Demo Data from SIGIR 2026 / reviewers in the wild / expert
Xiaoyan Jing
dblp:279/3954
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2023
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2 · 1 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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
2 papers |
Coding theory · 93% Information theory · 7% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › sequences › pseudorandom sequences
autocorrelation |
0.7 | 1 | 2023 | Arithmetic Autocorrelation Distribution of Binary m-Sequences · IEEE Trans. Inf. Theory 2023 |
Coding theory
error-correcting codes |
0.7 | 1 | 2023 | Optimal Combinatorial Neural Codes With Matched Metric δr: Characterization and Constructions · IEEE Trans. Inf. Theory 2023 |
Coding theory › sequences › pseudorandom sequences
m-sequences |
0.7 | 1 | 2023 | Arithmetic Autocorrelation Distribution of Binary m-Sequences · IEEE Trans. Inf. Theory 2023 |
Coding theory › sequences
pseudorandom sequences |
0.7 | 1 | 2023 | Arithmetic Autocorrelation Distribution of Binary m-Sequences · IEEE Trans. Inf. Theory 2023 |
Computational science and engineering
theoretical neuroscience |
0.2 | 1 | 2023 | Optimal Combinatorial Neural Codes With Matched Metric δr: Characterization and Constructions · IEEE Trans. Inf. Theory 2023 |
Methods — techniques the papers use, named apart from their topics
hamming distance · 1.3bent functions · 1.3asymmetric discrepancy · 1.3linear shift registers · 0.72-adic analysis · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Arithmetic Autocorrelation Distribution of Binary m-SequencesabstractBinary${m}$-sequences are those with the largest period$n=2^{m}-1$among the binary sequences produced by linear shift registers with length$m$. They have a wide range of applications in communication since they have several desirable pseudorandom properties, such as balance, uniform pattern distribution, and ideal (classical) autocorrelation. In 1967, Mandelbaum introduced a 2-adic version of classical autocorrelation of binary sequences, called arithmetic autocorrelation, in his research on arithmetic codes. Later, Goresky and Klapper generalized this notion to the nonbinary case and got several properties of arithmetic autocorrelation related to linear shift registers with carry. Recently, Z. Chen et al. showed an upper bound on the arithmetic autocorrelation of binary${m}$-sequences and raised a conjecture on the absolute value distribution of the arithmetic autocorrelation of binary${m}$-sequences. In this paper, we present a general formula for computing arithmetic autocorrelation, from which we completely determine the arithmetic autocorrelation distribution of arbitrary binary${m}$-sequences. In particular, the conjecture raised by Z. Chen et al. is verified. Xiaoyan Jing, Aixian Zhang, Keqin Feng |
IEEE Trans. Inf. Theory | 1 |
| 2023 | Optimal Combinatorial Neural Codes With Matched Metric δr: Characterization and ConstructionsabstractBased on theoretical neuroscience, G. Cotardo and A. Ravagnani (2022) introduced a class of asymmetric binary codes called combinatorial neural codes (CN codes for short), with a “matched metric”$\delta _{r}$called asymmetric discrepancy, instead of the Hamming distance$d_{H}$for usual error-correcting codes. They also presented the Hamming, Singleton and Plotkin bounds for CN codes with respect to$\delta _{r}$and asked how to construct CN codes${\mathcal C}$with large size$| {\mathcal C}|$and minimum$\delta _{r}({\mathcal C})$. In this paper, we first show that a binary code${\mathcal C}$reaches one of the above bounds for$\delta _{r}({\mathcal C})$if and only if${\mathcal C}$reaches the corresponding bounds for$d_{H}$and$r$is sufficiently close to 1. This means that all optimal CN codes come from the usual optimal codes. Then, we present several constructions of CN codes with good and flexible parameters$(n,K, \delta _{r}({\mathcal C}))$by using bent functions. Aixian Zhang, Xiaoyan Jing, Keqin Feng |
IEEE Trans. Inf. Theory | 2 |
| 2022 | The 4-Adic Complexity of Quaternary Sequences of Even Period With Ideal AutocorrelationabstractThe purpose of this paper is to determine the 4-adic complexity of the balanced quaternary sequences of period 2(2n−1) with ideal autocorrelation defined by Jang et al. (ISIT, pp. 278-281, 2009). Results show that the 4-adic complexity of such sequences is large enough to resist the attack of the rational approximation algorithm for feedback with carry shift registers. Shiyuan Qiang, Xiaoyan Jing, Keqin Feng, Dongdai Lin |
ISIT | 3 |