H03M7/3082

Systems and methods for communication efficient distributed mean estimation

The present disclosure provides systems and methods for communication efficient distributed mean estimation. In particular, aspects of the present disclosure can be implemented by a system in which a number of vectors reside on a number of different clients, and a centralized server device seeks to estimate the mean of such vectors. According to one aspect of the present disclosure, a client computing device can rotate a vector by a random rotation matrix and then subsequently perform probabilistic quantization on the rotated vector. According to another aspect of the present disclosure, subsequent to quantization but prior to transmission, the client computing can encode the quantized vector according to a variable length coding scheme (e.g., by computing variable length codes).

Compressing and Decompressing Image Data Using Compacted Region Transforms
20210377572 · 2021-12-02 ·

A method of compressing image data comprising a set of image values each representing a position in image-value space so as to define an occupied region thereof. The method comprises selectively applying a series of compression transforms to subsets of the image data items to generate a transformed set of image data items occupying a compacted region of value space. The method further comprises identifying a set of one or more reference data items that quantizes the compacted region in value space. For each image data item in the set of image data items, a sequence of decompression transforms from a fixed set of decompression transforms is identified that generates an approximation of that image data item when applied to a selected one of the one or more reference data items. Each image data item in the set of image data items is encoded as a representation of the identified sequence of decompression transforms for that image data item. The encoded image data items, set of reference data items and the fixed set of decompression transforms are stored as compressed image data.

Methods and apparatus for compression data streams

Methods and apparatus for compressing data streams. In an embodiment, a method includes calculating a probability distribution function (PDF) for scaler data, matching the PDF to PDF templates to determine a closest matching PDF template, and selecting an encoder corresponding to the closest matching PDF template wherein a corresponding encoder identifier is determined. The method also includes encoding the scaler data with the encoder to generate an encoded stream, and transmitting the encoded stream and the encoder identifier.

Method and apparatus for biological sequence processing fastq files comprising lossless compression and decompression
11360940 · 2022-06-14 · ·

This application provides a biological sequence data processing method including selecting a target base from bases in a biological sequence fastq file according to characteristic information of each base. A base patch file is generated by using characteristic information of the target base. Lossless compression is performed on the biological sequence fastq file to obtain a compressed fastq file, and lossless compression is performed on the base patch file to obtain a compressed patch file. The compressed patch file and the compressed fastq file are decompressed. In response to determining that characteristic information of the target base in the decompressed compressed patch file is inconsistent with characteristic information of the target base in the decompressed compressed fastq file, the characteristic information of the target base in the decompressed compressed fastq file is modified to the characteristic information of the target base in the decompressed compressed patch file.

System and methods for data compression and nonuniform quantizers

An optical network includes a transmitting portion configured to (i) encode an input digitized sequence of data samples into a quantized sequence of data samples having a first number of digits per sample, (ii) map the quantized sequence of data samples into a compressed sequence of data samples having a second number of digits per sample, the second number being lower than the first number, and (iii) modulate the compressed sequence of data samples and transmit the modulated sequence over a digital optical link. The optical network further includes a receiving portion configured to (i) receive and demodulate the modulated sequence from the digital optical link, (ii) map the demodulated sequence from the second number of digits per sample into a decompressed sequence having the first number of digits per sample, and (iii) decode the decompressed sequence.

Entropy agnostic data encoding and decoding

Entropy agnostic data encoding includes: receiving, by an encoder, input data including a bit string; generating a plurality of candidate codewords, including encoding the input data bit string with a plurality of binary vectors, wherein the plurality of binary vectors includes a set of deterministic biased binary vectors and a set of random binary vectors; selecting, in dependence upon a predefined criteria, one of the plurality of candidate codewords; and transmitting the selected candidate codeword to a decoder.

Vector quantizer

Vector Quantizer and method therein for vector quantization, e.g. in a transform audio codec. The method comprises comparing an input target vector with four centroids C.sub.0, C.sub.1, C.sub.0,flip and C.sub.1,flip, wherein centroid C.sub.0,flip is a flipped version of centroid C.sub.0 and centroid C.sub.1,flip is a flipped version of centroid C.sub.1, each centroid representing a respective class of codevectors. A starting point for a search related to the input target vector in the codebook is determined, based on the comparison. A search is performed in the codebook, starting at the determined starting point, and a codevector is identified to represent the input target vector. A number of input target vectors per block or time segment is variable. A search space is dynamically adjusted to the number of input target vectors. The codevectors are sorted according to a distortion measure reflecting the distance between each codevector and the centroids C.sub.0 and C.sub.1.

SYSTEMS AND METHODS FOR ENCODING/DECODING A DEEP NEURAL NETWORK

The disclosure relates to a method comprising quantizing parameters of an input tensor, said quantizing using a codebook whose size is obtained according to a distortion value determined between the at least one tensor and a quantized version of said at least one tensor. The disclosure also relates to a method for quantizing parameters of the input tensor using a pdf-based initialization bounded according to at least one first pdf factor, said first pdf factor being selected among several candidate bounding pdf factors according to resulting entropy. The disclosure also relates to corresponding signal; bitstream, storage media and encoder and/or decoder devices.

Efficient Memory Utilization for Cartesian Products of Rules
20230269310 · 2023-08-24 ·

A network device includes one or more ports, and action-select circuitry. The ports are to exchange packets over a network. The act-ion-select circuitry is to determine, for a given packet, a first search key based on a first header field of the given packet, and a second search key based on a second header field of the given packet, to compare the first search key to a first group of compare values, to output a multi-element vector responsively to a match between the first search key and a first compare value, to generate a composite search key by concatenating the second search key and the multi-element vector, to compare the composite search key to a second group of compare values, and, responsively to a match between the composite search key and a second compare value, to output an action indicator for applying to the given packet.

Compressing and Decompressing Image Data Using Compacted Region Transforms
20230262269 · 2023-08-17 ·

A method of compressing image data comprising a set of image values each representing a position in image-value space so as to define an occupied region thereof. The method comprises selectively applying a series of compression transforms to subsets of the image data items to generate a transformed set of image data items occupying a compacted region of value space. The method further comprises identifying a set of one or more reference data items that quantizes the compacted region in value space. For each image data item in the set of image data items, a sequence of decompression transforms from a fixed set of decompression transforms is identified that generates an approximation of that image data item when applied to a selected one of the one or more reference data items. Each image data item in the set of image data items is encoded as a representation of the identified sequence of decompression transforms for that image data item. The encoded image data items, set of reference data items and the fixed set of decompression transforms are stored as compressed image data.