Fine-grained complexity theory is the area of theoretical computer sciencethat proves conditional lower bounds based on the Strong Exponential TimeHypothesis and similar conjectures. This area has been thriving in the lastdecade, leading to conditionally best-possible algorithms for a wide variety ofproblems on graphs, strings, numbers etc. This article is an introduction tofine-grained lower bounds in computational geometry, with a focus on lowerbounds for polynomial-time problems based on the Orthogonal Vectors Hypothesis.Specifically, we discuss conditional lower bounds for nearest neighbor searchunder the Euclidean distance and Fr\'echet distance.<br
Many computational problems are subject to a quantum speed-up: one might find that a problem having ...
Computational Complexity is concerned with the resources that are required for algorithms to detect ...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
A central goal of algorithmic research is to determine how fast computational problems can be solved...
Suppose the fastest algorithm that we can design for some problem runs in time O(n^2). However, we w...
This dissertation presents several results in fine-grained complexity. Fine-grained complexity aims ...
A central goal of algorithmic research is to determine how fast computational problems can be solved...
The motivation of this thesis is to present new lower bounds for important computational problems on...
The Strong Exponential Time Hypothesis (SETH) asserts that for every $\varepsilon>0$ there exists $k...
We present functions that can be computed in some fixed polynomial time but are hard on average for ...
To date, the only way to argue polynomial lower bounds for dynamic algorithms is via fine-grained co...
Conditional lower bounds based on $\textup{P}\neq \textup{NP}$, the Exponential-Time Hypothesis (ETH...
This paper presents a new semantic method for proving lower bounds in computational complexity. We u...
The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions us...
This dissertation presents several results at the intersection ofcomplexity theory and algorithm des...
Many computational problems are subject to a quantum speed-up: one might find that a problem having ...
Computational Complexity is concerned with the resources that are required for algorithms to detect ...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
A central goal of algorithmic research is to determine how fast computational problems can be solved...
Suppose the fastest algorithm that we can design for some problem runs in time O(n^2). However, we w...
This dissertation presents several results in fine-grained complexity. Fine-grained complexity aims ...
A central goal of algorithmic research is to determine how fast computational problems can be solved...
The motivation of this thesis is to present new lower bounds for important computational problems on...
The Strong Exponential Time Hypothesis (SETH) asserts that for every $\varepsilon>0$ there exists $k...
We present functions that can be computed in some fixed polynomial time but are hard on average for ...
To date, the only way to argue polynomial lower bounds for dynamic algorithms is via fine-grained co...
Conditional lower bounds based on $\textup{P}\neq \textup{NP}$, the Exponential-Time Hypothesis (ETH...
This paper presents a new semantic method for proving lower bounds in computational complexity. We u...
The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions us...
This dissertation presents several results at the intersection ofcomplexity theory and algorithm des...
Many computational problems are subject to a quantum speed-up: one might find that a problem having ...
Computational Complexity is concerned with the resources that are required for algorithms to detect ...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...