Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts

We present a Bayesian nonparametric framework for multilevel clustering which utilizes group-level context information to simultaneously discover low-dimensional structures of the group contents and partitions groups into clusters. Using the Dirichlet process as the building block, our model constructs a product base-measure with a nested structure to accommodate content and context observations at multiple levels. The proposed model possesses properties that link the nested Dirichlet processes (nDP) and the Dirichlet process mixture models (DPM) in an interesting way: integrating out all contents results in the DPM over contexts, whereas integrating out group-specific contexts results in the nDP mixture over content variables. We provide a Polya-urn view of the model and an efficient collapsed Gibbs inference procedure. Extensive experiments on real-world datasets demonstrate the advantage of utilizing context information via our model in both text and image domains.Comment: Full version of ICML 201

Automorphism Groups of Graphical Models and Lifted Variational Inference

Using the theory of group action, we first introduce the concept of the automorphism group of an exponential family or a graphical model, thus formalizing the general notion of symmetry of a probabilistic model. This automorphism group provides a precise mathematical framework for lifted inference in the general exponential family. Its group action partitions the set of random variables and feature functions into equivalent classes (called orbits) having identical marginals and expectations. Then the inference problem is effectively reduced to that of computing marginals or expectations for each class, thus avoiding the need to deal with each individual variable or feature. We demonstrate the usefulness of this general framework in lifting two classes of variational approximation for MAP inference: local LP relaxation and local LP relaxation with cycle constraints; the latter yields the first lifted inference that operate on a bound tighter than local constraints. Initial experimental results demonstrate that lifted MAP inference with cycle constraints achieved the state of the art performance, obtaining much better objective function values than local approximation while remaining relatively efficient.Comment: Extended version of the paper to appear in Statistical Relational AI (StaRAI-12) workshop at UAI '1

Study of Factors Affecting the Leadership Capacity of CEO in Industrial SMEs in Vietnam

The leadership capabilities of management team greatly influence the performance of management activities in an enterprise. Capturing and evaluating the impact of elements influencing leadership ability might help enterprises to formulate policies to optimize the capacity of the management team. The scope of the study in this paper is the survey of SMEs in Vietnam. The research team conducted 141 surveys by executives and managers working as heads of departments within current industrial SMEs in Vietnam. Research has indicated the three influential factors including self-efficacy, environment and personal characteristics, with personal traits making the least impact. Keywords: Leadership capabilities, CEO, small and medium industry enterprises

Using interaction signatures to find and label chairs and floors

The use of interaction signatures to recognize objects without considering the object\u27s physical structure is discussed. Without object recognition, smart homes cannot make full use of video cameras because vision systems cannot provide object-related context to the human activities monitored. One important advantage of interaction signatures is that people frequently and repeatedly interact with household objects, so the system can build evidence for object locations and labels

Influence of the Frequency-chirp on Pulse in Passively Mode-locking Optical Fiber Ring Laser

We consider a model of a passively mode-locking fiber ring laser bult using a saturable absorber and a chirped fiber Bragg grating to balance dispersion and nonlinearity. The evolution of the slowly envelope of the optical field in a loop fiber subject to dispersion , Kerr nonlinearity, frequency- chirp and nonlinear absorption is given by the generalized complex Ginzburg-Landau equation. The influence of the frequency-chirp on the pulse is simulated and discussed, and the stationary conditions concerning the chirp parameter are  found out for our laser