In BURTON-KEANE'S structural paper 1] a situation has not been lightened, such that the proof of their result about the topological structure of ribbons in the two-dimensional site percolation has a gap. We introduce the connuent zone notion and prove, using Burton-Keane's arguments , the almost surely absence of these zones (This completes the proof of the topological structure of ribbons anno...

This paper applies machine learning and the mathematics of chaos to the task of designing indoor rock-climbing routes. Chaotic variation has been used to great advantage on music and dance, but the challenges here are quite different, beginning with the representation. We present a formalized system for transcribing rock climbing problems, then describe a variation generator that is designed to...

The Expectation-Maximization (EM) algorithm is a hill-climbing approach to finding a local maximum of a likelihood function [7, 8]. The EM algorithm alternates between finding a greatest lower bound to the likelihood function (the “E Step”), and then maximizing this bound (the “M Step”). The EM algorithm belongs to a broader class of alternating minimization algorithms [6], which includes the A...

The multiple extension problem arises because a default theory can use diierent subsets of its defaults to propose diierent, mutually incompatible , answers to some queries. This paper presents an algorithm that uses a set of observations to learn a credulous version of this default theory that is (essentially) \optimally accurate". In more detail, we can associate a given default theory with a...

The paper utilizes Port State Control inspection data for discovering interactions between the numbers of various types of deficiencies found on ships and between the deficiencies and ship’s involvement in maritime traffic accidents and incidents. Bayesian network models for describing the dependencies of the inspection results, ship age, type, flag, accident involvement, and incidents reported...

Current endeavors in community detection suffer from the resolution limit problem and can be quite expensive for large networks, especially those based on optimization schemes. We propose a conceptually different approach for multi-resolution community detection, by introducing the kernels from statistical literature into the graph, which mimic the node interaction that decays locally with the ...

The structured language model (SLM) of [1] was one of the first to successfully integrate syntactic structure into language models. We extend the SLM framework in two new directions. First, we propose a new syntactic hierarchical interpolation that improves over previous approaches. Second, we develop a general information-theoretic algorithm for pruning the underlying Jelinek-Mercer interpolat...

We empirically investigate the properties of the search space and the behavior of hill-climbing search for solving hard, random Boolean satis ability problems. In these experiments it was frequently observed that rather than attempting to escape from plateaus by extensive search, it was better to completely restart from a new random initial state. The optimumpoint to terminate search and restar...

We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.