Computational geometry

We give a deterministic algorithm for triangulating a simple polygon in linear time. The basic strategy is to build a coarse approximation of a triangulation in a bottom-up phase and then use the information computed along the way to refine the triangulation in a top-down phase. The main tools used are the polygon-cutting theorem, which provides us with a balancing scheme, and the planar separator theorem, whose role is essential in the discovery of new diagonals. Only elementary data structures are required by the algorithm. In particular, no dynamic search trees, of our algorithm.

Triangulating a simple polygon in linear time

Computational geometry.

Origami describes rules for creating folded structures from patterns on a flat sheet, but does not prescribe how patterns can be designed to fit target shapes. Here, starting from the simplest periodic origami pattern that yields one-degree-of-freedom collapsible structures-we show that scale-independent elementary geometric constructions and constrained optimization algorithms can be used to determine spatially modulated patterns that yield approximations to given surfaces of constant or varying curvature. Paper models confirm the feasibility of our calculations. We also assess the difficulty of realizing these geometric structures by quantifying the energetic barrier that separates the metastable flat and folded states. Moreover, we characterize the trade-off between the accuracy to which the pattern conforms to the target surface, and the effort associated with creating finer folds. Our approach enables the tailoring of origami patterns to drape complex surfaces independent of absolute scale, as well as the quantification of the energetic and material cost of doing so.

Programming curvature using origami tessellations

Voting based extreme learning machine

Consider laying out a fixed-topology tree of N nodes into external memory with block size B so as to minimize the worst-case number of block memory transfers required to traverse a path from the root to a node of depth D. We prove that the optimal number of memory transfers is $$ \cases{ 
\displaystyle 
\Theta\left( {D \over \lg (1{+}B)} \right) 
& when $D = O(\lg N)$, \cr 
\displaystyle 
\Theta\left( {\lg N \over \lg \left(1{+}{B \lg N \over D}\right)} \right) 
& when $D = \Omega(\lg N)$ and $D = O(B \lg N)$, \cr 
\displaystyle 
\Theta\left( {D \over B} \right) 
& when $D = \Omega(B \lg N)$. 
} $$

Worst-Case Optimal Tree Layout in External Memory

We present the first potential function for pairing heaps with linear range. This implies that the runtime of a short sequence of operations is faster than previously known. It is also simpler than the only other potential function known to give amortized constant amortized time for insertion.

A Linear Potential Function for Pairing Heaps

We study dynamic planar point location in the External Memory Model or Disk Access Model (DAM). Previous work in this model achieves polylog query and polylog amortized update time. We present a data structure with $O( \log_B^2 N)$ query time and $O(\frac{1}{ B^{1-\epsilon}} \log_B N)$ amortized update time, where $N$ is the number of segments, $B$ the block size and $\epsilon$ is a small positive constant, under the assumption that all faces have constant size. This is a $B^{1-\epsilon}$ factor faster for updates than the fastest previous structure, and brings the cost of insertion and deletion down to subconstant amortized time for reasonable choices of $N$ and $B$. Our structure solves the problem of vertical ray-shooting queries among a dynamic set of interior-disjoint line segments; this is well-known to solve dynamic planar point location for a connected subdivision of the plane with faces of constant size.

External Memory Planar Point Location with Fast Updates

The 3SUM problem asks if an input $n$-set of real numbers contains a triple whose sum is zero. We consider the 3POL problem, a natural generalization of 3SUM where we replace the sum function by a constant-degree polynomial in three variables. The motivations are threefold. Raz, Sharir, and de Zeeuw gave a $O(n^{11/6})$ upper bound on the number of solutions of trivariate polynomial equations when the solutions are taken from the cartesian product of three $n$-sets of real numbers. We give algorithms for the corresponding problem of counting such solutions. Gronlund and Pettie recently designed subquadratic algorithms for 3SUM. We generalize their results to 3POL. Finally, we shed light on the General Position Testing (GPT) problem: "Given $n$ points in the plane, do three of them lie on a line?", a key problem in computational geometry. 
We prove that there exist bounded-degree algebraic decision trees of depth $O(n^{\frac{12}{7}+\varepsilon})$ that solve 3POL, and that 3POL can be solved in $O(n^2 {(\log \log n)}^\frac{3}{2} / {(\log n)}^\frac{1}{2})$ time in the real-RAM model. Among the possible applications of those results, we show how to solve GPT in subquadratic time when the input points lie on $o({(\log n)}^\frac{1}{6}/{(\log \log n)}^\frac{1}{2})$ constant-degree polynomial curves. This constitutes a first step towards closing the major open question of whether GPT can be solved in subquadratic time. 
To obtain these results, we generalize important tools --- such as batch range searching and dominance reporting --- to a polynomial setting. We expect these new tools to be useful in other applications.

Subquadratic Algorithms for Algebraic Generalizations of 3SUM

We construct the first two continuous bloomings of all convex polyhedra. First, the source unfolding can be continuously bloomed. Second, any unfolding of a convex polyhedron can be refined (further cut, by a linear number of cuts) to have a continuous blooming.

John Iacono

Papers

Worst-Case Optimal Tree Layout in External Memory

A Linear Potential Function for Pairing Heaps

External Memory Planar Point Location with Fast Updates

Subquadratic Algorithms for Algebraic Generalizations of 3SUM

Continuous Blooming of Convex Polyhedra