Gauge fields are special in the sense that they are invariant under gauge transformations and " ipso facto " they lead to problems when we try quantizing them straightforwardly. To circumvent this problem we need to specify a gauge condition to fix the gauge so that the fields that are connected by gauge invariance are not overcounted in the process of quantization. The usual way we do this in ...

In this paper, we propose to solve the linear multicommodity flow problem using a partial Lagrangian relaxation. The relaxation is restricted to the set of arcs that are likely to be saturated at the optimum. This set is itself approximated by an active set strategy. The partial Lagrangian dual is solved with Proximal-ACCPM, a variant of the analytic center cutting plane method. The new approac...

In this article it is shown how non-holonomic constraints can be included in the formulation of the dynamic equations of flexible multibody systems. The equations are given in state space form with the degrees of freedom, their derivatives and the kinematic coordinates as state variables, which circumvents the use of Lagrangian multipliers. With these independent state variables for the system ...

We also evaluated our hypotheses using two additional firm performance measures: Tobin’s Q, which is the total dollar amount market value divided by the total dollar amount replacement value of a firm in a given year) and operating revenue/total assets, which is the total dollar amount of revenue divided by total dollar amount of assets of a firm in a given year. We selected these measures beca...

Marcet and Marimon (1994, revised 1998) developed a recursive saddle point method which can be used to solve dynamic contracting problems that include participation, enforcement and incentive constraints. Their method uses a recursive multiplier to capture implicit prior promises to the agent(s) that were made in order to satisfy earlier instances of these constraints. As a result, their method...

Clustering is one of the most fundamental and important tasks in data mining. Traditional clustering algorithms, such as K-means, assign every data point to exactly one cluster. However, in real-world datasets, the clusters may overlap with each other. Furthermore, often, there are outliers that should not belong to any cluster. We recently proposed the NEO-K-Means (Non-Exhaustive, Overlapping ...

| This paper describes two new xed-rate entropy-coded quantization methods for stationary memoryless sources where the structure of code-words are derived from a variable-length scalar quantizer. In the rst method, we formulate the quantization as a zero-one integer optimization problem. We show that the resulting integer program can be closely approximated by solving a simple linear program. T...

Recently, new cost-based filtering algorithms for shorter-path constraints have been developed. However, so far only the theoretical properties of shorter-path constraint filtering have been studied. We provide the first extensive experimental evaluation of the new algorithms in the context of the resource constrained shortest path problem. We show how reasoning about path-substructures in comb...

We show that the Lagrangian dual of a constrained linear estimation problem is a particular nonlinear optimal control problem. The result has an elegant symmetry, which is revealed when the constrained estimation problem is expressed as an equivalent nonlinear optimisation problem. The results extend and enhance known connections between the linear quadratic regulator and linear quadratic state...

The goal of subspace segmentation is to partition a set of data drawn from a union of subspace into their underlying subspaces. The performance of spectral clustering based approaches heavily depends on learned data affinity matrices, which are usually constructed either directly from the raw data or from their computed representations. In this paper, we propose a novel method to simultaneously...