This paper develops slacks-based measure (SBM) and additive SBM (ASBM) to evaluate efficiency of decision making units (DMUs) in a two-stage structure with undesirable outputs and feedback variables from the internal perspective. The SBM model is linearized  for a specific weight and the ASBM model is reformulated as a second order cone program. The target values for all inputs, outputs (both d...

The current paper proposes a slack-based version of the Super SBM, which is an alternative superefficiency model for the SBM proposed by Tone. Our two-stage approach provides the same superefficiency score as that obtained by the Super SBM model when the evaluated DMU is efficient and yields the same efficiency score as that obtained by the SBM model when the evaluated DMU is inefficient. The p...

Stochastic blockmodel (SBM) enables us to decompose and analyze an exploratory network without a priori knowledge about its intrinsic structure. However, the task of effectively and efficiently learning a SBM from a large-scale network is still challenging due to the high computational cost of its model selection and parameter estimation. To address this issue, we present a novel SBM learning a...

The Stochastic Block Model (SBM) is a widely used random graph model for networks with communities. Despite the recent burst of interest in community detection under the SBM from statistical and computational points of view, there are still gaps in understanding the fundamental limits of recovery. In this paper, we consider the SBM in its full generality, where there is no restriction on the nu...

In the history of DEA, there are two fundamental “Radial” and “Non-radial” approaches for the efficiency measurement. Each approach has its own advantageous and shortcomings. Avkiran et al. (2008) provided a unified framework, named Connected-SBM, for linking these approaches. In the present paper, first, based on the directional distance function we develop the Directional Slack-Based Measures...

many studies have been conducted to determine the efficiency of two-stage network structures in the recent years. the two-stage network with additional inputs to the second stage, in which the second stage is independent of the first stage are one of these structures. thus, there is a need for a model capable of calculating the efficiency of two-stage structures as well as efficiency of each st...

In this paper, we propose HMM-based text-to-speech (TTS) using sub-band basis spectrum model (SBM). SBM can represent vocal tract spectra and phase characteristics by a linear combination of sub-band basis vectors. Some reports suggest that analysis-synthesized speech based on SBM is close to natural speech and SBM can perform effectively in TTS. Therefore, the SBM framework is expected to have...

The stochastic block model (SBM) is a probabilistic model for community structure in networks. Typically, only the adjacency matrix is used to perform SBM parameter inference. In this paper, we consider circumstances in which nodes have an associated vector of continuous attributes that are also used to learn the node-to-community assignments and corresponding SBM parameters. While this assumpt...

Clustering is an important task in network analysis, with applications in fields such as biology and the social sciences. We present a novel inference algorithm for the Stochastic Block Model (SBM), a well known network clustering model. Previous inference in this model typically utilizes Markov Chain Monte Carlo or Variational Bayes, but our method is the first to utilize Stochastic Variationa...