The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions used to prove a plethora of lower bounds, especially in the realm of polynomial-time algorithms. The OV-conjecture in moderate dimension states there is no $\epsilon>0$ for which an $O(N^{2-\epsilon})\mathrm{poly}(D)$ time algorithm can decide whether there is a pair of orthogonal vectors in a given set of size $N$ that contains $D$-dimensional binary vectors. We strengthen the evidence for these hardness assumptions. In particular, we show that if the OV-conjecture fails, then two problems for which we are far from obtaining even tiny improvements over exhaustive search would have surprisingly fast algorithms. If the OV conjecture is false, th...
We present functions that can be computed in some fixed polynomial time but are hard on average for ...
We show that popular hardness conjectures about problems from the field of fine-grained complexity t...
We revisit the hardness of approximating the diameter of a network. In the CONGEST model, $ \tilde \...
The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions us...
The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions us...
The Strong Exponential Time Hypothesis (SETH) asserts that for every $\varepsilon>0$ there exists $k...
A central goal of algorithmic research is to determine how fast computational problems can be solved...
© Josh Alman and Virginia Vassilevska Williams. A graph G on n nodes is an Orthogonal Vectors (OV) g...
Fine-grained complexity theory is the area of theoretical computer sciencethat proves conditional lo...
Algorithmic research strives to develop fast algorithms for fundamental problems. Despite its many s...
In this paper, we introduce a general framework for fine-grained reductions of approximate counting ...
To date, the only way to argue polynomial lower bounds for dynamic algorithms is via fine-grained co...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
We investigate the relation between $\delta$ and $\epsilon$ required for obtaining a $(1+\delta)$-ap...
The Orthogonal Vectors problem (OV) asks: given n vectors in {0, 1}O(log n), are two of them orthogo...
We present functions that can be computed in some fixed polynomial time but are hard on average for ...
We show that popular hardness conjectures about problems from the field of fine-grained complexity t...
We revisit the hardness of approximating the diameter of a network. In the CONGEST model, $ \tilde \...
The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions us...
The Strong Exponential Time Hypothesis and the OV-conjecture are two popular hardness assumptions us...
The Strong Exponential Time Hypothesis (SETH) asserts that for every $\varepsilon>0$ there exists $k...
A central goal of algorithmic research is to determine how fast computational problems can be solved...
© Josh Alman and Virginia Vassilevska Williams. A graph G on n nodes is an Orthogonal Vectors (OV) g...
Fine-grained complexity theory is the area of theoretical computer sciencethat proves conditional lo...
Algorithmic research strives to develop fast algorithms for fundamental problems. Despite its many s...
In this paper, we introduce a general framework for fine-grained reductions of approximate counting ...
To date, the only way to argue polynomial lower bounds for dynamic algorithms is via fine-grained co...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
We investigate the relation between $\delta$ and $\epsilon$ required for obtaining a $(1+\delta)$-ap...
The Orthogonal Vectors problem (OV) asks: given n vectors in {0, 1}O(log n), are two of them orthogo...
We present functions that can be computed in some fixed polynomial time but are hard on average for ...
We show that popular hardness conjectures about problems from the field of fine-grained complexity t...
We revisit the hardness of approximating the diameter of a network. In the CONGEST model, $ \tilde \...