Implementations of the present disclosure include methods, systems, and computer-readable storage mediums for receiving first and second data sets, both the first and second data sets including structured data in a plurality of columns, for each of the first data set and the second data set, inputting each column into an encoder specific to a column type of a respective column, the encoder providing encoded data for the first data set, and the second data set, respectively, providing a first multi-dimensional vector based on encoded data of the first data set, providing a second multi-dimensional vector based on encoded data of the second data set, and outputting the first multi-dimensional vector and the second multi-dimensional vector to a loss-function, the loss-function processing the first multi-dimensional vector and the second multi-dimensional vector to provide an output, the output representing matched data points between the first and second data sets.

The present invention aims to encode and decode a sequence of integer values by substantially assigning the number of bits of a decimal fraction value per sample. An integer converter 11 selects M selected integer values from L input integer values for a set of the L input integer values and obtains J-value selection information that specifies which of the L input integer values the M selected integer values are. Furthermore, the integer converter 11 obtains one converted integer value by reversibly converting the M selected integer value and an integer value corresponding to the J-value selection information. An integer encoder 12 encodes the converted integer value to obtain a code.

A database management system is described that can encode data to generate a plurality of data vectors. The database management system can perform the encoding by using a dictionary. The database management system can adaptively reorder the plurality of data vectors to prepare for compression of the plurality of data vectors. During a forward pass of the adaptive reordering, most frequent values of a data vector of the plurality of data vectors can be moved-up in the data vector. During a backward pass of the adaptive reordering, content within a rest range of a plurality of rest ranges can be rearranged within the plurality of data vectors according to frequencies of the content. The reordering according to frequency can further sort the rest range by value. Related apparatuses, systems, methods, techniques, computer programmable products, computer readable media, and articles are also described.

An encoder and a method therein for Pyramid Vector Quantizer, PVQ, shape search, the PVQ taking a target vector x as input and deriving a vector y by iteratively adding unit pulses in an inner dimension search loop. The method comprises, before entering a next inner dimension search loop for unit pulse addition, determining, based on the maximum pulse amplitude, maxamp.sub.y, of a current vector y, whether more than a current bit word length is needed to represent enloop.sub.y, in a lossless manner in the upcoming inner dimension loop. The variable enloop.sub.y is related to an accumulated energy of the vector y. The performing of this method enables the encoder to keep the complexity of the search at a reasonable level.

A network node signals to a wireless communication device which precoders in a codebook are restricted from being used. The network node in this regard generates codebook subset restriction signaling that, for each of one or more groups of precoders, jointly restricts the precoders in the group by restricting a certain component (e.g., a certain beam precoder) that the precoders in the group have in common. This signaling may be for instance rank-agnostic signaling that jointly restricts the precoders in a group without regard to the precoders transmission rank. Regardless, the network node sends the generated signaling to the wireless communication device.

Techniques and systems are provided for implementing a convolutional neural network. One or more convolution accelerators are provided that each include a feature line buffer memory, a kernel buffer memory, and a plurality of multiply-accumulate (MAC) circuits arranged to multiply and accumulate data. In a first operational mode the convolutional accelerator stores feature data in the feature line buffer memory and stores kernel data in the kernel data buffer memory. In a second mode of operation, the convolutional accelerator stores kernel decompression tables in the feature line buffer memory.

A computer-implemented method of an arithmetic processing, the method including: identifying maximum absolute values of individual dimensions by projecting a maximum absolute value in a direction of each of the individual dimensions of a tensor represented by a multidimensional array, the tensor in which a value is set for each of elements of the array; identifying a minimum value that indicates a minimum maximum absolute value among the maximum absolute values of the individual dimensions; and setting a quantization range for the tensor on a basis of the minimum value.

In an embodiment, a processor supports one or more compression assist instructions which may be employed in compression software to improve the performance of the processor when performing compression/decompression. That is, the compression/decompression task may be performed more rapidly and consume less power when the compression assist instructions are employed then when they are not. In some cases, the cost of a more effective, more complex compression algorithm may be reduced to the cost of a less effective, less complex compression algorithm.

A computer-readable storage medium storing a program for causing a computer to perform processing including: dividing a sequence indicating a rational formula of a compound, into a character string of a minimum unit of the sequence and a branch symbol indicating a branched portion of the compound; generating a first coded sequence by using a group dictionary indicating a relationship between the sequence and the compression code, the generating including assigning a compression code to the character string of the minimum unit, and assigning the compression code according to a type of the branched portion to the branch symbol; and generating a second coded sequence by using a primary structure dictionary indicating a relationship between a group primary structure of the sequence and the compression code, the generating of the second coded sequence including encoding the compression code in the first coded sequence in units of the group primary structure.

A system comprises an encoder configured to compress attribute information and/or spatial for a point cloud and/or a decoder configured to decompress compressed attribute and/or spatial information for the point cloud. To compress the attribute and/or spatial information, the encoder is configured to convert a point cloud into an image based representation. Also, the decoder is configured to generate a decompressed point cloud based on an image based representation of a point cloud. A processing/filtering element utilizes occupancy map information and/or auxiliary patch information to determine relationships between patches in image frames and adjusts encoding/decoding and/or filtering or pre/post-processing parameters based on the determined relationships.