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In this paper, we present a new approach to learning cascaded classifiers for use in computing environments that involve networks of heterogeneous and resource-constrained, low-power embedded compute and sensing nodes. We present a…

Machine Learning · Statistics 2017-06-27 Hamid Dadkhahi , Benjamin M. Marlin

We propose a low complexity complex valued Sphere Decoding (CV-SD) algorithm, referred to as Circular Sphere Decoding (CSD) which is applicable to multiple-input multiple-output (MIMO) systems with arbitrary two dimensional (2D)…

Information Theory · Computer Science 2016-11-17 Hwanchol Jang , Saeid Nooshabadi , Kiseon Kim , Heung-No Lee

This paper shows how to build a sparse tensor algebra compiler that is agnostic to tensor formats (data layouts). We develop an interface that describes formats in terms of their capabilities and properties, and show how to build a modular…

Mathematical Software · Computer Science 2018-11-13 Stephen Chou , Fredrik Kjolstad , Saman Amarasinghe

An anytime decoding algorithm for tree codes using Monte-Carlo tree search is proposed. The meaning of anytime decoding here is twofold: 1) the decoding algorithm is an anytime algorithm, whose decoding performance improves as more…

Information Theory · Computer Science 2021-05-04 Aolin Xu

We propose a full-rate iterated space-time code construction, to design 2n-dimensional codes from n-dimensional cyclic algebra based codes. We give a condition to determine whether the resulting codes satisfy the full-diversity property,…

Information Theory · Computer Science 2013-03-12 Nadya Markin , Frederique Oggier

The capacity of symmetric, neighboring and consecutive side-information single unicast index coding problems (SNC-SUICP) with number of messages equal to the number of receivers was given by Maleki, Cadambe and Jafar. For these index coding…

Information Theory · Computer Science 2017-05-17 Mahesh Babu Vaddi , B. Sundar Rajan

This paper investigates the Triangle Single Parity Check (T/SPC) code, a novel class of high-rate low-complexity LDPC codes. T/SPC is a regular, soft decodable, linear-time encodable/decodable code. Compared to previous high-rate and…

Information Theory · Computer Science 2011-04-11 Damian A. Morero , Graciela Corral-Briones , Carmen Rodriguez , Mario R. Hueda

In this paper, we introduce a novel explicit family of subcodes of Reed-Solomon (RS) codes that efficiently achieve list decoding capacity with a constant output list size. Our approach builds upon the idea of large linear subcodes of RS…

Information Theory · Computer Science 2024-01-29 Amit Berman , Yaron Shany , Itzhak Tamo

Motivated by signal processing, we present a new class of channel codes, called signal codes, for continuous-alphabet channels. Signal codes are lattice codes whose encoding is done by convolving an integer information sequence with a fixed…

Information Theory · Computer Science 2016-11-18 Ofir Shalvi , Naftali Sommer , Meir Feder

Unsourced random access (URA) has emerged as a pragmatic framework for next-generation distributed sensor networks. Within URA, concatenated coding structures are often employed to ensure that the central base station can accurately recover…

Information Theory · Computer Science 2021-12-02 Vamsi K. Amalladinne , Jamison R. Ebert , Jean-Francois Chamberland , Krishna R. Narayanan

We propose a computationally efficient multilevel coding scheme to achieve the capacity of an ISI channel using layers of binary inputs. The transmitter employs multilevel coding with linear mapping. The receiver uses multistage decoding…

Information Theory · Computer Science 2007-07-13 Mei Chen , Teng Li , Oliver M. Collins

In this paper, we study a class of spatially coupled turbo codes, namely partially information- and partially parity-coupled turbo codes. This class of codes enjoy several advantages such as flexible code rate adjustment by varying the…

Information Theory · Computer Science 2020-12-25 Min Qiu , Xiaowei Wu , Alexandre Graell i Amat , Jinhong Yuan

Complex Orthogonal Design (COD) codes are known to have the lowest detection complexity among Space-Time Block Codes (STBCs). However, the rate of square COD codes decreases exponentially with the number of transmit antennas. The…

Information Theory · Computer Science 2016-11-17 Amr Ismail , Jocelyn Fiorina , Hikmet Sari

Speculative decoding is a technique to leverage hardware concurrency in order to enable multiple steps of token generation in a single forward pass, thus improving the efficiency of large-scale autoregressive (AR) Transformer models.…

Machine Learning · Computer Science 2025-10-29 Yangchao Wu , Zongyue Qin , Alex Wong , Stefano Soatto

Polar codes under cyclic redundancy check aided successive cancellation list (CA-SCL) decoding can outperform the turbo codes and the LDPC codes when code lengths are configured to be several kilobits. In order to reduce the decoding…

Information Theory · Computer Science 2015-08-11 Kai Chen , Bin Li , Hui Shen , Jie Jin , David Tse

An efficient decoding algorithm named `divided decoder' is proposed in this paper. Divided decoding can be combined with any decoder using QR-decomposition and offers different pairs of performance and complexity. Divided decoding provides…

Information Theory · Computer Science 2009-01-23 In Sook Park

Perfect Space-Time Block Codes (PSTBCs) achieve full diversity, full rate, nonvanishing constant minimum determinant, uniform average transmitted energy per antenna, and good shaping. However, the high decoding complexity is a critical…

Information Theory · Computer Science 2012-08-17 Boyu Li , Ender Ayanoglu

The simplified parse tree (SPT) presented in Aroma, a state-of-the-art code recommendation system, is a tree-structured representation used to infer code semantics by capturing program \emph{structure} rather than program \emph{syntax}.…

Rate and diversity impose a fundamental trade-off in communications. This trade-off was investigated for flat-fading channels in [15] as well as for Inter-symbol Interference (ISI) channels in [1]. A different point of view was explored in…

Information Theory · Computer Science 2009-12-24 S. Dusad , S. N. Diggavi

Self-supervised representation learning of Multivariate Time Series (MTS) is a challenging task and attracts increasing research interests in recent years. Many previous works focus on the pretext task of self-supervised learning and…

Machine Learning · Computer Science 2022-03-10 Yijiang Chen , Xiangdong Zhou , Zhen Xing , Zhidan Liu , Minyang Xu