Microsoft Research

During this talk I will be giving a demo of Madoko: a scholarly markdown processor that enables light-weight creation of high-quality scholarly and industrial documents with a focus on simplicity

1st Code Hunt Workshop Microsoft Research, Redmond, WA Conference Room 99/1919 February 9-10, 2015 Goals of the workshop - To expose the state of the platform and data of Code Hunt and its

Natural-language question answering (QA) has clear practical and scientific values, such as evaluating a machine’s understanding of a domain, or providing succinct and precise answers to search

1st Code Hunt Workshop Microsoft Research, Redmond, WA Conference Room 99/1919 February 9-10, 2015 Goals of the workshop - To expose the state of the platform and data of Code Hunt and its

1st Code Hunt Workshop Microsoft Research, Redmond, WA Conference Room 99/1919 February 9-10, 2015 Goals of the workshop - To expose the state of the platform and data of Code Hunt and its

Asynchrony is fundamental to a broad class of software systems such as device drivers, cloud infrastructure, interacting web services, and client-server web applications.

In parallel programs, threads communicate according to the memory consistency model: the set of memory ordering rules enforced by a given architecture.

1st Code Hunt Workshop Microsoft Research, Redmond, WA Conference Room 99/1919 February 9-10, 2015 Goals of the workshop - To expose the state of the platform and data of Code Hunt and its

1st Code Hunt Workshop Microsoft Research, Redmond, WA Conference Room 99/1919 February 9-10, 2015 Goals of the workshop - To expose the state of the platform and data of Code Hunt and its

Regular algebra provides a full set of simple laws for the programming of abstract state machines by regular expressions. They apply equally to sequential programs run on real computers.

Mental health and wellbeing are fundamental to our quality of life, enabling us to be resilient against everyday stresses, work productively, and experience life as meaningful.

Most of the currently available speech enhancement algorithms use a statistical signal processing approach to remove the noise component from observed signals.

DNA computing is emerging as a versatile technology that promises a vast range of applications, including biosensing, drug delivery and synthetic biology.

Challenges in automated verification and synthesis for molecular programming

…musical tones are the simpler and more regular elements of the sensations of hearing, and that we have consequently first to study the laws and peculiarities of this class of sensations.

Typical high-dimensional learning problems such as sparse regression, low-rank matrix completion, robust PCA etc can be solved using projections onto non-convex sets.

We study the design of a recommender system for organizing social learning on a product.

This talk will introduce scikit-learn, an Open Source project for Machine Learning in Python and review some new features from the recent 0.15 release: faster randomized ensemble of decision trees

We think we know what shapes are, right? Maybe you think of squares, circles, ovals? But nothing in nature has these shapes, even away from the atomic scale.

Health apps have become common, with thousands on app stores. Among the most common are those that address mental health problems.

The study of monotonicity and negation complexity for Boolean functions has been prevalent in complexity theory as well as in computational learning theory, but little attention has been given to it

The general perception is that kernel methods are not scalable, and neural nets are the methods of choice for nonlinear learning problems. Or have we simply not tried hard enough for kernel methods?

For some time my colleagues and I have been studying cancer tumor boards, now rapidly becoming molecularized by the molbio/omics/big-data revolutions.

We study the general problem of how to learn through experience to make intelligent decisions.

Cell cycle switching by an algorithm

Typical high-dimensional learning problems such as sparse regression, low-rank matrix completion, robust PCA etc can be solved using projections onto non-convex sets.

I will describe recent joint work with Sara Billey (UW) and Alexander Holroyd (MSR), generalizing earlier work of mine, in which we bijectively prove the general case of Macdonald's identity in

The state-of-the-art in object recognition has undergone dramatic changes in the last 20 years.

The time taken by an algorithm to make predictions is of critical importance as machine learning transitions to becoming a service available on the cloud.

The aim of this tutorial is to introduce tools and techniques that are used to analyze machine learning algorithms in statistical settings.