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Scott Kayser

dblp:118/2323 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 2Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Coding theory · 75% Information theory · 25%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 50% Storage systems · 50%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes › code construction
coset coding
0.112012
Codes for Write-Once Memories · IEEE Trans. Inf. Theory 2012
Coding theory › error-correcting codes › code construction
linear code construction
0.112012
Codes for Write-Once Memories · IEEE Trans. Inf. Theory 2012
Information theory › network information theory › multiuser capacity
sum-rate
0.112012
Codes for Write-Once Memories · IEEE Trans. Inf. Theory 2012
Coding theory › error-correcting codes › storage coding › write-once memory
write-once memory codes
0.112012
Codes for Write-Once Memories · IEEE Trans. Inf. Theory 2012
Memory systems
non-volatile memory
0.012012
Codes for Write-Once Memories · IEEE Trans. Inf. Theory 2012
Storage systems › non-volatile memory storage
write-once memory
0.012012
Codes for Write-Once Memories · IEEE Trans. Inf. Theory 2012

Methods — techniques the papers use, named apart from their topics

wozencraft ensemble · 0.3recursive code construction · 0.3coset coding · 0.3
YearPublicationVenuePosition
2014 Constructions for constant-weight ICI-free codes
abstract
In this paper, we consider the joint coding constraint of forbidding the 101 subsequence and requiring all codewords to have the same Hamming weight. These two constraints are particularly applicable to SLC flash memory - the first constraint mitigates the problem of inter-cell interference, while the second constraint helps to alleviate the problems that arise from voltage drift of programmed cells. We give a construction for codes that satisfy both constraints, then analyze properties of best-case codes that can come from this construction.
Scott Kayser, Paul H. Siegel
ISIT1
2012 Codes for Write-Once Memories
abstract
A write-once memory (WOM) is a storage device that consists of cells that can take on$q$values, with the added constraint that rewrites can only increase a cell's value. A length-$n$,$t$-write WOM-code is a coding scheme that allows$t$messages to be stored in$n$cells. If on the$i$th write we write one of$M_{i}$messages, then the rate of this write is the ratio of the number of written bits to the total number of cells, i.e.,$\log_{2}M_{i}/n$. The sum-rate of the WOM-code is the sum of all individual rates on all writes. A WOM-code is called a fixed-rate WOM-code if the rates on all writes are the same, and otherwise, it is called a variable-rate WOM-code. We address two different problems when analyzing the sum-rate of WOM-codes. In the first one, called the fixed-rate WOM-code problem, the sum-rate is analyzed over all fixed-rate WOM-codes, and in the second problem, called the unrestricted-rate WOM-code problem, the sum-rate is analyzed over all fixed-rate and variable-rate WOM-codes. In this paper, we first present a family of two-write WOM-codes. The construction is inspired by the coset coding scheme, which was used to construct multiple-write WOM-codes by Cohenand recently by Wu, in order to construct from each linear code a two-write WOM-code. This construction improves the best known sum-rates for the fixed- and unrestricted-rate WOM-code problems. We also show how to take advantage of two-write WOM-codes in order to construct codes for the Blackwell channel. The two-write construction is generalized for two-write WOM-codes with$q$levels per cell, which is used with ternary cells to construct three- and four-write binary WOM-codes. This construction is used recursively in order to generate a family of$t$-write WOM-codes for all$t$. A further generalization of these$t$-write WOM-codes yields additional families of efficient WOM-codes. Finally, we show a recursive method that uses the previously constructed WOM-codes in order to construct fixed-rate WOM-codes. We conclude and show that the WOM-codes constructed here outperform all previously known WOM-codes for$2\leqslant t\leqslant 10$for both the fixed- and unrestricted-rate WOM-code problems.
Eitan Yaakobi, Scott Kayser, Paul H. Siegel, Alexander Vardy, Jack K. Wolf
IEEE Trans. Inf. Theory2
2010 Efficient two-write WOM-codes
abstract
A Write Once Memory (WOM) is a storage medium with binary memory elements, called cells, that can change from the zero state to the one state only once. Examples of WOMs are punch cards, optical disks, and more recently flash memories. A t-write WOM-code is a coding scheme for storing t messages in n cells in such a way that each cell can change its value only from the zero state to the one state. The WOM-rate of a t-write WOM-code is the ratio of the total amount of information written to the WOM in t writes to the number of cells. In this paper we present a family of 2-write WOM-codes. It is shown how to construct from each linear code C a 2-write WOM-code. Then, we find 2-write WOM-codes that improve the best known WOM-rate with two writes. This scheme is proved to be capacity achieving when the parity check matrix of the linear code C is chosen uniformly at random. Finally, we show how to take advantage of 2-write WOM-codes in order to construct codes for the Blackwell channel.
Eitan Yaakobi, Scott Kayser, Paul H. Siegel, Alexander Vardy, Jack K. Wolf
ITW2