Microsoft

About: Microsoft is a company organization based out in Redmond, Washington, United States. It is known for research contribution in the topics: User interface & Context (language use). The organization has 49501 authors who have published 86900 publications receiving 4195429 citations. The organization is also known as: MS & MSFT.

Scalable designs for quasiparticle-poisoning-protected topological quantum computation with Majorana zero modes

Abstract: We present designs for scalable quantum computers composed of qubits encoded in aggregates of four or more Majorana zero modes, realized at the ends of topological superconducting wire segments that are assembled into superconducting islands with significant charging energy. Quantum information can be manipulated according to a measurement-only protocol, which is facilitated by tunable couplings between Majorana zero modes and nearby semiconductor quantum dots. Our proposed architecture designs have the following principal virtues: (1) the magnetic field can be aligned in the direction of all of the topological superconducting wires since they are all parallel; (2) topological T junctions are not used, obviating possible difficulties in their fabrication and utilization; (3) quasiparticle poisoning is abated by the charging energy; (4) Clifford operations are executed by a relatively standard measurement: detection of corrections to quantum dot energy, charge, or differential capacitance induced by quantum fluctuations; (5) it is compatible with strategies for producing good approximate magic states.

Detours: binary interception of Win32 functions

Abstract: Innovative systems research hinges on the ability to easily instrument and extend existing operating system and application functionality. With access to appropriate source code, it is often trivial to insert new instrumentation or extensions by rebuilding the OS or application. However, in today's world of commercial software, researchers seldom have access to all relevant source code. We present Detours, a library for instrumenting arbitrary Win32 functions on x86 machines. Detours intercepts Win32 functions by re-writing target function images. The Detours package also contains utilities to attach arbitrary DLLs and data segments (called payloads) to any Win32 binary. While prior researchers have used binary rewriting to insert debugging and profiling instrumentation, to our knowledge, Detours is the first package on any platform to logically preserve the un-instrumented target function (callable through a trampoline) as a subroutine for use by the instrumentation. Our unique trampoline design is crucial for extending existing binary software. We describe our experiences using Detours to create an automatic distributed partitioning system, to instrument and analyze the DCOM protocol stack, and to create a thunking layer for a COM-based OS API. Micro-benchmarks demonstrate the efficiency of the Detours library.

Shift: a technique for operating pen-based interfaces using touch

Abstract: Retrieving the stylus of a pen-based device takes time and requires a second hand. Especially for short intermittent interactions many users therefore choose to use their bare fingers. Although convenient, this increases targeting times and error rates. We argue that the main reasons are the occlusion of the target by the user's finger and ambiguity about which part of the finger defines the selection point. We propose a pointing technique we call Shift that is designed to address these issues. When the user touches the screen, Shift creates a callout showing a copy of the occluded screen area and places it in a non-occluded location. The callout also shows a pointer representing the selection point of the finger. Using this visual feedback, users guide the pointer into the target by moving their finger on the screen surface and commit the target acquisition by lifting the finger. Unlike existing techniques, Shift is only invoked when necessary--over large targets no callout is created and users enjoy the full performance of an unaltered touch screen. We report the results of a user study showing that with Shift participants can select small targets with much lower error rates than an unaided touch screen and that Shift is faster than Offset Cursor for larger targets.

Information retrieval by natural language querying

Abstract: A natural language information querying system includes an indexing facility configured to automatically generate indices of updated textual sources based on one or more predefined grammars and a database coupled to the indexing facility to store the indices for subsequent searching.

FloatBoost learning and statistical face detection

Abstract: A novel learning procedure, called FloatBoost, is proposed for learning a boosted classifier for achieving the minimum error rate. FloatBoost learning uses a backtrack mechanism after each iteration of AdaBoost learning to minimize the error rate directly, rather than minimizing an exponential function of the margin as in the traditional AdaBoost algorithms. A second contribution of the paper is a novel statistical model for learning best weak classifiers using a stagewise approximation of the posterior probability. These novel techniques lead to a classifier which requires fewer weak classifiers than AdaBoost yet achieves lower error rates in both training and testing, as demonstrated by extensive experiments. Applied to face detection, the FloatBoost learning method, together with a proposed detector pyramid architecture, leads to the first real-time multiview face detection system reported.