This paper presents a method of extending Support Vector Machines (SVMs) for dealing with multiclass problems. Motivated by the Decision Directed Acyclic Graph (DDAG), we propose the Adaptive DAG (ADAG): a modified structure of the DDAG that has a lower number of decision levels and reduces the dependency on the sequence of nodes. Thus, the ADAG improves the accuracy of the DDAG while maintaini...

The introduction of statistical models represented by directed acyclic graphs (DAGs) has proved fruitful in the construction of expert systems, in allowing efficient updating algorithms that take advantage of conditional independence relations (Pearl, 1988, Lauritzen et al. 1993), and in inferring causal structure from conditional independence relations (Spirtes and Glymour, 1991, Spirtes, Glym...

A chain graph (CG) is a graph admitting both directed and undirected edges with forbidden directed cycles. It generalizes both the concept of undirected graph (UG) and the concept of directed acyclic graph (DAG). CGs can be used eeciently to store graphoids, that is, independency knowledge of the form \X is independent of Y given Z" obeying a set of ve properties (axioms). Two equivalent criter...

Density map is an effective visualization technique for depicting the scalar field distribution in 2D space. Conventional methods constructing density maps are mainly based on Euclidean distance, limiting their applicability urban analysis that shall consider road network and traffic. In this work, we propose a new method named Topology Map, targeting accurate intuitive context of environment. ...

In a dominance drawing Γ of directed acyclic graph (DAG) G, vertex v is reachable from u if, and only if all the coordinates are greater than or equal to in Γ. Dominance drawings DAGs very important many areas research. They combine aspect DAG on grid with fact that transitive closure apparently obvious by relation between points associated vertices. The smallest number d for which given G has ...

Directed Acyclic Graph(DAG) could be used for modeling subsumption hierarchies. Several labeling schemes have been proposed or tailored for indexing DAG in order to efficiently explore relationships in such hierarchy. However few of them can satisfy all the requirements in response time, space, and effect of updates simultaneously. In this paper, the prime number labeling scheme is extended for...

A DTW-based directed acyclic graph (DAG) optimization method is proposed to exploit the interaction information of speech and speaker in feature component. We introduce the DAG representation of intra-class samples based on dynamic time warping (DTW) measure and propose two criteria based on in-degree of DAG. Combined with (l − r) optimization algorithm, the DTW-based DAG model is applied to di...

Many real-world applications involve multilabel classification, in which the labels are organized in the form of a tree or directed acyclic graph (DAG). However, current research efforts typically ignore the label dependencies or can only exploit the dependencies in tree-structured hierarchies. In this paper, we present a novel hierarchical multilabel classification algorithm which can be used ...

A conjugate and conditional conjugate Bayesian analysis is presented for bi-directed discrete graphical models, which are used to describe and estimate marginal associations between categorical variables. To achieve this, each bi-directed graph is re-expressed by a Markov equivalent, over the observed margin, directed acyclic graph (DAG). This DAG equivalent model is obtained using the same ver...

Differential Neural Architecture Search (NAS) methods represent the network architecture as a repetitive proxy directed acyclic graph (DAG) and optimize weights alternatively in differential manner. However, existing model on each edge (i.e., layer network) statistically independent variables, ignoring dependency between edges DAG induced by their topological connections. In this paper, we make...