VLDB 2026 Research / reviewers in the wild / expert
Zeev Geyzel
dblp:125/0264
· DBLP profile ↗
3ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Theory of computation · 1 · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Error Resilient Space PartitioningabstractAbstract A major research area in discrete geometry is to consider the best way to partition the d -dimensional Euclidean space $$\mathbb {R}^d$$ R d under various quality criteria. In this paper we introduce a new type of space partitioning that is motivated by the problem of rounding noisy measurements from the continuous space $$\mathbb {R}^d$$ R d to a discrete subset of representative values. Specifically, we study partitions of $$\mathbb {R}^d$$ R d into bounded-size tiles colored by one of k colors, such that tiles of the same color have a distance of at least t from each other. Such tilings allow for error-resilient rounding, as two points of the same color and distance less than t from each other are guaranteed to belong to the same tile, and thus, to be rounded to the same point. The main problem we study in this paper is characterizing the achievable tradeoffs between the number of colors k and the distance t , for various dimensions d . On the qualitative side, we show that in $$\mathbb {R}^d$$ R d , using $$k=d+1$$ k = d + 1 colors is both sufficient and necessary to achieve $$t>0$$ t > 0 . On the quantitative side, we achieve numerous upper and lower bounds on t as a function of k . In particular, for $$d=3,4,8,24$$ d = 3 , 4 , 8 , 24 , we obtain sharp asymptotic bounds on t , as $$k \rightarrow \infty $$ k → ∞ . We obtain our results with a variety of techniques including isoperimetric inequalities, the Brunn-Minkowski theorem, sphere packing bounds, Bapat’s connector-free lemma, and Čech cohomology. Orr Dunkelman, Zeev Geyzel, Chaya Keller, Nathan Keller, Eyal Ronen, Adi Shamir, Ran J. Tessler |
Discret. Comput. Geom. | 2 |
| 2021 | Error Resilient Space Partitioning (Invited Talk)abstractA major research area in discrete geometry is to consider the best way to partition the $d$-dimensional Euclidean space $\mathbb{R}^d$ under various quality criteria. In this paper we introduce a new type of space partitioning that is motivated by the problem of rounding noisy measurements from the continuous space $\mathbb{R}^d$ to a discrete subset of representative values. Specifically, we study partitions of $\mathbb{R}^d$ into bounded-size tiles colored by one of $k$ colors, such that tiles of the same color have a distance of at least $t$ from each other. Such tilings allow for \emph{error-resilient} rounding, as two points of the same color and distance less than $t$ from each other are guaranteed to belong to the same tile, and thus, to be rounded to the same point. The main problem we study in this paper is characterizing the achievable tradeoffs between the number of colors $k$ and the distance $t$, for various dimensions $d$. On the qualitative side, we show that in $\mathbb{R}^d$, using $k=d+1$ colors is both sufficient and necessary to achieve $t>0$. On the quantitative side, we achieve numerous upper and lower bounds on $t$ as a function of $k$. In particular, for $d=3,4,8,24$, we obtain sharp asymptotic bounds on $t$, as $k \to \infty$. We obtain our results with a variety of techniques including isoperimetric inequalities, the Brunn-Minkowski theorem, sphere packing bounds, Bapat's connector-free lemma, and Čech cohomology. Orr Dunkelman, Zeev Geyzel, Chaya Keller, Nathan Keller, Eyal Ronen, Adi Shamir, Ran J. Tessler |
ICALP | 2 |
| 1995 | Fitting a Second Degree Curve in the Presence of ErrorabstractThis correspondence presents a statistically sound, simple and, fast method to estimate the parameters of a second degree curve from a set of noisy points that originated from the curve.> Michael Werman, Zeev Geyzel |
IEEE Trans. Pattern Anal. Mach. Intell. | 2 |