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1. 发明申请

US20180107716A1 LOWER-DIMENSIONAL SUBSPACE APPROXIMATION OF A DATASET 审中-公开
公开(公告)号：US20180107716A1
公开(公告)日：2018-04-19
申请号：US15295388
申请日：2016-10-17
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Kenneth L. Clarkson , David P. Woodruff
IPC分类号： G06F17/30
CPC分类号： G06F16/24561 , G06F16/334 , G06F16/35
摘要： A lower-dimensional representation (e.g., approximation) of a dataset is determined. The lower-dimensional representation can be used, for example, to perform semantic document analysis. Given a matrix of input data points, where each entry of the matrix indicates a number of times a particular term in a set of terms appears in a particular document in a set of documents, a lower-dimensional compressed matrix is obtained from the matrix by sampling rows of the matrix based on a target rank parameter, a desired accuracy tolerance, leverage scores calculated for the rows, and/or distances from rows of the matrix to a span of the initial set of sampled rows. The compressed matrix is used to determine a similarity metric indicative of a degree of similarity between documents. The documents can then be classified into a same document cluster or different clusters based on whether the similarity metric satisfied a threshold value.

2. 发明授权

US09928214B2 Sketching structured matrices in nonlinear regression problems 有权
公开(公告)号：US09928214B2
公开(公告)日：2018-03-27
申请号：US14333978
申请日：2014-07-17
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Haim Avron , Vikas Sindhwani , David P. Woodruff
IPC分类号： G06F17/18 , G06F17/16 , G06F17/10 , G06F17/27
CPC分类号： G06F17/18 , G06F17/10 , G06F17/16 , G06F17/2785
摘要： A system, method and computer program product for quickly and approximately solving structured regression problems. In one aspect, the system, method and computer program product are applied to problems that arise naturally in various statistical modeling settings—when the design matrix is a Vandermonde matrix or a sequence of such matrices. Using the Vandermonde matrix structure further accelerates the solution of the regression problem, achieving running times that are faster than “input sparsity”. The modeling framework speedup benefits of randomized regression for solving structured regression problems.

3. 发明授权

US09438705B2 Communication and message-efficient protocol for computing the intersection between different sets of data 有权
公开(公告)号：US09438705B2
公开(公告)日：2016-09-06
申请号：US14107097
申请日：2013-12-16
申请人： International Business Machines Corporation
发明人： David P. Woodruff , Grigory Yaroslavtsev
IPC分类号： G06F7/04 , G06F17/30 , H04L29/06
CPC分类号： H04L69/24 , G06F17/30017 , G06F17/30283 , G06F17/30312 , H04L67/1097 , H04L69/166 , H04L69/26
摘要： Embodiments relate to data processing. A method includes analyzing a plurality of data items in a relational database, where different portions of the data items are stored in a plurality of servers. The method also includes determining a maximum size of a subset of the data items stored in each of at least two servers among the plurality of servers, calculating a logarithm function based on the maximum size of the subset of the data items in each of the two servers, and calculating a highest number of sequences of communications between the two servers such that when the logarithmic function is iteratively applied, a value of the logarithmic function remains smaller than one. A protocol is then generated between the two servers for performing an intersection operation using the highest number of sequences calculated.

4. 发明申请

US20140280426A1 INFORMATION RETRIEVAL USING SPARSE MATRIX SKETCHING 审中-公开
标题翻译：使用SPARSE MATRIX草图的信息检索
公开(公告)号：US20140280426A1
公开(公告)日：2014-09-18
申请号：US13800497
申请日：2013-03-13
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Kenneth L. Clarkson , David P. Woodruff
IPC分类号： G06F17/16
CPC分类号： G06F17/16
摘要： Embodiments of the invention include method of approximating a matrix of data using sparse matrices which includes receiving a first matrix and generating a second matrix based on the first matrix and a first sparse matrix. The method further includes generating a third matrix based on the first matrix and a second sparse matrix and generating a fourth matrix by generating a Moore-Penrose pseudo-inverse matrix based on the first matrix, the second matrix and the third matrix. The method also includes generating a fifth matrix based on a product of the second matrix, the third matrix, and a fourth matrix. The method further includes receiving, by a computer, a request to access at least one entry of the first matrix and responding to the request by accessing an entry of the fifth matrix.
摘要翻译：本发明的实施例包括使用稀疏矩阵逼近数据矩阵的方法，该稀疏矩阵包括接收第一矩阵并且基于第一矩阵和第一稀疏矩阵生成第二矩阵。该方法还包括基于第一矩阵和第二稀疏矩阵生成第三矩阵，并且通过基于第一矩阵，第二矩阵和第三矩阵生成摩尔 - 彭罗斯伪逆矩阵来产生第四矩阵。该方法还包括基于第二矩阵，第三矩阵和第四矩阵的乘积生成第五矩阵。该方法还包括由计算机接收访问第一矩阵的至少一个条目并通过访问第五矩阵的条目来响应该请求的请求。

5. 发明申请

US20160117285A1 FINDING A CUR DECOMPOSITION 有权
标题翻译：找到一个CUR分解
公开(公告)号：US20160117285A1
公开(公告)日：2016-04-28
申请号：US14525917
申请日：2014-10-28
申请人： International Business Machines Corporation
发明人： Christos Boutsidis , David P. Woodruff
IPC分类号： G06F17/16
CPC分类号： G06F17/16 , H03M7/30 , H03M7/3082
摘要： One embodiments is a computer-implemented method for finding a CUR decomposition. The method includes constructing, by a computer processor, a matrix C based on a matrix A. A matrix R is constructed based on the matrix A and the matrix C. A matrix U is constructed based on the matrices A, C, and R. The matrices C, U, and R provide a CUR decomposition of the matrix A. The construction of the matrices C, U, and R provide at least one of an input-sparsity-time CUR and a deterministic CUR.
摘要翻译：一个实施例是用于找到CUR分解的计算机实现的方法。该方法包括由计算机处理器基于矩阵A构建矩阵C.基于矩阵A和矩阵C构建矩阵R.矩阵U基于矩阵A，C和R构成。矩阵C，U和R提供矩阵A的CUR分解。矩阵C，U和R的构造提供输入稀疏时间CUR和确定性CUR中的至少一个。

6. 发明申请

US20160034201A1 MANAGING DE-DUPLICATION USING ESTIMATED BENEFITS 审中-公开
标题翻译：使用预期的好处管理失效
公开(公告)号：US20160034201A1
公开(公告)日：2016-02-04
申请号：US14450889
申请日：2014-08-04
申请人： International Business Machines Corporation
发明人： David D. Chambliss , M. Corneliu Constantinescu , Joseph S. Glider , Danny Harnik , Maohua Lu , David P. Woodruff
IPC分类号： G06F3/06 , G06F12/10
CPC分类号： G06F3/0608 , G06F3/0641 , G06F3/0671 , G06F12/1018 , G06F16/1748 , G06F2212/1044 , G06F2212/65
摘要： A protocol is employed to estimate duplication of data in a storage system. This estimate is employed as a factor of enabling de-duplication, and if de-duplication is enabled, the data sets which will be subject to the de-duplication. The protocol includes a measurement procedure and an execution procedure. The measurement procedure characterizes data duplication in part of the data on the storage system, and the execution procedure use the characterization to adjust selection of which data sets are subject to de-duplication.
摘要翻译：采用协议来估计存储系统中数据的重复。这种估算被用作启用重复数据删除的一个因素，如果重复数据删除功能被启用，将会被重复数据删除的数据集。该协议包括测量过程和执行过程。测量过程表征存储系统上部分数据的数据复制，执行过程使用表征来调整选择哪些数据集进行重复数据删除。

7. 发明授权

US09158807B2 Fast distributed database frequency summarization 有权
标题翻译：快速分布式数据库频率汇总
公开(公告)号：US09158807B2
公开(公告)日：2015-10-13
申请号：US13790098
申请日：2013-03-08
申请人： International Business Machines Corporation
发明人： David P. Woodruff
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30386 , G06F17/30539
摘要： A mechanism is provided for computing the frequency packets in network devices. Respective packets are associated with entities in a vector, where each of the entities is mapped to corresponding ones of the respective packets, and the entities correspond to computers. Upon a network device receiving the respective packets, a count is individually increased for the respective packets in the vector respectively mapped to the entities, and computing a matrix vector product of a matrix A and the vector. The matrix A is a product of at least a first matrix and a second matrix. The first matrix includes rows and columns where each of the rows has a single random location with a one value and remaining locations with zero values. The matrix vector product is transmitted to a centralized computer for aggregating with other matrix vector products.
摘要翻译：提供一种用于计算网络设备中的频率分组的机制。相应的分组与向量中的实体相关联，其中每个实体被映射到相应分组中的相应分组，并且实体对应于计算机。在网络设备接收到相应的分组时，分别对于分别映射到实体的向量中的各个分组增加计数，并且计算矩阵A和向量的矩阵向量积。矩阵A是至少第一矩阵和第二矩阵的乘积。第一个矩阵包括行和列，其中每个行具有单个随机位置，其中一个值和剩余的具有零值的位置。矩阵矢量积被发送到集中式计算机，用于与其他矩阵向量积聚。

8. 发明申请

US20150286612A1 Robust Regression Analysis Techniques Using Exponential Random Variables 有权
标题翻译：使用指数随机变量的鲁棒回归分析技术
公开(公告)号：US20150286612A1
公开(公告)日：2015-10-08
申请号：US14246174
申请日：2014-04-07
申请人： International Business Machines Corporation
发明人： David P. Woodruff , Qin Zhang
IPC分类号： G06F17/18
CPC分类号： G06F17/18
摘要： Embodiments relate to methodologies and program product is provided for conducting regression analysis. In one embodiment the method includes obtaining data related to a statistical process including a plurality of points in a plurality of dimensions and organizing the plurality of points and the plurality of dimensions in a matrix. The method also includes calculating a vector of a particular measurement such that the measurement equal the number of the plurality of points and calculating a least absolute deviation by determining the number of non-zero entries provided in the matrix.
摘要翻译：实施例涉及方法和程序产品用于进行回归分析。在一个实施例中，该方法包括获得与统计过程相关的数据，所述统计过程包括多个维度中的多个点，并且以矩阵形式组织多个点和多个维度。该方法还包括计算特定测量的向量，使得测量等于多个点的数量，并通过确定矩阵中提供的非零条目的数量来计算最小绝对偏差。

9. 发明申请

US20140351020A1 ESTIMATING THE TOTAL SALES OVER STREAMING BIDS 审中-公开
标题翻译：估计流浪儿童的总销售额
公开(公告)号：US20140351020A1
公开(公告)日：2014-11-27
申请号：US13901165
申请日：2013-05-23
申请人： International Business Machines Corporation
发明人： Benny Kimelfeld , David P. Woodruff
IPC分类号： G06Q30/02
CPC分类号： G06Q30/0201 , G06Q30/0206
摘要： A mechanism is provided for computing an estimation of maximum total sales over streaming items. Each item having an associated value is designated as an item value pair. Value ranges are established to place the item value pairs. The value ranges are distinct. Each of the item value pairs is added into the value ranges according to each of the associated values for the item value pairs. Repeated item value pairs are removed that are in the same value ranges. A number of the item value pairs is reduced in each of the value ranges respectively based on an error factor, by randomly selecting the item value pairs to remove from each of the value ranges. An estimate of a total maximum value of the bids for the item value pairs in all of the value ranges is computed based on a scale factor.
摘要翻译：提供了一种用于计算流媒体项目的最大总销售额的估计的机制。具有关联值的每个项目被指定为项目值对。建立价值范围以放置料品价值对。值范围是不同的。每个项目值对根据项目值对的每个关联值被添加到值范围中。重复的项目值对被删除，它们在相同的值范围内。通过随机选择要从每个值范围中删除的项目值对，分别基于误差因子在每个值范围中减少多个项目值对。基于比例因子计算所有值范围中的项目值对的出价的总最大值的估计。

10. 发明申请

US20140351007A1 ESTIMATING THE TOTAL SALES OVER STREAMING BIDS 审中-公开
公开(公告)号：US20140351007A1
公开(公告)日：2014-11-27
申请号：US14022672
申请日：2013-09-10
申请人： International Business Machines Corporation
发明人： Benny Kimelfeld , David P. Woodruff
IPC分类号： G06Q30/02
CPC分类号： G06Q30/0201 , G06Q30/0206
摘要： A mechanism is provided for computing an estimation of maximum total sales over streaming items. Each item having an associated value is designated as an item value pair. Value ranges are established to place the item value pairs. The value ranges are distinct. Each of the item value pairs is added into the value ranges according to each of the associated values for the item value pairs. Repeated item value pairs are removed that are in the same value ranges. A number of the item value pairs is reduced in each of the value ranges respectively based on an error factor, by randomly selecting the item value pairs to remove from each of the value ranges. An estimate of a total maximum value of the bids for the item value pairs in all of the value ranges is computed based on a scale factor.

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