arXiv subjects

Rui Ferreira

Publications and source records attributed to Rui Ferreira.

5 recordsLinked to original sources

arXiv2025

Mittag-Leffler functions and convex ordering

The monotonicity of the Mittag-Leffler function $E_α$ with respect to the parameter $α$ is investigated, via some convex ordering properties for related random variables. In particular, it is shown that the mapping $α\mapsto E_α(x^α)$ decreases on $(0,2)$ for all $x> 0$, that the mapping $α\mapsto E_α(-x^α)$ decreases on $(0,1)$ for all $x\ge 1$ and that the mapping $α\mapsto E_α(Γ(1+α)x)$ decreases on $(0,1)$ for all $x\in{\mathbb R}^\ast.$ Analogous results are presented for the two parameter Mittag-Leffler functions $E_{α, β}$ with $β\ge α,$ with an emphasis on the extremal case $β=α.$ Several applications of these results are discussed for Abelian integral equations and subdiffusions.

math.CA↗

arXiv2019

Misspelling Oblivious Word Embeddings

In this paper we present a method to learn word embeddings that are resilient to misspellings. Existing word embeddings have limited applicability to malformed texts, which contain a non-negligible amount of out-of-vocabulary words. We propose a method combining FastText with subwords and a supervised task of learning misspelling patterns. In our method, misspellings of each word are embedded close to their correct variants. We train these embeddings on a new dataset we are releasing publicly. Finally, we experimentally show the advantages of this approach on both intrinsic and extrinsic NLP tasks using public test sets.

cs.CL↗

arXiv2014

Amortized $\tilde{O}(|V|)$-Delay Algorithm for Listing Chordless Cycles in Undirected Graphs

Chordless cycles are very natural structures in undirected graphs, with an important history and distinguished role in graph theory. Motivated also by previous work on the classical problem of listing cycles, we study how to list chordless cycles. The best known solution to list all the $C$ chordless cycles contained in an undirected graph $G = (V,E)$ takes $O(|E|^2 +|E|\cdot C)$ time. In this paper we provide an algorithm taking $\tilde{O}(|E| + |V |\cdot C)$ time. We also show how to obtain the same complexity for listing all the $P$ chordless $st$-paths in $G$ (where $C$ is replaced by $P$ ).

cs.DS↗

arXiv2013

Efficiently Listing Combinatorial Patterns in Graphs

Graphs are extremely versatile and ubiquitous mathematical structures with potential to model a wide range of domains. For this reason, graph problems have been of interest since the early days of computer science. Some of these problems consider substructures of a graph that have certain properties. These substructures of interest, generally called patterns, are often meaningful in the domain being modeled. Classic examples of patterns include spanning trees, cycles and subgraphs. This thesis focuses on the topic of explicitly listing all the patterns existing in an input graph. One of the defining features of this problem is that the number of patterns is frequently exponential on the size of the input graph. Thus, the time complexity of listing algorithms is parameterized by the size of the output. The main contribution of this work is the presentation of optimal algorithms for four different problems of listing patterns in graphs, namely the listing of k-subtrees, k-subgraphs, st-paths and cycles. The algorithms presented are framed within the same generic approach, based in a recursive partition of the search space that divides the problem into subproblems. The key to an efficient implementation of this approach is to avoid recursing into subproblems that do not list any patterns. With this goal in sight, a dynamic data structure, called the certificate, is introduced and maintained throughout the recursion. Moreover, properties of the recursion tree and lower bounds on the number of patterns are used to amortize the cost of the algorithm on the size of the output.

cs.DS↗

arXiv2012

Optimal Listing of Cycles and st-Paths in Undirected Graphs

We present the first optimal algorithm for the classical problem of listing all the cycles in an undirected graph. We exploit their properties so that the total cost is the time taken to read the input graph plus the time to list the output, namely, the edges in each of the cycles. The algorithm uses a reduction to the problem of listing all the paths from a vertex s to a vertex t which we also solve optimally.

cs.DS↗