Directed Gaussian graphical models are statistical that use a directed acyclic graph (DAG) to represent the conditional independence structures between set of jointly normal random variables. The DAG specifies model through recursive factorization parametrization, via restricted distributions. In this paper, we make an attempt characterize DAGs whose vanishing ideals toric ideals. particular, g...

Bayesian networks represent relations between variables using a directed acyclic graph (DAG). Learning the DAG is an NP-hard problem and exact learning algorithms are feasible only for small sets of variables. We propose two scalable heuristics DAGs in linear structural equation case. Our methods learn by alternating unconstrained gradient descent-based step to optimize objective function solvi...

We introduce directed acyclic graph (DAG) games, a generalization of standard tree games, to study cost sharing on networks. This structure has not been previously analyzed from a cooperative game theoretic perspective. Every monotonic and subadditive cost game – including monotonic minimum cost spanning tree games – can be modeled as a DAG-game. We provide an efficiently verifiable condition s...

Several real problems ranging from text classification to computational biology are characterized by hierarchical multi-label classification tasks. Most of the methods presented in literature focused on tree-structured taxonomies, but only few on taxonomies structured according to a Directed Acyclic Graph (DAG). In this contribution novel classification ensemble algorithms for DAG-structured ta...

We generalise the insertion into a binary heap to any directed acyclic graph (DAG) with one source vertex. This lets us formulate a general method for converting any such DAG into a data structure with priority queue interface. We apply our method to a hypercube DAG to obtain a sorting algorithm of complexity $\mathcal{O}(n\log^2 (n))$. As another curious application, we derive a relationship b...

The activities, in project scheduling, can be represented graphically in two different ways, by either assigning the activities to the nodes ‘AoN’ directed acyclic graph (dag) or to the arcs ‘AoA dag’. In this paper, a new algorithm is proposed for generating, for a given project scheduling problem, an Activity-on-Arc dag starting from the Activity-on-Node dag using the concepts of line graphs ...

An algorithm for generating the structure of a directed acyclic graph from data using the notion of causal input lists is prest'nted. The algorithm manipulates the ordt'ring of the variables with operations which very much resemble arc reversal. Operations are only applied if the DAG after the operation repre­ sents at least the independencies represented by the DAG before the operation until n...

In this note I describe how to capture the kinematics of quantum causal evolution using a logic called BV developed by the Calculus of Structures group at Dresden. The setting is discrete quantum mechanics. We imagine a finite “web” of spacetime points. The points are events in spacetime. They are viewed as verhtees in a directed acyclic graph (DAG); the edges of the DAG represent causal links ...

In this paper, we present a system partitioning technique in which the input system specification is based on C++ language. The proposed technique processes data and precedence dependencies simultaneously in one graph representation DADGP, which is an extension of Directed Acyclic Graph (DAG). The DADGP (Directed Acyclic Data dependency Graph with Precedence) based partitioning technique minimi...

AWARE is a knowledge representation language for specifying NLU inference rules. AWARE-system takes as its input the parse trees of NL utterances and further refines them by using DAG-transformations (Directed Acyclic Graph) and recursive descent translation techniques. AWARE has been used for semantic analysis in our Finnish language database interface. The input dependency tree is transformed...