Second, GRAB blocks (Figa priorioruseasequential fixed. Thefirsttwo terms,logdet ( ) trace (S ), in Eq (3) correspondtologP(X| ), thelog-likelihoodof GGM givenaparticularparameter (i.e., anestimateof 1), asdescribedin Section 2.1.

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Unfortunately, the notion is seriously flawed on two counts [8]. First, it doesn't ensure fairness.

This paper presents Generalized Correspondence-LDA (GC-LDA), a generalization of the Correspondence-LDA model that allows for variable spatial representations to be associated with topics, and increased flexibility in terms of the strength of the correspondence between data types induced by the model. We present three variants of GC-LDA, each of which associates topics with a different spatial representation, and apply them to a corpus of neuroimaging data. In the context of this dataset, each topic corresponds to a functional brain region, where the region's spatial extent is captured by a probability distribution over neural activity, and the region's cognitive function is captured by a probability distribution over linguistic terms. We illustrate the qualitative improvements offered by GC-LDA in terms of the types of topics extracted with alternative spatial representations, as well as the model's ability to incorporate a-priori knowledge from the neuroimaging literature. We furthermore demonstrate that the novel features of GC-LDA improve predictions for missing data.

The recursive teaching dimension (RTD) of a concept class C {0,1}n, introduced by Zilles et al. [ZLHZ11], is a complexity parameter measured by the worst-case number of labeled examples needed to learn any target concept of C in the recursive teaching model. In this paper, we study the quantitative relation between RTD and the well-known learning complexity measure VC dimension (VCD), and improve the best known upper and (worst-case) lower bounds on the recursive teaching dimension with respect to the VC dimension. Given a concept class C {0,1}n with VCD(C) = d, we first show that RTD(C) is at most d 2d+1. This is the first upper bound for RTD(C)that depends only on VCD(C), independent of the size of the concept class |C| and its domain size n. Before our work, the best known upper bound for RTD(C) is O(d2d loglog|C|), obtained by Moran et al. [MSWY15].

Generative state estimators based on probabilistic filters and smoothers are one of the most popular classes of state estimators for robots and autonomous vehicles.

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Air strikes have targeted the headquarters of the Iran-aligned Popular Mobilisation Forces (PMF) in Iraq's capital, Baghdad, as the country becomes a two-way battlefield between armed factions and the United States during its war with Iran . The US carried out strikes against the Shia paramilitary umbrella group, also known locally as Hashed al-Shaabi, late on Sunday after attacks on a US diplomatic and logistics centre at Baghdad International Airport. The attack was carried out after Iraqi security officials said four explosions were heard near Camp Victory, a US logistics centre at the capital's main airport. Al Jazeera's Assed Baig, reporting from Baghdad, said some drones "breached air defences and caused damage, more symbolic damage than anything else". "At the same time, Iraqi security forces have set up checkpoints around Baghdad to try and stop these drone strikes because some of these factions are launching drones from the vicinity of Baghdad," he said.

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