7 research outputs found
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