Front-to-End Bidirectional Heuristic Search with Near-Optimal Node Expansions

It is well-known that any admissible unidirectional heuristic search algorithm must expand all states whose $f$-value is smaller than the optimal solution cost when using a consistent heuristic. Such states are called "surely expanded" (s.e.). A recent study characterized s.e. pairs of states for bidirectional search with consistent heuristics: if a pair of states is s.e. then at least one of the two states must be expanded. This paper derives a lower bound, VC, on the minimum number of expansions required to cover all s.e. pairs, and present a new admissible front-to-end bidirectional heuristic search algorithm, Near-Optimal Bidirectional Search (NBS), that is guaranteed to do no more than 2VC expansions. We further prove that no admissible front-to-end algorithm has a worst case better than 2VC. Experimental results show that NBS competes with or outperforms existing bidirectional search algorithms, and often outperforms A* as well.Comment: Accepted to IJCAI 2017. Camera ready version with new timing result

Learning from the past with experiment databases

Thousands of Machine Learning research papers contain experimental comparisons that usually have been conducted with a single focus of interest, and detailed results are usually lost after publication. Once past experiments are collected in experiment databases they allow for additional and possibly much broader investigation. In this paper, we show how to use such a repository to answer various interesting research questions about learning algorithms and to verify a number of recent studies. Alongside performing elaborate comparisons and rankings of algorithms, we also investigate the effects of algorithm parameters and data properties, and study the learning curves and bias-variance profiles of algorithms to gain deeper insights into their behavior

The prediction of fatigue using speech as a biosignal

Automatic systems for estimating operator fatigue have application in safety-critical environments. We develop and evaluate a system to detect fatigue from speech recordings collected from speakers kept awake over a 60-hour period. A binary classification system (fatigued/not-fatigued) based on time spent awake showed good discrimination, with 80 % unweighted accuracy using raw features, and 90 % with speaker-normalized features. We describe the data collection, feature analysis, machine learning and cross-validation used in the study. Results are promising for real-world applications in domains such as aerospace, transportation and mining where operators are in regular verbal communication as part of their normal working activities

Assemblies of aziridinemethanols

Contains fulltext : 14060.pdf (publisher's version ) (Open Access

Empirical Evaluation of the Difficulty of Finding a Good Value of k for the Nearest Neighbor

As an analysis of the classification accuracy bound for the Nearest Neighbor technique, in this work we have studied if it is possible to find a good value of the parmeter k for each example according to their attribute values. Or at least, if there is a pattern for the parameter k in the original search space. We have carried out different approaches based onthe Nearest Neighbor technique and calculated the prediction accuracy for a group of databases from the UCI repository. Based on the experimental results of our study, we can state that, in general, it is not possible to know a priori a specific value of k to correctly classify an unseen example

A General Buffer Scheme for the Windows Scheduling Problem

Broadcasting is an efficient alternative to unicast for delivering popular on-demand media requests. Broadcasting schemes that are based on windows scheduling algorithms provide a way to satisfy all requests with both low bandwidth and low latency. Consider a system of n pages that need to be scheduled (transmitted) on identical channels an infinite number of times. Time is slotted, and it takes one time slot to transmit each page. In the windows scheduling problem (WS) each page i, 1 ≤ i ≤ n, is associated with a request window wi. In a feasible schedule for WS, page i must be scheduled at least once in any window of wi time slots. The objective function is to minimize the number of channels required to schedule all the pages. The main contribution of this paper is the design of a general buffer scheme for the windows scheduling problem such that any algorithm for WS follows this scheme. As a result, this scheme can serve as a tool to analyze and/or exhaust all possible WS-algorithms. The buffer scheme is based on modelling the system as a nondeterministic finite state machine in which any directed cycle corresponds to a legal schedule and vice-versa. Since WS is NP-hard, w

Finding a short and accurate decision rule in disjunctive normal form by exhaustive search

Greedy approaches suffer from a restricted search space which could lead to suboptimal classifiers in terms of performance and classifier size. This study discusses exhaustive search as an alternative to greedy search for learning short and accurate decision rules. The Exhaustive Procedure for LOgic-Rule Extraction (EXPLORE) algorithm is presented, to induce decision rules in disjunctive normal form (DNF) in a systematic and efficient manner. We propose a method based on subsumption to reduce the number of values considered for instantiation in the literals, by taking into account the relational operator without loss of performance. Furthermore, we describe a branch-and-bound approach that makes optimal use of user-defined performance constraints. To improve the generalizability we use a validation set to determine the optimal length of the DNF rule. The performance and size of the DNF rules induced by EXPLORE are compared to those of eight well-known rule learners. Our results show that an exhaustive approach to rule learning in DNF results in significantly smaller classifiers than those of the other rule learners, while securing comparable or even better performance. Clearly, exhaustive search is computer-intensive and may not always be feasible. Nevertheless, based on this study, we believe that exhaustive search should be considered an alternative for greedy search in many problems

Spinal involvement in mucopolysaccharidosis IVA (Morquio-Brailsford or Morquio A syndrome): presentation, diagnosis and management.

Mucopolysaccharidosis IVA (MPS IVA), also known as Morquio-Brailsford or Morquio A syndrome, is a lysosomal storage disorder caused by a deficiency of the enzyme N-acetyl-galactosamine-6-sulphate sulphatase (GALNS). MPS IVA is multisystemic but manifests primarily as a progressive skeletal dysplasia. Spinal involvement is a major cause of morbidity and mortality in MPS IVA. Early diagnosis and timely treatment of problems involving the spine are critical in preventing or arresting neurological deterioration and loss of function. This review details the spinal manifestations of MPS IVA and describes the tools used to diagnose and monitor spinal involvement. The relative utility of radiography, computed tomography (CT) and magnetic resonance imaging (MRI) for the evaluation of cervical spine instability, stenosis, and cord compression is discussed. Surgical interventions, anaesthetic considerations, and the use of neurophysiological monitoring during procedures performed under general anaesthesia are reviewed. Recommendations for regular radiological imaging and neurologic assessments are presented, and the need for a more standardized approach for evaluating and managing spinal involvement in MPS IVA is addressed

Hopf algebras and Markov chains: Two examples and a theory

The operation of squaring (coproduct followed by product) in a combinatorial Hopf algebra is shown to induce a Markov chain in natural bases. Chains constructed in this way include widely studied methods of card shuffling, a natural "rock-breaking" process, and Markov chains on simplicial complexes. Many of these chains can be explictly diagonalized using the primitive elements of the algebra and the combinatorics of the free Lie algebra. For card shuffling, this gives an explicit description of the eigenvectors. For rock-breaking, an explicit description of the quasi-stationary distribution and sharp rates to absorption follow.Comment: 51 pages, 17 figures. (Typographical errors corrected. Further fixes will only appear on the version on Amy Pang's website, the arXiv version will not be updated.