Microsoft Research

We propose a new market design for display advertising contracts, based on posted prices.

In many applications, we face the challenge of modeling the interactions between multiple observations.

The BodyTrack project develops open source tools to aggregate and visualize self-tracking data from a variety of sources.

Opinions in social media are increasingly used by individuals and organizations for making purchase decisions and for marketing and product design.

In many modern optimization problems, specifically those arising in machine learning, the amount data is too large to apply standard convex optimization methods.

The existence of nonlinear and turbulent phenomena in the speech production process has been theoretically and experimentally established.

A user-level deterministic log/replay system is able to faithfully re-enact a past multithreaded execution without any modifications to the underlying OS or hardware.

In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not scale well due to

An important byproduct of the emergence of social networking platforms is an access to abundance of social data in all forms: blogs, clicks, facebook feeds, transactions and tweets.

Pointers are ubiquitous in modern object-oriented programming languages, and many data structures such as trees, lists, graphs, hash tables, etc. depend on them heavily.

Stan Kurkovsky is a Professor of Computer Science at Central Connecticut State University.

I will introduce Causality Checking, a technique extending model checking designed to establish causalities for safety property violations in system models.

�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.

My field of Micro-Electro-Mechanical Systems (MEMS) has advanced tremendously for the last 20 years.

Stress has been regarded as an exacerbating factor for many physical and mental disorders. Stress management considers the detection and mitigation of stress.

The preferred listening level for music and speech in cars depends on the environmental noise, which can vary dynamically.

Network data structures have been used extensively in recent years for modeling entities and their ties for many diverse disciplines.

At the heart of most machine learning problems lies a regularized risk minimization problem.

In this talk I will quantify the resources (number of qubits, number of quantum gates, computation time) needed to perform error correction with the surface code.

The understanding of e.g. multifactorial diseases requires the discovery of entities and their relationships from several domains: proteomics, metabolomics, toxicology, etc.

The challenge of making elections demonstrably accurate while guaranteeing ballot secrecy with minimal trust assumptions has been taken up by the crypto/security community.

In this work, we investigate the relationships between social network structure and personality; we assess the performances of different subsets of structural network features, and in particular

The classical result of Erdos and Renyi shows that the random graph G(n,p) experiences sharp phase transition around p=1/n -- for any \epsilon0 and p=(1-\epsilon)/n, all connected components of

The first explicit expander graph family was constructed by G. Margulis in the 1970�s. In this expository lecture, a simple proof will be given that these graphs indeed have the expansion property

Program analysis is a challenging task when source code is available. It is even more challenging when analyzing malware where neither the source code nor debug information are present.

I will discuss algorithms for reversible and quantum circuit synthesis that guarantee different kinds of optimality.

In this talk, we will describe an efficient software implementation of characteristic 2 fields making extensive use of vector instruction sets commonly found in desktop processors.

Properly designed and engineered computerized voting systems can facilitate voting and increase the security and reliability of our voting systems.

Machine solvers are a class of general-purpose software tools which input a set of equations and output a satisfying assignment to these equations (or a proof of unsatisfiability).

Cryptographic standards abound: TLS, SSH, IPSec, XML Encryption, PKCS, and so many more.