arXiv subjects

Yaqiao Li

Publications and source records attributed to Yaqiao Li.

At least 19 recordsLinked to original sources

arXiv2026

New bounds for online coloring three-colorable graphs

We prove new lower and upper bounds for online coloring of three-colorable graphs, improving classical bounds of Vishwanathan [FOCS'1990] that have stood for more than three decades. For the lower bound against deterministic algorithms, we improve Vishwanathan's $Ω(\log^2n)$ to $\exp\!\bigl(Ω((\log n)^{1/3}(\log\log n)^{2/3})\bigr)$. For the upper bound of randomized algorithms, we give a randomized algorithm that achieves $O(\sqrt{n})$ improving Vishwanathan's $O(\sqrt{n \log n})$. Technically, for the lower bound construction, we introduce the language of $t$-fold coloring for simpler description of recursive construction, and the notion of post-degree for future control, and use the flexibility of two-sided colors of bipartite graph, constructed using the independent set amplification method of Vishwanathan, as building blocks to ensure three-colorability. The randomized algorithm integrates, in a new way, some of the ideas in offline coloring of Wigderson and Blum with ideas of Vishwanathan in the online setting, such as the degree control from Wigderson, the offline-monochromatic class from Blum, and the anchor-sampling from Vishwanathan and the CBIP algorithm by Lov{á}sz, Saks and Trotter.

cs.DS↗

arXiv2026

Two exact quantum queries use at most six variables

We give a direct analytic proof that every total Boolean function computable exactly with at most two quantum queries depends on at most six input variables. This bound is sharp. A previous derivation relied on a numerical classification of Boolean functions on at most four variables; to the best of our knowledge, ours is the first unconditional proof. The main difficulty beyond the one-query case is that query-path vectors need not be mutually orthogonal, so interference prevents the scalar weight-counting argument from applying. We overcome this difficulty by establishing a rigid support-and-branch decomposition: after the coordinates in the first-query support are fixed, the second query induces a family of exact one-query branches. This structural description may be of independent interest.

quant-ph↗

arXiv2026

Online geometric matching and segments block points

Given a sequence of online points in general position in the plane, the geometric matching problem asks to match as many points as possible, subject to segment crossing constraints. We initiate the study of online geometric matching with limited crosses. In the $k$-crossing model each matched segment is allowed to have at most $k$ crosses, where $k=0$ corresponds to the online noncrossing matching model for which Bose et al. proved that Greedy is an optimal deterministic algorithm achieving a competitive ratio of $2/3$. In the triangle-free-crossing model no three matched segments are allowed to pairwise cross each other. Interestingly, we show in both cases the performance of Greedy does not improve by allowing crosses, and in fact, becomes worse in the $k$-crossing setting for $k\ge 1$. In the triangle-free-crossing model, we propose a simple two-layer-Greedy deterministic algorithm achieving a competitive ratio $4/5$. More interestingly, we propose and study the underlying segments blocking points extremal problem, and discuss its connection to vertex cover numbers and Ramsey numbers, with interesting open problems that might be of independent interest. We revisit the noncrossing model. We give a randomized algorithm which is an asymmetric version of Kamali et al., improving the competitive ratio from $0.66952$ to $0.67034$. We also show, via a conceptually simple construction, that no randomized algorithm can match more than $6/7$ fraction of points, improving the previous $16/17$ by Boyar et al.

cs.DS↗

arXiv2026

FirstFit coloring process of random bipartite graphs and an online coloring lower bound in the random order model

FirstFit colors each arriving vertex with the smallest positive integer absent from its previously colored neighborhood. We prove that this rule can require $n^{Ω(1)}$ many colors on certain bipartite graph of $n$ vertices even when the vertices arrive in a uniformly random order. This refutes the conjecture of Bosek, Gutowski, Lasoń, and Przybyło [BGLP24] that FirstFit uses a polylogarithmic expected number of colors on every bipartite graph in the random order model. We obtain the lower bound by analyzing the FirstFit coloring process on random bipartite graphs, where vertices arrive to either side with equal probability, and with an independent edge density $n^{-x}$ for some $0 < x < 1$. Our result can also be viewed as a qualitative strengthening of Kučera [Kuč91], who showed that, for every $ε> 0$, there are graphs with chromatic number at most $n^ε$ on which FirstFit uses $Ω(n/\log n)$ colors in expectation under a uniformly random order. Our result shows that such poor behavior of FirstFit already occurs for $χ(G) = 2$.

cs.DS↗

arXiv2026

FirstFit online coloring in the random order model

The average performance of FirstFit online coloring on trees in the random order model is completely determined in recent works of Frei et al. and Bosek et al., showing $Θ(\log n /\log\log n)$ number of colors, improving the $Θ(\log n)$ colors in the adversarial model. We provide a few further results on slightly more general graph classes. Firstly, we extend their method to obtain a simple path-counting principle for sparse graph classes, which immediately yields for example that cactus graphs and uniform hypertrees exhibit a similar improvement. We then show that FirstFit uses only $O(1)$ colors on crown graphs, a standard example where adversarial arrival forces $Θ(n)$ colors. We further show that density alone (even linear minimum degree) is insufficient to guarantee $O(1)$ colors even on bipartite graphs. Finally, we identify graph classes, including unit interval graphs and some graphs of high chromatic number, for which random arrival provides only limited improvement. We end with some open problems.

cs.DS↗

arXiv2026

Online Interval Selection on a Simple Chain

A set of intervals $I = \{ I_1, I_2, \dots, I_n \}$ forms a simple chain if, for every $2\leq i \leq n-1$, interval $I_i$ overlaps only with $I_{i-1}$ and $I_{i+1}$. We show that a deterministic memoryless one-directional revoking algorithm achieves a competitive ratio of $2(1 - 1/\sqrt{e}) \approx 0.786$ on the simple chain in the random order model, hence performs worse than the basic greedy algorithm without revoking that has a competitive ratio of $(1 - 1/e^2) \approx 0.864$, but better than any deterministic revoking algorithm in the adversarial model that has a competitive ratio of at most $0.75$. The proof of the latter also leads to a lower bound of $n/4$ for the advice complexity.

cs.DS↗

arXiv2026

A Top-Down Depth-Four Circuit Lower Bound for Majority

We present a top-down depth-four circuit lower bound for Majority function by extending recent work of Göös, Riazanov, Sofronova, and Sokolov (FOCS 2023), who gave a top-down proof of a depth-four circuit lower bound for Parity which relies on the robust sunflower to construct a mirror set and the block unpredictability to find the local limits. The main challenge for the case of Majority is to construct a corresponding mirror set, the difference is that to flip the value of Majority function, one may have to flip many bits of the input Boolean string, while for Parity, flipping one bit suffices. We avoid this flipping by considering slices of the Boolean cube, that is, Boolean strings of fixed Hamming weight approximately $n/2$.

cs.CC↗

arXiv2026

On the Online Weighted Non-Crossing Matching Problem

We introduce and study the weighted version of an online matching problem in the Euclidean plane with non-crossing constraints: points with non-negative weights arrive online, and an algorithm can match an arriving point to one of the unmatched previously arrived points. In the classic model, the decision on how to match (if at all) a newly arriving point is irrevocable. The goal is to maximize the total weight of matched points under the constraint that straight-line segments corresponding to the edges of the matching do not intersect. The unweighted version of the problem was introduced in the offline setting by Atallah in 1985, and this problem became a subject of study in the online setting with and without advice in several recent papers. We observe that deterministic online algorithms cannot guarantee a non-trivial competitive ratio for the weighted problem, but we give upper and lower bounds on the problem with bounded weights. In contrast to the deterministic case, we show that using randomization, a constant competitive ratio is possible for arbitrary weights. We also study other variants of the problem, including revocability and collinear points, both of which permit non-trivial online algorithms, and we give upper and lower bounds for the attainable competitive ratios. Finally, we prove an advice complexity bound for obtaining optimality, improving the best known bound.

cs.DS↗

arXiv2025

Undecidability of Polynomial Inequalities in Subset Densities and Additive Energies

Many results in extremal graph theory can be formulated as certain polynomial inequalities in graph homomorphism densities. Answering fundamental questions raised by Lov{á}sz, Szegedy and Razborov, Hatami and Norine proved that determining the validity of an arbitrary such polynomial inequality in graph homomorphism densities is undecidable. We observe that many results in additive combinatorics can also be formulated as polynomial inequalities in subset's density and its variants. Based on techniques introduced in Hatami and Norine, together with algebraic and graph construction and Fourier analysis, we prove similarly two theorems of undecidability, thus showing that establishing such polynomial inequalities in additive combinatorics are inherently difficult in their full generality.

math.CO↗

arXiv2025

Diversity-seeking swap games in networks

Schelling games use a game-theoretic approach to study the phenomenon of residential segregation as originally modeled by Schelling. Inspired by the recent increase in the number of people and businesses preferring and promoting diversity, we propose swap games under three diversity-seeking utility functions: the binary utility of an agent is 1 if it has a neighbor of a different type, and 0 otherwise; the difference-seeking utility of an agent is equal to the number of its neighbors of a different type; the variety-seeking utility of an agent is equal to the number of types different from its own in its neighborhood. We consider four global measures of diversity: degree of integration, number of colorful edges, neighborhood variety, and evenness, and prove asymptotically tight or almost tight bounds on the price of anarchy with respect to these measures on both general graphs, as well as on cycles, cylinders, and tori that model residential neighborhoods. We complement our theoretical results with simulations of our swap games starting either from random placements of agents, or from segregated placements. Our simulation results are generally consistent with our theoretical results, showing that segregation is effectively removed when agents are diversity-seeking; however strong diversity, such as measured by neighborhood variety and evenness, is harder to achieve by our swap games.

cs.GT↗

arXiv2024

Newman's theorem via Carathéodory

We give a streamlined short proof of Newman's theorem in communication complexity by applying the classical and the approximate Carathéodory's theorems.

cs.CC↗

arXiv2024

Renting Servers for Multi-Parameter Jobs in the Cloud

We study the Renting Servers in the Cloud problem (RSiC) in multiple dimensions. In this problem, a sequence of multi-parameter jobs must be scheduled on servers that can be rented on-demand. Each job has an arrival time, a finishing time, and a multi-dimensional size vector that specifies its resource demands. Each server has a multi-dimensional capacity and jobs can be scheduled on a server as long as in each dimension the sum of sizes of jobs does not exceed the capacity of the server in that dimension. The goal is to minimize the total rental time of servers needed to process the job sequence. AF algorithms do not rent new servers to accommodate a job unless they have to. We introduce a sub-family of AF algorithms called monotone AF algorithms. We show this family have a tight competitive ratio of $Theta(d mu)$, where $d$ is the dimension of the problem and $mu$ is the ratio between the maximum and minimum duration of jobs in the input sequence. We also show that upper bounds for the RSiC problem obey the direct-sum property with respect to dimension $d$, that is we show how to transform $1$-dimensional algorithms for RSiC to work in the $d$-dimensional setting with competitive ratio scaling by a factor of $d$. As a corollary, we obtain an $O(d\sqrt{log mu})$ upper bound for $d$-dimensional clairvoyant RSiC. We also establish a lower bound of $\widetilde{Omega}(d mu)$ for both deterministic and randomized algorithms for $d$-dimensional non-clairvoyant RSiC, under the assumption that $mu \le log d - 2$. Lastly, we propose a natural greedy algorithm called Greedy. Greedy, is a clairvoyant algorithm belongs to the monotone AF family, achieves a competitive ratio of $Theta(d mu)$. Our experimental results indicate that Greedy performs better or matches all other existing algorithms, for almost all the settings of arrival rates and values of mu and $d$ that we implemented.

cs.DS↗

arXiv2023

Lifting query complexity to time-space complexity for two-way finite automata

Time-space tradeoff has been studied in a variety of models, such as Turing machines, branching programs, and finite automata, etc. While communication complexity as a technique has been applied to study finite automata, it seems it has not been used to study time-space tradeoffs of finite automata. We design a new technique showing that separations of query complexity can be lifted, via communication complexity, to separations of time-space complexity of two-way finite automata. As an application, one of our main results exhibits the first example of a language $L$ such that the time-space complexity of two-way probabilistic finite automata with a bounded error (2PFA) is $\widetildeΩ(n^2)$, while of exact two-way quantum finite automata with classical states (2QCFA) is $\widetilde{O}(n^{5/3})$, that is, we demonstrate for the first time that exact quantum computing has an advantage in time-space complexity comparing to classical computing.

cs.CC↗

arXiv2023

Online Vector Bin Packing and Hypergraph Coloring Illuminated: Simpler Proofs and New Connections

This paper studies the online vector bin packing (OVBP) problem and the related problem of online hypergraph coloring (OHC). Firstly, we use a double counting argument to prove an upper bound of the competitive ratio of $FirstFit$ for OVBP. Our proof is conceptually simple, and strengthens the result in Azar et. al. by removing the dependency on the bin size parameter. Secondly, we introduce a notion of an online incidence matrix that is defined for every instance of OHC. Using this notion, we provide a reduction from OHC to OVBP, which allows us to carry known lower bounds of the competitive ratio of algorithms for OHC to OVBP. Our approach significantly simplifies the previous argument from Azar et. al. that relied on using intricate graph structures. In addition, we slightly improve their lower bounds. Lastly, we establish a tight bound of the competitive ratio of algorithms for OHC, where input is restricted to be a hypertree, thus resolving a conjecture in Nagy-Gyorgy et. al. The crux of this proof lies in solving a certain combinatorial partition problem about multi-family of subsets, which might be of independent interest.

cs.DS↗

arXiv2023

Perspective on complexity measures targetting read-once branching programs

A model of computation for which reasonable yet still incomplete lower bounds are known is the read-once branching program. Here variants of complexity measures successful in the study of read-once branching programs are defined and studied. Some new or simpler proofs of known bounds are uncovered. Branching program resources and the new measures are compared extensively. The new variants are developed in part in the hope of tackling read-k branching programs for the tree evaluation problem studied in Cook et al. Other computation problems are studied as well. In particular, a common view of a function studied by Gal and a function studied by Bollig and Wegener leads to the general combinatorics of blocking sets. Technical combinatorial results of independent interest are obtained. New leads towards further progress are discussed. An exponential lower bound for non-deterministic read-k branching programs for the GEN function is also derived, independently from the new measures.

cs.CC↗

arXiv2020

Chang's lemma via Pinsker's inequality

Extending the idea in [Impagliazzo, R., Moore, C. and Russell, A., An entropic proof of Chang's inequality. SIAM Journal on Discrete Mathematics, 28(1), pp.173-176.] we give a short information theoretic proof for Chang's lemma that is based on Pinsker's inequality.

cs.DM↗

arXiv2020

Online Coloring and a New Type of Adversary for Online Graph Problems

We introduce a new type of adversary for online graph problems. The new adversary is parameterized by a single integer $κ$, which upper bounds the number of connected components that the adversary can use at any time during the presentation of the online graph $G$. We call this adversary "$κ$ components bounded", or $κ$-CB for short. On one hand, this adversary is restricted compared to the classical adversary because of the $κ$-CB constraint. On the other hand, we seek competitive ratios parameterized only by $κ$ with no dependence on the input length $n$, thereby giving the new adversary power to use arbitrarily large inputs. We study online coloring under the $κ$-CB adversary. We obtain finer analysis of the existing algorithms $FirstFit$ and $CBIP$ by computing their competitive ratios on trees and bipartite graphs under the new adversary. Surprisingly, $FirstFit$ outperforms $CBIP$ on trees. When it comes to bipartite graphs $FirstFit$ is no longer competitive under the new adversary, while $CBIP$ uses at most $2κ$ colors. We also study several well known classes of graphs, such as $3$-colorable, $C_k$-free, $d$-inductive, planar, and bounded treewidth, with respect to online coloring under the $κ$-CB adversary. We demonstrate that the extra adversarial power of unbounded input length outweighs the restriction on the number of connected components leading to non existence of competitive algorithms for these classes.

cs.DS↗

arXiv2020

Conflict complexity is lower bounded by block sensitivity

We show conflict complexity of every total Boolean function, recently introduced in [Swagato Sanyal. A composition theorem via conict complexity. arXiv preprint arXiv:1801.03285, 2018.] to prove a composition theorem of randomized decision tree complexity, is at least a half of its block sensitivity. We propose to compare conflict complexity with certificate complexity, and explain why it could be interesting.

cs.CC↗