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Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest. The system leverages big data to find examples that maximize the training value of its interaction with the teacher.
Project details
Labs: Redmond
Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest. The system leverages big data to find examples that maximize the training value of its interaction with the teacher.
Project details
Labs: Redmond
The Kamino project explores ways in which systems should adopt new memory technologies including SSDs (NAND-Flash), battery-backed DRAM and emerging non-volatile memory technologies (phase change memory, memristors, spin-torque transfer memory, etc.) for increased performance and efficiency. The project explores how to best leverage such new memory technologies inside systems of all sizes and shapes: from mobile to data center scale.
Project details
Labs: Redmond
We introduce a novel approach for automatically generating image descriptions. Visual detectors, language models, and deep multimodal similarity models are learned directly from a dataset of image captions. Our system is state-of-the-art on the official Microsoft COCO benchmark, producing a BLEU-4 score of 29.1%. Human judges consider the captions to be as good as or better than humans 34% of the time.
Project details
Labs: Redmond
Project details
Labs: Redmond
The Eye Gaze keyboard is a project to enable people who are unable to speak or use a physical keyboard to communicate using only their eyes. Our initial prototypes are based around an on screen qwerty keyboard very similar to the 'taptip' keyboard built into Windows 8 which has been extended to response to eye gaze input from a sensor bar like the Tobii EyeX. Our goal is to improve communication speed by 25% compared to experienced users of off the shelf Speech Generating Devices.
This project aims to enable people to converse with their devices. We are trying to teach devices to engage with humans using human language in ways that appear seamless and natural to humans. Our research focuses on statistical methods by which devices can learn from human-human conversational interactions and can situate responses in the verbal context and in physical or virtual environments.
Project details
Labs: Redmond
Project details
Labs: Redmond
The Logical Form analysis produced by the NLPwin parser is very close in spirit to the level of semantic representation defined in AMR, Abstract Meaning Representation. The "NLPwin parses AMR" project is a conversion from LF to AMR in order to facilitate 1) evaluation of the NLPwin LF and 2) contribution the ongoing discussion of the specification of AMR. In this project, we include publications, as well as links to our LF training data converted to AMR and to the LF-AMR parser for English.
Project details
Labs: Redmond
This is a project looking into design and evaluation of efficient and deployable algorithms for assignment of complex workloads to resources in modern cloud service platforms.
Project details
Labs: Cambridge
The Indoor Patrol Robot is a low cost holonomic-drive enabled robot that can navigate autonomously indoors using just RGB and ultrasonic sensors. The robot leverages the Better Together Framework to allow real-time remote-viewing of the video, and includes a feature to upload photos to OneDrive. The robot can sef-navigate to a charging base, enabling 24/7 maintenance-free operation.
Project details
Labs: Asia
The aim of this project is to develop a personalized recommendation system for the timelines of twitter users where tweets are ranked by the user's home location and personal interests. TRUPIL addresses the challenge of Twitter users who tend to post short messages of 140 characters reflecting a variety of topics. The large volume of posts in several topics is overwhelming to twitter users who might be interested in only few topics.
Project details
Labs: ATL Cairo
The ability to detect human actions in real-time is fundamental to several applications such as surveillance, gaming, and sign language detection. These applications demand accurate and robust localization of actions at low latencies which remains a very challenging computer vision task. In this project we present efficient descriptors for action detection on RGBD sequences.
Project details
Labs: ATL Cairo
Project Blush explorers the materiality of digital ephemera and people's receptiveness to 'digital jewellery' - exploring the materials and aesthetics that may allow wearables to become jewellables.Project Blush is a research project that originates from the Human Experience and Design group (HXD). HXD specialise in designing and fabricating new human experiences with computing. These play on many different kinds of human values, from amplifying efficiency and effectiveness to creating delight a
Project details
Labs: Cambridge
Code Hunt is a serious educational game. The Code Hunt community is interested in all aspects of research and development around the game, including analysis of the data and development of the platform.
Project details
Labs: Redmond
Code Hunt is a serious gaming platform for coding contests and practicing programming skills. It is based on the symbolic white box execution engine, Pex. Code Hunt is unique as an online coding platform in that each puzzle is presented with test cases only, no specification. Players have to first work out the pattern and then code the answer. Code Hunt has been used by over 100,000 players as of February 2015.
Project details
Labs: Redmond
Catapult is a Microsoft project investigating the use of field-programmable gate arrays (FPGAs) to improve performance, reduce power, and provide new capabilities in the datacenter.
Project details
Labs: Redmond
Deep Structured Semantic Model / Deep Semantic Similarity Model
Project details
Labs: Redmond
FaST-LMM (Factored Spectrally Transformed Linear Mixed Models) is a set of tools for performing genome-wide association studies (GWAS) on large data sets. FaST-LMM runs on both Windows and Linux, and contains code to do (1) univariate GWAS, (2) testing sets of SNPs, (3) feature selection for background correction, (4) epistatic association scans, (5) a correction method for cellular heterogeneity in methylation and similar data.
Project details
Team Three Rs is a group of Microsoft Researchers working on the Global Learning XPRIZE challenge, which aims to create software to help children in the developing world achieve success in learning the "Three Rs" (Reading, Writing, and Arithmetic.
Project details
We envision using Eye Gaze technology to bring independent mobility to people living with disabilities who are unable to use a joystick.
Parasail is a novel approach to parallelizing a large class of seemingly sequential applications wherein dependencies are, at runtime, treated as symbolic values. The efficiency of parallelization, then, depends on the efficiency of the symbolic computation, an active area of research in static analysis, verification, and partial evaluation. This is exciting as advances in these fields can translate to novel parallel algorithms for sequential computation.
Project details
Labs: Redmond
NLPwin is a software project at Microsoft Research that aims to provide Natural Language Processing tools for Windows (hence, NLPwin). The project was started in 1991, just as Microsoft inaugurated the Microsoft Research group; while active development of NLPwin continued through 2002, it is still being updated regularly, primarily in service of Machine Translation.
Project details
Labs: Redmond
We explore grip and motion sensing to afford new techniques that leverage how users naturally manipulate tablet and stylus devices during pen-and-touch interaction. We can detect whether the user holds the pen in a writing grip or tucked between his fingers. We can distinguish bare-handed inputs, such as drag and pinch gestures, from touch gestures produced by the hand holding the pen, and we can sense which hand grips the tablet, and determine the screen's relative orientation to the pen.
Project details
Labs: Redmond
Mano-a-Mano is a unique spatial augmented reality system that combines dynamic projection mapping, multiple perspective views and device-less interaction to support face-to-face, or dyadic, interaction with 3D virtual objects. Its main advantage over more traditional AR approaches is users are able to interact with 3D virtual objects and each other without cumbersome devices that obstruct face to face interaction.
Project details
Labs: Redmond
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