss the result of the experts changing their belief before the mechanism - either due to a signal they received or due to costly research that they carry out

Search using queries on indistinguishable items

We investigate the problem of determining a set S of k indistinguishable integers in the range [1, n]. The algorithm is allowed to query an integer q ∈ [1, n], and receive a response comparing this integer to an integer randomly chosen from S. The algorithm has no control over which element of S the query q is compared to. We show tight bounds for this problem. In particular, we show that in the natural regime where k ≤ n, the optimal number of queries to attain n −Ω(1) error probability is Θ(k 3 log n). In the regime where k> n, the optimal number of queries is Θ(n 2 k log n). Our main technical tools include the use of information theory to derive the lower bounds, and the application of noisy binary search in the spirit of Feige, Raghavan, Peleg, and Upfal (1994). In particular, our lower bound technique is likely to be applicable in other situations that involve search under uncertainty

From boundary spanning to creolization: a study of Chinese software and services outsourcing vendors

In achieving success in global sourcing arrangements, the role of a cultural liaison, boundary spanner or transnational intermediary is frequently highlighted as being critical. This paper critiques, builds upon and synthesizes relevant streams of ideas in relation to boundary-spanning and cross-cultural management across a number of disciplines, and constructs a multi-layered creolization framework, encompassing processes at the individual, intra- and inter-organizational and inter-national levels which, we argue, are entangled and interrelated. Viewed as a vital and innovative phenomenon, creolization embodies the interactive, contentious and creative processes of network expansion, mutual sensemaking, cultural hybridity and identity multiplicity. Qualitative empirical data from the software and services outsourcing industry in Northwest China is used to demonstrate the complexity of cross-cultural practices in offshore collaborations and illustrate creolization processes. Potentials for theoretical development are outlined and implications for cross-cultural practices are discussed