Machine Learning has become very famous currently which assist in identifying the patterns from the raw data. Technological advancement has led to substantial improvement in Machine Learning which, thus helping to improve prediction. Current Machine Learning models are based on Classical Theory, which can be replaced by Quantum Theory to improve the effectiveness of the model. In the previous work, we developed binary classifier inspired by Quantum Detection Theory. In this extended abstract, our main goal is to develop multi-class classifier. We generally use the terminology multinomial classification or multi-class classification when we have a classification problem for classifying observations or instances into one of three or more classes.

We introduce a novel Deep Reinforcement Learning (DRL) algorithm called Deep Quality-Value (DQV) Learning. DQV uses temporal-difference learning to train a Value neural network and uses this network for training a second Quality-value network that learns to estimate state-action values. We first test DQV's update rules with Multilayer Perceptrons as function approximators on two classic RL problems, and then extend DQV with the use of Deep Convolutional Neural Networks, `Experience Replay' and `Target Neural Networks' for tackling four games of the Atari Arcade Learning environment. Our results show that DQV learns significantly faster and better than Deep Q-Learning and Double Deep Q-Learning, suggesting that our algorithm can potentially be a better performing synchronous temporal difference algorithm than what is currently present in DRL.

Build accurate DNN models requires training on large labeled, context specific datasets, especially those matching the target scenario. We believe advances in wireless localization, working in unison with cameras, can produce automated annotation of targets on images and videos captured in the wild. Using pedestrian and vehicle detection as examples, we demonstrate the feasibility, benefits, and challenges of an automatic image annotation system. Our work calls for new technical development on passive localization, mobile data analytics, and error-resilient ML models, as well as design issues in user privacy policies.

We introduce an extension to the Protégé ontology editor, which allows for discovering concept definitions, which are not explicitly present in axioms, but are logically implied by an ontology. The plugin supports ontologies formulated in the Description Logic EL, which underpins the OWL 2 EL profile of the Web Ontology Language and despite its limited expressiveness captures most of the biomedical ontologies published on the Web. The developed tool allows to verify whether a concept can be defined using a vocabulary of interest specified by a user. In particular, it allows to decide whether some vocabulary items can be omitted in a formulation of a complex concept. The corresponding definitions are presented to the user and are provided with explanations generated by an ontology reasoner.

Learning to generate fluent natural language from structured data with neural networks has become an common approach for NLG. This problem can be challenging when the form of the structured data varies between examples. This paper presents a survey of several extensions to sequence-to-sequence models to account for the latent content selection process, particularly variants of copy attention and coverage decoding. We further propose a training method based on diverse ensembling to encourage models to learn distinct sentence templates during training. An empirical evaluation of these techniques shows an increase in the quality of generated text across five automated metrics, as well as human evaluation.

MOSCOW – The head of the U.S. space agency said Tuesday that he's sure that investigators will determine the cause of a mysterious hole that appeared on the International Space Station, which his Russian counterpart has said was deliberately drilled. NASA Administrator Jim Bridenstine also said that collaboration with Russia's Roscosmos remains important, despite recent comments by agency head Dmitry Rogozin that Russia wouldn't accept a "second-tier role" in a NASA-led plan to build an outpost near the moon. The hole that appeared in a Russian Soyuz capsule docked to the ISS caused a brief loss of air pressure in August before being patched. The incident sparked wide speculation and consternation. "I strongly believe we're going to get the right answer to what caused the hole on the International Space Station and that together we'll be able to continue our strong collaboration," Bridenstine said.

Last year, Instagram introduced an enhanced comment filter that uses machine learning to spot offensive words and phrases in challenging contexts. Now, the company is expanding similar coverage to photos and captions. Today, it announced that it will use AI to "proactively detect bullying" before sending content to human moderators for review. The new feature will roll out to users in the coming weeks, launching in time for October's National Bullying Prevention Month in the US and just before Anti-Bullying Week in the UK. The same technology is also being added to live videos to filter comments there as well.

Tieto announced today that it is one of the first Nordic companies to join the European AI Alliance, a newly-formed forum for artificial intelligence (AI) stakeholders to come together to push European competitiveness on AI research and development and its impacts on industry and society. The AI Alliance, established by the European Commission, brings together a diverse set of leading AI actors, including companies, consumer organizations, trade unions and other representatives of civil society bodies across Europe to share best practices. The AI Alliance aims to directly contribute to the European debate on AI and impact the Commission's AI policy-making. To achieve that, the AI Alliance works in close collaboration with the High-Level Expert Group on Artificial Intelligence (AI HLEG), a group the Commission has also established, with 52 members from academia, business and civil society such as Bayer, BMW, Bosch, Fraunhofer Institute, Google, IBM, Nokia, Siemens, Telenor and University of Oxford. The AI HLEG advises the Commission on AI's opportunities and challenges, and supports it in the implementation of the European strategy on AI.

An NHS hospital trust has become the first to use AI robots as secretaries in an effort to cut costs. Ipswich Hospital, run by East Suffolk and North Essex NHS Trust, has'employed' three virtual workers to free up staff from'mundane and repetitive tasks', such as submitting scans and blood test results. This is thought to allow real medical secretaries more time to focus on patient care, with the system being eight times more productive than human staff, the trust claims. The system, which is run by a computer, has been in place since July and has saved more than 500 hours of work, according to the trust's deputy director of ICT Darren Atkins. Over the next nine months, the AI programme will save them £220,000, he added.

Tallinn Digital Summit 2018 will host government ministers, entrepreneurs, and innovators from digitally minded countries around the world. The McKinsey Global Institute, the Lisbon Council, the Centre for Public Impact, and the European Centre for International Political Economy are amongst those bodies taking part. AI is a burning issue which requires immediate action, said Estonian Prime Minister Jüri Ratas. "AI will bring major changes in the near future and we cannot leave this to chance," Mr Ratas said. "We need a common legal framework, and guidelines on ethics and technology which would boost development and innovation while ensuring safety and trust. That's why Tallinn Digital Summit will focus on AI and the global free trade of data, as well as their impact on governance, entrepreneurship and society,'' he continued. IT minister Rene Tammist (SDE) added Estonia aims to lead the international discussion on the legal issues surrounding AI. "Everyone who uses Google or Facebook has been exposed to AI.