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Salicylate induction of antibiotic resistance in Escherichia coli: activation of the mar operon and a mar-independent pathway.
Since the growth of wild-type Escherichia coli in salicylate results in a multiple antibiotic resistance phenotype similar to that of constitutive mutants (Mar) of the chromosomal mar locus, theExpand
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Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation
TLDR
We propose a stochastic algorithm for collapsed variational Bayesian inference for latent Dirichlet allocation for LDA, which is simpler and more efficient than the state of the art method. Expand
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A review of multi-instance learning assumptions
TLDR
Multi-instance (MI) learning is a variant of inductive machine learning where each learning example contains a bag of instances instead of a single feature vector. Expand
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Joint Models of Disagreement and Stance in Online Debate
TLDR
We introduce a scalable unified probabilistic modeling framework for stance classification models that 1) are collective, 2) reason about disagreement, and 3) can model stance at either the author level or at the post level. Expand
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On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis
TLDR
We show that a simple alternative based on the Laplace mechanism, the workhorse of differential privacy, is as asymptotically efficient as non-private posterior inference, under general assumptions. Expand
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Porin channels in Escherichia coli: studies with beta-lactams in intact cells.
Wild-type Escherichia coli K-12 produces two porins, OmpF (protein 1a) and OmpC (protein 1b). In mutants deficient in both of these "normal" porins, secondary mutants that produce a "new" porin,Expand
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Collective Spammer Detection in Evolving Multi-Relational Social Networks
TLDR
We model a social network as a time-stamped multi-relational graph where vertices represent users and edges represent different activities between them. Expand
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A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks
TLDR
We propose a Bayesian nonparametric latent feature model for such data, where the latent features for each actor in the network evolve according to a Markov process, extending recent work on similar models for static networks. Expand
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Revisiting Multiple-Instance Learning Via Embedded Instance Selection
TLDR
We present an empirical study investigating the efficacy of alternative base learners for Multiple-Instance Learning via Embedded Instance Selection (MILES) and compare MILES to other MI algorithms. Expand
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Learning Instance Weights in Multi-Instance Learning
TLDR
This thesis investigates the case where each instance has a weight value determining the level of influence that it has on its bag’s class label. Expand
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