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Zander Kelley

dblp:187/4443 · DBLP profile ↗
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8ranked-venue papers
6as first author
6since 2021 · last 2025
0000-0003-0734-2030ORCID · corroborated

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

Theory of computation · 8 · 6 first-author · 6 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
7 papers
Computational complexity · 80% Combinatorics and discrete mathematics · 19% Graph algorithms and graph theory · 2%

Topics — the 17 heaviest of 18, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational complexity
communication complexity
1.622025
More efficient sifting for grid norms, and applications to multiparty communication complexity · FOCS 2025
Explicit Separations between Randomized and Deterministic Number-on-Forehead Communication · STOC 2024
Combinatorics and discrete mathematics
additive combinatorics
1.522025
More efficient sifting for grid norms, and applications to multiparty communication complexity · FOCS 2025
Strong Bounds for 3-Progressions · FOCS 2023
Computational complexity › pseudorandomness
pseudorandom generators
0.922022
Random Restrictions and PRGs for PTFs in Gaussian Space · CCC 2022
Pseudorandom Generators for Read-Once Branching Programs, in Any Order · FOCS 2018
Computational complexity › communication complexity
multiparty communication complexity
0.912025
More efficient sifting for grid norms, and applications to multiparty communication complexity · FOCS 2025
Computational complexity
derandomization
0.822021
An improved derandomization of the switching lemma · STOC 2021
Pseudorandom Generators for Read-Once Branching Programs, in Any Order · FOCS 2018
Computational complexity › algebraic complexity › matrix multiplication
boolean matrix multiplication
0.812024
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms · STOC 2024
Computational complexity
fine-grained complexity
0.812024
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms · STOC 2024
Computational complexity › algebraic complexity
matrix multiplication
0.812024
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms · STOC 2024
Computational complexity › communication complexity › multiparty communication complexity
number-on-forehead model
0.812024
Explicit Separations between Randomized and Deterministic Number-on-Forehead Communication · STOC 2024
Combinatorics and discrete mathematics › extremal combinatorics
density bounds
0.712023
Strong Bounds for 3-Progressions · FOCS 2023
Computational complexity
gaussian space
0.612022
Random Restrictions and PRGs for PTFs in Gaussian Space · CCC 2022
Computational complexity › boolean function analysis
polynomial threshold function
0.612022
Random Restrictions and PRGs for PTFs in Gaussian Space · CCC 2022
Computational complexity › circuit complexity
random restrictions
0.612022
Random Restrictions and PRGs for PTFs in Gaussian Space · CCC 2022
Computational complexity
circuit complexity
0.512021
An improved derandomization of the switching lemma · STOC 2021
Computational complexity › circuit complexity › branching programs
read-once branching programs
0.312018
Pseudorandom Generators for Read-Once Branching Programs, in Any Order · FOCS 2018
Computational complexity › derandomization
space-bounded derandomization
0.312018
Pseudorandom Generators for Read-Once Branching Programs, in Any Order · FOCS 2018
Graph algorithms and graph theory
graph decomposition
0.212024
New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms · STOC 2024

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

sifting argument · 0.9cylinder intersection covering · 0.9graph decomposition techniques · 0.8explicit construction · 0.8combinatorial matrix multiplication · 0.8arithmetic progression avoidance · 0.8finite-field adaptation · 0.7analytic techniques · 0.7random restrictions · 0.6pseudorandom restriction · 0.5
YearPublicationVenuePosition
2025 More efficient sifting for grid norms, and applications to multiparty communication complexity
abstract
Building on the techniques behind the recent progress on the 3-term arithmetic progression problem [15], Kelley, Lovett, and Meka [14] constructed the first explicit 3-player function $f:[N]^{3} \rightarrow\{0,1\}$ that demonstrates a strong separation between randomized and (non-)deterministic NOF communication complexity. Specifically, their hard function can be solved by a randomized protocol sending $O(1)$ bits, but requires $\Omega\left(\log ^{1 / 3}(N)\right)$ bits of communication with a deterministic (or non-deterministic) protocol. We show a stronger $\Omega\left(\log ^{1 / 2}(N)\right)$ lower bound for their construction. To achieve this, the key technical advancement is an improvement to the sifting argument for grid norms of (somewhat dense) bipartite graphs. In addition to quantitative improvement, we qualitatively improve over [14] by relaxing the hardness condition: while [14] proved their lower bound for any function f that satisfies a strong two-sided pseudorandom condition, we show that a weak one-sided condition suffices. This is achieved by a new structural result for cylinder intersections (or, in graph-theoretic language, the set of triangles induced from a tripartite graph), showing that any small cylinder intersection can be efficiently covered by a sum of simple “slice” functions.
Zander Kelley
FOCS1
2024 New Graph Decompositions and Combinatorial Boolean Matrix Multiplication Algorithms
abstract
We revisit the fundamental Boolean Matrix Multiplication (BMM) problem. With the invention of algebraic fast matrix multiplication over 50 years ago, it also became known that BMM can be solved in truly subcubic O(nω) time, where ω<3; much work has gone into bringing ω closer to 2. Since then, a parallel line of work has sought comparably fast combinatorial algorithms but with limited success. The na'ive O(n3)-time algorithm was initially improved by a log2n factor [Arlazarov et al.; RAS’70], then by log2.25n [Bansal and Williams; FOCS’09], then by log3n [Chan; SODA’15], and finally by log4n [Yu; ICALP’15].
Amir Abboud, Nick Fischer, Zander Kelley, Shachar Lovett, Raghu Meka
STOC3
2024 Explicit Separations between Randomized and Deterministic Number-on-Forehead Communication
abstract
We study the power of randomness in the Number-on-Forehead (NOF) model in communication complexity. We construct an explicit 3-player function f:[N]3 → {0,1}, such that: (i) there exist a randomized NOF protocol computing it that sends a constant number of bits; but (ii) any deterministic or nondeterministic NOF protocol computing it requires sending about (logN)1/3 many bits. This exponentially improves upon the previously best-known such separation. At the core of our proof is an extension of a recent result on sets of integers without 3-term arithmetic progressions into a non-arithmetic setting.
Zander Kelley, Shachar Lovett, Raghu Meka
STOC1
2023 Strong Bounds for 3-Progressions
abstract
We show that for some constant $\beta\gt0$, any subset A of integers $\{1, \ldots, N\}$ of size at least $2^{-O\left((\log N)^{\beta}\right)} \cdot N$ contains a non-trivial three-term arithmetic progression. Previously, three-term arithmetic progressions were known to exist only for sets of size at least $N /(\log N)^{1+c}$ for a constant $c\gt0$.Our approach is first to develop new analytic techniques for addressing some related questions in the finite-field setting and then to apply some analogous variants of these same techniques, suitably adapted for the more complicated setting of integers.
Zander Kelley, Raghu Meka
FOCS1
2022 Random Restrictions and PRGs for PTFs in Gaussian Space
abstract
A polynomial threshold function (PTF) $f:\mathbb{R}^n \rightarrow \mathbb{R}$ is a function of the form $f(x) = \mathsf{sign}(p(x))$ where $p$ is a polynomial of degree at most $d$. PTFs are a classical and well-studied complexity class with applications across complexity theory, learning theory, approximation theory, quantum complexity and more. We address the question of designing pseudorandom generators (PRG) for polynomial threshold functions (PTFs) in the gaussian space: design a PRG that takes a seed of few bits of randomness and outputs a $n$-dimensional vector whose distribution is indistinguishable from a standard multivariate gaussian by a degree $d$ PTF. Our main result is a PRG that takes a seed of $d^{O(1)}\log ( n / \varepsilon)\log(1/\varepsilon)/\varepsilon^2$ random bits with output that cannot be distinguished from $n$-dimensional gaussian distribution with advantage better than $\varepsilon$ by degree $d$ PTFs. The best previous generator due to O'Donnell, Servedio, and Tan (STOC'20) had a quasi-polynomial dependence (i.e., seedlength of $d^{O(\log d)}$) in the degree $d$. Along the way we prove a few nearly-tight structural properties of restrictions of PTFs that may be of independent interest.
Zander Kelley, Raghu Meka
CCC1
2021 An improved derandomization of the switching lemma
abstract
We prove a new derandomization of Håstad’s switching lemma, showing how to efficiently generate restrictions satisfying the switching lemma for DNF or CNF formulas of size m using only O(logm) random bits. Derandomizations of the switching lemma have been useful in many works as a key building-block for constructing objects which are in some way provably-pseudorandom with respect to AC0-circuits.
Zander Kelley
STOC1
2018 Pseudorandom Generators for Read-Once Branching Programs, in Any Order
abstract
A central question in derandomization is whether randomized logspace (RL) equals deterministic logspace (L). To show that RL = L, it suffices to construct explicit pseudorandom generators (PRGs) that fool polynomial-size read-once (oblivious) branching programs (roBPs). Starting with the work of Nisan [Nis92], pseudorandom generators with seedlength O(log2n) were constructed (see also [INW94], [GR14]). Unfortunately, improving on this seed-length in general has proven challenging and seems to require new ideas. A recent line of inquiry (e.g., [BV10], [GMR+12], [IMZ12], [RSV13], [SVW14], [HLV17], [LV17], [CHRT17]) has suggested focusing on a particular limitation of the existing PRGs ([Nis92], [INW94], [GR14]), which is that they only fool roBPs when the variables are read in a particular known order, such as x1n. In comparison, existentially one can obtain logarithmic seed-length for fooling the set of polynomial-size roBPs that read the variables under any fixed unknown permutation xπ(1)xπ(n). While recent works have established novel PRGs in this setting for subclasses of roBPs, there were no known no(1)seed-length explicit PRGs for general polynomial-size roBPs in this setting. In this work, we follow the "bounded independence plus noise" paradigm of Haramaty, Lee and Viola [HLV17], [LV17], and give an improved analysis in the general roBP unknownorder setting. With this analysis we obtain an explicit PRG with seed-length O(log3n) for polynomial-size roBPs reading their bits in an unknown order. Plugging in a recent Fourier tail bound of Chattopadhyay, Hatami, Reingold, and Tal [CHRT17], we can obtain a Õ(log2n) seed-length when the roBP is of constant width.
Michael A. Forbes 0001, Zander Kelley
FOCS2
2017 Estimating the number of roots of trinomials over finite fields
Zander Kelley, Sean W. Owen
J. Symb. Comput.1