22 citations · 69 across the 12 of their papers we have counts for
14 papers
A New Class of Geometric Analog Error Correction Codes for Crossbar Based In-Memory Computing
Ziyuan Zhu, Changcheng Yuan, Ron M. Roth +2
Analog error correction codes have been proposed for analog in-memory computing on resistive crossbars, which can accelerate vector-matrix multiplication for machine learning. Unli…
On the Height Profile of Analog Error-Correcting Codes
Ron M. Roth, Ziyuan Zhu, Changcheng Yuan +2
In recent work, it has been shown that maintaining reliability in analog vector--matrix multipliers can be modeled as the following coding problem. Vectors in are en…
CodNN -- Robust Neural Networks From Coded Classification
Netanel Raviv, Siddharth Jain, Pulakesh Upadhyaya +2
Deep Neural Networks (DNNs) are a revolutionary force in the ongoing information revolution, and yet their intrinsic properties remain a mystery. In particular, it is widely known…
Functional Error Correction for Robust Neural Networks
Kunping Huang, Paul Siegel, Anxiao +1
When neural networks (NeuralNets) are implemented in hardware, their weights need to be stored in memory devices. As noise accumulates in the stored weights, the NeuralNet's perfor…
Machine Learning for Error Correction with Natural Redundancy
Pulakesh Upadhyaya, Anxiao Jiang
The persistent storage of big data requires advanced error correction schemes. The classical approach is to use error correcting codes (ECCs). This work studies an alternative appr…
Representation-Oblivious Error Correction by Natural Redundancy
Pulakesh Upadhyaya, Anxiao, Jiang
Storage systems have a strong need for substantially improving their error correction capabilities, especially for long-term storage where the accumulating errors can exceed the de…
U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting
Ramakrishna Prabhu, Xiaojing Yu, Zhangyang Wang +3
This paper studies the challenging problem of fingerprint image denoising and inpainting. To tackle the challenge of suppressing complicated artifacts (blur, brightness, contrast,…
Joint Source-Channel Decoding of Polar Codes for Language-Based Source
Ying Wang, Minghai Qin, Krishna R. Narayanan +2
We exploit the redundancy of the language-based source to help polar decoding. By judging the validity of decoded words in the decoded sequence with the help of a dictionary, the p…
Asymmetric Error Correction and Flash-Memory Rewriting using Polar Codes
Eyal En Gad, Yue Li, Joerg Kliewer +3
We propose efficient coding schemes for two communication settings: 1. asymmetric channels, and 2. channels with an informed encoder. These settings are important in non-volatile m…
Systematic Error-Correcting Codes for Rank Modulation
Hongchao Zhou, Moshe Schwartz, Anxiao Jiang +1
The rank-modulation scheme has been recently proposed for efficiently storing data in nonvolatile memories. Error-correcting codes are essential for rank modulation, however, exist…
Balanced Modulation for Nonvolatile Memories
Hongchao Zhou, Anxiao, Jiang +1
This paper presents a practical writing/reading scheme in nonvolatile memories, called balanced modulation, for minimizing the asymmetric component of errors. The main idea is to e…
Nonuniform Codes for Correcting Asymmetric Errors in Data Storage
Hongchao Zhou, Anxiao, Jiang +1
The construction of asymmetric error correcting codes is a topic that was studied extensively, however, the existing approach for code construction assumes that every codeword shou…
Trajectory Codes for Flash Memory
Anxiao, Jiang, Michael Langberg +2
Flash memory is well-known for its inherent asymmetry: the flash-cell charge levels are easy to increase but are hard to decrease. In a general rewriting model, the stored data cha…
Position Modulation Code for Rewriting Write-Once Memories
Yunnan Wu, Anxiao Jiang
A write-once memory (wom) is a storage medium formed by a number of ``write-once'' bit positions (wits), where each wit initially is in a `0' state and can be changed to a `1' stat…