Multi-view datasets are increasingly collected in many real-world applications, and we have seen better learning performance by existing multi-view learning methods than by conventional single-view learning methods applied to each view individually. But, most of these multi-view learning methods are built on the assumption that at each instance no view is missing and all data points from all views must be perfectly paired. Hence they cannot handle unpaired data but ignore them completely from their learning process. However, unpaired data can be more abundant in reality than paired ones and simply ignoring all unpaired data incur tremendous waste in resources. In this paper, we focus on learning uncorrelated features by semi-paired subspace learning, motivated by many existing works that show great successes of learning uncorrelated features. Specifically, we propose a generalized uncorrelated multi-view subspace learning framework, which can naturally integrate many proven learning criteria on the semi-paired data. To showcase the flexibility of the framework, we instantiate five new semi-paired models for both unsupervised and semi-supervised learning. We also design a successive alternating approximation (SAA) method to solve the resulting optimization problem and the method can be combined with the powerful Krylov subspace projection technique if needed. Extensive experimental results on multi-view feature extraction and multi-modality classification show that our proposed models perform competitively to or better than the baselines.

Who knows what could possibly be driving this, but post-apocalyptic video games are having a moment. In the past year we've already seen Fallout 76, Anthem and Metro Exodus, while an open beta for Ubisoft's online shooter The Division 2, set in a ruined Washington DC, started on 1 March. Arguably, however, the two most anticipated genre pieces are still to come on PlayStation 4: Days Gone and The Last of Us 2. Both set after most of the population has been wiped out by a pandemic, their different approaches tell us a lot about what it takes to stand out from the shambling, undead crowd. Days Gone, out April 26 from Sony Bend Studios, takes an open-world approach. Set after a virus has turned most of humanity (and a lot of animals) into bloodthirsty monsters, you play as roving bounty hunter and motorcycle fanatic Deacon St John.

LUIS is now generally available in the Australia East, Brazil South, West US 2, South Central US, East US, East Asia, and North Europe regions, in addition to the current availability in the East US 2, West Central US, West US, West Europe, and Southeast Asia regions. General availability (GA) pricing will begin on February 1, 2018. Usage prior to February 1, 2018, will be billed at preview rates.

Transparency Market Research has released a new market report titled Text Analytics Market - Global Industry Analysis, Size, Share, Growth, Trends and Forecast 2016 - 2024. According to this report, the global text analytics market revenue stood at US 2.82 bn in 2015 and is expected to reach US 12.16 bn by 2024, at a CAGR of 17.6% from 2016 to 2024. Text analytics is a method of converting unstructured data into a meaningful form for the analysis of customer feedback, product reviews, sentimental analysis, and entity modeling for supporting fact-based decision making. Several techniques of statistical, linguistic and machine learning are used in text analytics solutions for the retrieval of relevant information from unstructured data. The increasing proliferation of textual data has challenged the ability of organizations across various sectors to summarize and understand them to make better business decisions.