公开(公告)号：US20160034786A1

公开(公告)日：2016-02-04

申请号：US14445463

申请日：2014-07-29

Applicant: Microsoft Corporation

Inventor： Nitin Suri ,  Xian-Sheng Hua ,  Tzong-Jhy Wang ,  William D. Sproule ,  Andrew S. Ivory ,  Jin Li

IPC: G06K9/62 ,  G06T7/20 ,  G06K9/66 ,  G06K9/46 ,  G06T7/00

CPC classification number: G06K9/6256 ,  G06K9/00744 ,  G06T7/20 ,  G06T2207/10016

Abstract: This disclosure describes techniques for training models from video data and applying the learned models to identify desirable video data. Video data may be labeled to indicate a semantic category and/or a score indicative of desirability. The video data may be processed to extract low and high level features. A classifier and a scoring model may be trained based on the extracted features. The classifier may estimate a probability that the video data belongs to at least one of the categories in a set of semantic categories. The scoring model may determine a desirability score for the video data. New video data may be processed to extract low and high level features, and feature values may be determined based on the extracted features. The learned classifier and scoring model may be applied to the feature values to determine a desirability score associated with the new video data.

Abstract translation: 本公开描述了用于从视频数据训练模型并应用所学习的模型以识别期望的视频数据的技术。 视频数据可以被标记以指示语义类别和/或指示期望性的分数。 可以处理视频数据以提取低级和高级特征。 可以基于提取的特征来训练分类器和评分模型。 分类器可以估计视频数据属于一组语义类别中的至少一个类别的概率。 评分模型可以确定视频数据的可取性得分。 可以处理新的视频数据以提取低级和高级特征，并且可以基于所提取的特征来确定特征值。 所学习的分类器和评分模型可以应用于特征值以确定与新视频数据相关联的期望得分。

公开(公告)号：US20150304420A1

公开(公告)日：2015-10-22

申请号：US14254795

申请日：2014-04-16

Applicant: Microsoft Corporation

Inventor： Jin Li ,  Sanjeev Mehrotra

IPC: H04L29/08

CPC classification number: H04L67/1097 ,  G06F9/5066 ,  G06F21/10 ,  H04L29/06 ,  H04L67/02

Abstract: Disclosed herein are systems and methods for executing programs written in functional style. A distributed computing system receives a program that expresses computation upon one or more sets of distributed key-value pairs (DKVs) and one or more global variables (GVs). The system distributes an assembly that includes at least a compiled binary of the program to the nodes of a computing cluster, with different portions of the DKVs being stored across the plurality of nodes of the computing cluster. The system causes execution of the assembly by each of the plurality of nodes of the computing cluster, the ones of the plurality of nodes executing the assembly using the different portions of the one or more DKVs stored thereon.

Abstract translation: 这里公开了用于执行以功能性风格书写的程序的系统和方法。 分布式计算系统接收在一组或多组分布式键值对（DKV）和一个或多个全局变量（GV）上表达计算的程序。 该系统将至少包含程序的编译二进制文件的程序集分发到计算集群的节点，其中DKV的不同部分被存储在计算集群的多个节点之间。 该系统使得计算集群的多个节点中的每一个节点执行组装，多个节点中的节点使用其上存储的一个或多个DKV的不同部分来执行组件。

公开(公告)号：US20130279338A1

公开(公告)日：2013-10-24

申请号：US13917441

申请日：2013-06-13

Applicant: Microsoft Corporation

Inventor： Sanjeev Mehrotra ,  Tong L. Wynn ,  Jin Li ,  Sudipta Sengupta

IPC: H04L12/70

CPC classification number: H04L47/25 ,  H04L47/22 ,  H04L47/2416 ,  H04L47/29 ,  H04L47/30

Abstract: In various embodiments, methods and systems are disclosed for a hybrid rate plus window based congestion protocol that controls the rate of packet transmission into the network and provides low queuing delay, practically zero packet loss, fair allocation of network resources amongst multiple flows, and full link utilization. In one embodiment, a congestion window may be used to control the maximum number of outstanding bits, a transmission rate may be used to control the rate of packets entering the network (packet pacing), a queuing delay based rate update may be used to control queuing delay within tolerated bounds and minimize packet loss, and aggressive ramp-up/graceful back-off may be used to fully utilize the link capacity and additive-increase, multiplicative-decrease (AIMD) rate control may be used to provide fairness amongst multiple flows.

Abstract translation: 在各种实施例中，公开了用于混合速率加上基于窗口的拥塞协议的方法和系统，其控制到网络的分组传输速率并提供低排队延迟，实际上零分组丢失，多个流之间的网络资源的公平分配以及全部 链接利用率。 在一个实施例中，可以使用拥塞窗口来控制未完成比特的最大数量，可以使用传输速率来控制进入网络的分组的速率（分组起搏），基于排队延迟的速率更新可以用于控制 可以利用容忍范围内的排队延迟并尽可能减少分组丢失，并且可以使用积极的提升/优雅退避来充分利用链路容量，并且可以使用加法增加乘法减少（AIMD）速率控制来提供多个 流动。

公开(公告)号：US09729659B2

公开(公告)日：2017-08-08

申请号：US13830950

申请日：2013-03-14

Applicant: Microsoft Corporation

Inventor： Sudipta Sengupta ,  Chenguang Zhu ,  Chun Ho Cheung ,  Jin Li ,  Abhishek Gupta

IPC: G06F15/16 ,  H04L29/08 ,  G06F17/30 ,  G06F12/0866 ,  G06F12/0804

CPC classification number: H04L67/2842 ,  G06F12/0804 ,  G06F12/0866 ,  G06F17/30097 ,  G06F17/30132 ,  G06F17/30159

Abstract: The subject disclosure is directed towards using primary data deduplication concepts for more efficient access of data via content addressable caches. Chunks of data, such as deduplicated data chunks, are maintained in a fast access client-side cache, such as containing chunks based upon access patterns. The chunked content is content addressable via a hash or other unique identifier of that content in the system. When a chunk is needed, the client-side cache (or caches) is checked for the chunk before going to a file server for the chunk. The file server may likewise maintain content addressable (chunk) caches. Also described are cache maintenance, management and organization, including pre-populating caches with chunks, as well as using RAM and/or solid-state storage device caches.

公开(公告)号：US09442929B2

公开(公告)日：2016-09-13

申请号：US13764788

申请日：2013-02-12

Applicant: Microsoft Corporation

Inventor： Sanjeev Mehrotra ,  Jin Li ,  Abhinav Shrivastava

IPC: G06F17/30

CPC classification number: G06F17/30011 ,  G06F17/3069

Abstract: A computer-implemented method and system for determining documents that are nearest to a query are provided herein. The method includes constructing a vantage point tree based on a number of document vectors. The method also includes searching the vantage point tree to determine a number of nearest neighbor document vectors to a query vector by removing a portion of the document vectors from the vantage point tree based on one or more vantage points for each of a number of nodes in the vantage point tree and a specified search radius centered about the query vector.

Abstract translation: 本文提供了一种用于确定最接近查询的文档的计算机实现的方法和系统。 该方法包括基于许多文档向量构建有利位置点树。 该方法还包括通过基于一个或多个有利位置从多个有利位置点树中的多个节点中的每个节点移除一部分文档向量来确定查询向量的最近邻文档向量的数目， 有利位置树和以查询向量为中心的指定搜索半径。

公开(公告)号：US09378084B2

公开(公告)日：2016-06-28

申请号：US13926722

申请日：2013-06-25

Applicant: MICROSOFT CORPORATION

Inventor： Bradley G. Calder ,  Parikshit Santhana Gopalan ,  Cheng Huang ,  Jin Li ,  Aaron W. Ogus ,  Huseyin Simitci ,  Sergey Yekhanin

IPC: G06F11/00 ,  G06F11/10

CPC classification number: G06F11/10 ,  G06F11/1076 ,  H03M13/2909 ,  H03M13/293 ,  H03M13/373

Abstract: In various embodiments, methods and systems for erasure coding data across multiple storage zones are provided. This may be accomplished by dividing a data chunk into a plurality of sub-fragments. Each of the plurality of sub-fragments is associated with a zone. Zones comprise buildings, data centers, and geographic regions providing a storage service. A plurality of reconstruction parities is computed. Each of the plurality of reconstruction parities computed using at least one sub-fragment from the plurality of sub-fragments. The plurality of reconstruction parities comprises at least one cross-zone parity. The at least one cross-zone parity is assigned to a parity zone. The cross-zone parity provides cross-zone reconstruction of a portion of the data chunk.

Abstract translation: 在各种实施例中，提供用于擦除跨多个存储区域的编码数据的方法和系统。 这可以通过将数据块划分成多个子片段来实现。 多个子片段中的每一个与区域相关联。 区域包括提供存储服务的建筑物，数据中心和地理区域。 计算多个重建奇偶校验。 使用来自多个子片段的至少一个子片段来计算多个重建奇偶校验中的每一个。 多个重建奇偶校验包括至少一个跨区域奇偶校验。 至少一个跨区奇偶校验被分配给奇偶校验区。 跨区域奇偶校验提供了一部分数据块的跨区域重建。

公开(公告)号：US20150317389A1

公开(公告)日：2015-11-05

申请号：US14266228

申请日：2014-04-30

Applicant: Microsoft Corporation

Inventor： Xian-Sheng Hua ,  Jin Li ,  Yoshitaka Ushiku

IPC: G06F17/30 ,  G06N99/00

CPC classification number: G06F17/30705 ,  G06F17/30675 ,  G06F17/30864 ,  G06N99/005

Abstract: Systems and methods for learning topic models from unstructured data and applying the learned topic models to recognize semantics for new data items are described herein. In at least one embodiment, a corpus of multimedia data items associated with a set of labels may be processed to generate a refined corpus of multimedia data items associated with the set of labels. Such processing may include arranging the multimedia data items in clusters based on similarities of extracted multimedia features and generating intra-cluster and inter-cluster features. The intra-cluster and the inter-cluster features may be used for removing multimedia data items from the corpus to generate the refined corpus. The refined corpus may be used for training topic models for identifying labels. The resulting models may be stored and subsequently used for identifying semantics of a multimedia data item input by a user.

Abstract translation: 本文描述了用于从非结构化数据学习主题模型并应用所学习的主题模型以识别新数据项的语义的系统和方法。 在至少一个实施例中，可以处理与一组标签相关联的多媒体数据项的语料库，以生成与该组标签相关联的多媒体数据项的精简语料库。 这种处理可以包括基于提取的多媒体特征的相似性来排列多媒体数据项，并且生成集群内和集群间特征。 集群内和集群间特征可以用于从语料库中移除多媒体数据项以产生精炼的语料库。 精致的语料库可用于训练用于识别标签的主题模型。 所得到的模型可以被存储并随后用于识别由用户输入的多媒体数据项的语义。

公开(公告)号：US20140310571A1

公开(公告)日：2014-10-16

申请号：US13863912

申请日：2013-04-16

Applicant: MICROSOFT CORPORATION

Inventor： Dennis Craig Fetterly ,  Parikshit S. Gopalan ,  Cheng Huang ,  Robert John Jenkins, JR. ,  Jin Li ,  Sergey Yekhanin

IPC: G06F11/10

CPC classification number: G06F11/1076 ,  G06F11/1088 ,  G06F2211/1057

Abstract: In some examples, an erasure code can be implemented to provide for fault-tolerant storage of data. Maximally recoverable cloud codes, resilient cloud codes, and robust product codes are examples of different erasure codes that can be implemented to encode and store data. Implementing different erasure codes and different parameters within each erasure code can involve trade-offs between reliability, redundancy, and locality. In some examples, an erasure code can specify placement of the encoded data on machines that are organized into racks.

Abstract translation: 在一些示例中，可以实现擦除代码以提供数据的容错存储。 最大可恢复的云代码，弹性云代码和强大的产品代码是可以实现的数据编码和存储的不同擦除代码的示例。 在每个擦除代码中实现不同的擦除代码和不同的参数可以包括可靠性，冗余和局部性之间的权衡。 在一些示例中，擦除代码可以指定将编码数据放置在组织到机架中的机器上。

公开(公告)号：US20140229473A1

公开(公告)日：2014-08-14

申请号：US13764788

申请日：2013-02-12

Applicant: MICROSOFT CORPORATION

Inventor： Sanjeev Mehrotra ,  Jin Li ,  Abhinav Shrivastava

IPC: G06F17/30

CPC classification number: G06F17/30011 ,  G06F17/3069

Abstract: A computer-implemented method and system for determining documents that are nearest to a query are provided herein. The method includes constructing a vantage point tree based on a number of document vectors. The method also includes searching the vantage point tree to determine a number of nearest neighbor document vectors to a query vector by removing a portion of the document vectors from the vantage point tree based on one or more vantage points for each of a number of nodes in the vantage point tree and a specified search radius centered about the query vector.

Abstract translation: 本文提供了一种用于确定最接近查询的文档的计算机实现的方法和系统。 该方法包括基于许多文档向量构建有利位置点树。 该方法还包括通过基于一个或多个有利位置从多个有利位置点树中的多个节点中的每个节点移除一部分文档向量来确定向查询向量的最近邻文档向量的数目， 有利位置树和以查询向量为中心的指定搜索半径。

公开(公告)号：US09244761B2

公开(公告)日：2016-01-26

申请号：US14223596

申请日：2014-03-24

Applicant: MICROSOFT CORPORATION

Inventor： Sergey Yekhanin ,  Huseyin Simitci ,  Aaron W. Ogus ,  Jin Li ,  Cheng Huang ,  Parikshit Santhan Gopalan ,  Bradley G. Calder

IPC: G06F11/00 ,  G06F11/10

CPC classification number: G06F11/10 ,  G06F11/1076 ,  H03M13/2909 ,  H03M13/293 ,  H03M13/373 ,  H04L67/1097

Abstract: In various embodiments, methods and systems for erasure coding data across multiple storage zones are provided. This may be accomplished by dividing a data chunk into a plurality of sub-fragments. Each of the plurality of sub-fragments is associated with a zone. Zones comprise buildings, data centers, and geographic regions providing a storage service. A plurality of reconstruction parities is computed. Each of the plurality of reconstruction parities computed using at least one sub-fragment from the plurality of sub-fragments. The plurality of reconstruction parities comprises at least one cross-zone parity. The at least one cross-zone parity is assigned to a parity zone. The cross-zone parity provides cross-zone reconstruction of a portion of the data chunk.

Abstract translation: 在各种实施例中，提供用于擦除跨多个存储区域的编码数据的方法和系统。 这可以通过将数据块划分成多个子片段来实现。 多个子片段中的每一个与区域相关联。 区域包括提供存储服务的建筑物，数据中心和地理区域。 计算多个重建奇偶校验。 使用来自多个子片段的至少一个子片段来计算多个重建奇偶校验中的每一个。 多个重建奇偶校验包括至少一个跨区域奇偶校验。 至少一个跨区奇偶校验被分配给奇偶校验区。 跨区域奇偶校验提供了一部分数据块的跨区域重建。