The present work deals with active sampling of graph nodes representing training data for binary classification. The graph may be given or constructed using similarity measures among nodal features. Leveraging the graph for classification builds on the premise that labels across neighboring nodes are correlated according to a categorical Markov random field (MRF). This model is further relaxed to a Gaussian (G)MRF with labels taking continuous values - an approximation that not only mitigates the combinatorial complexity of the categorical model, but also offers optimal unbiased soft predictors of the unlabeled nodes. The proposed sampling strategy is based on querying the node whose label disclosure is expected to inflict the largest change on the GMRF, and in this sense it is the most informative on average. Such a strategy subsumes several measures of expected model change, including uncertainty sampling, variance minimization, and sampling based on the $\Sigma-$optimality criterion. A simple yet effective heuristic is also introduced for increasing the exploration capabilities of the sampler, and reducing bias of the resultant classifier, by taking into account the confidence on the model label predictions. The novel sampling strategies are based on quantities that are readily available without the need for model retraining, rendering them computationally efficient and scalable to large graphs. Numerical tests using synthetic and real data demonstrate that the proposed methods achieve accuracy that is comparable or superior to the state-of-the-art even at reduced runtime.

Due to increasing urban population and growing number of motor vehicles, traffic congestion is becoming a major problem of the 21st century. One of the main reasons behind traffic congestion is accidents which can not only result in casualties and losses for the participants, but also in wasted and lost time for the others that are stuck behind the wheels. Early detection of an accident can save lives, provides quicker road openings, hence decreases wasted time and resources, and increases efficiency. In this study, we propose a preliminary real-time autonomous accident-detection system based on computational intelligence techniques. Istanbul City traffic-flow data for the year 2015 from various sensor locations are populated using big data processing methodologies. The extracted features are then fed into a nearest neighbor model, a regression tree, and a feed-forward neural network model. For the output, the possibility of an occurrence of an accident is predicted. The results indicate that even though the number of false alarms dominates the real accident cases, the system can still provide useful information that can be used for status verification and early reaction to possible accidents.

WASHINGTON – U.S.-European cooperation on economic issues is at a low ebb. Efforts to rekindle interest in mutually advantageous policies such as the revival of the Transatlantic Trade and Investment Partnership are not likely to succeed for the time being. Under the prevailing circumstances, trans-Atlantic disillusionment has settled in. A better approach than letting mutual acrimony languish would be to focus on a joint challenge -- how to meet the resolute Chinese challenge to the industrial economies of the West. Chinese President Xi Jinping's growing consolidation of power is giving ever more momentum to the ambitious Chinese plan to gain dominance of high-tech industries.

Kuri will arrive in our homes early in the New Year. The chirruping 50 cm high robot can trundle around entertaining your kids, take photographs when it thinks you are doing something interesting, wake you up in the morning and greet you at the front door. The makers of Kuri, an American start up backed by Bosch, believe that robots like this, and jibo, a similar product, are the future we will all live in. Artificially intelligent household robots, they are betting, will perform more and more of the mundane tasks in our households. Within a relatively short time they will also become increasingly sophisticated and smarter, serving us and our children in all sorts of ways, understanding our needs and making life easier.

MUMBAI: Corporate thought-leader and Infosys co-founder NR Narayana Murthy has flayed the high wage hikes that senior managements have been apportioning to themselves when the software industry is in trying times and has advised them to make "sacrifices" to maintain common man's faith in capitalism. Conceding that times are difficult for the IT services sector, Murthy dismissed the commonly attributed threats of artificial intelligence and automation as "more hype than reality". Terming the trend of no hikes for juniors and freshers as "worrisome," Murthy rued that the senior level people have been taking handsome hikes. "I think that is not the way to make capitalism acceptable to the larger masses in a country that has huge poverty," he said, speaking at the IIT-Bombay over the weekend. "If we believe in capitalism, if we believe that is the best solution for the country to move forward, then the leaders of capitalism will have to demonstrate self-restraints in apportioning to themselves the part of the benefits that come out of running companies, Murthy, who mostly flies the economy class, added. Murthy, a strong proponent of "compassionate capitalism" since his days in the company, did not make any reference to Infosys. It can be noted that over the past few months, Murthy had gone public with his displeasure over senior executive compensation at Infosys. Speaking before the students at the prestigious institute, Murthy said in the last seven years, the salaries of freshers in the software industry have stayed stagnant while the same for senior-level employees have grown by up to 1,000 per cent. "If all of us make sacrifices, then the youngsters will understand," he said. He said the IT sector is passing through a trough that is cyclical in nature and may occur once a few years. One of the reasons for this is the investments in IT done by the developed world clients in the past, he said, adding they are waiting to reap the benefits of the same before starting to invest again. However, change in the technological landscape where automation and artificial intelligence are said to be making deeper in-roads was dismissed by him. "There is this whole thing about automation and artificial intelligence.

MUMBAI: Amid a raging global debate on the consequences of artificial intelligence (AI), India has formed a "policy group" to study the new technologies and recommend a framework for its adoption, IT industry body Nasscom said today. "We all are currently working out on a policy framework on AI," its vice president K S Viswanathan told PTI, when asked about concerns over AI or the intelligence exhibited by machines. He said a "policy group" has been created by the Ministry of Electronics and Information Technology with representation from the academia, which has done a lot of research on the subject, and Nasscom for the industry's perspective. The group will focus on aspects like skilling the workforce, privacy, security and fixing responsibility if anything goes wrong, Viswanathan said. "We have to create a thought leadership on what is this programme all about, what is the likely impact. Create a thought leadership when AI becomes a reality, what are the elements and sub-elements which need to be taken care of, how do we take care of that," he said.

The publisher of Kojien, the most authoritative dictionary in Japan, has been stuck between a rock and a hard place over its definition of Taiwan as a province of China, prompting a request for a correction from the self-ruled island. Since its first publication in 1955, the dictionary has become a household name. The media and other organizations often use it to get the final say on a word's meaning. The seventh edition is slated to be released next month. On Friday, Iwanami Shoten, the publisher, said Kojien's entry on Taiwan is in line with the 1972 Japan-China Joint Communique, in which Japan recognized the People's Republic of China as the sole legal government of China and "fully understands and respects" the PRC's stance that Taiwan is an inalienable part of its territory.

Asset managers need all the help they can get. The number of products the company is carrying is growing. The number of clients being farmed out to managers is growing. Clients are demanding better personalized service from their wealth managers. When combined with volatile market dynamics that is understating the complexity of a connected global economy, you start to feel a little bit more sympathy for your wealth manager's position.

India's largest homegrown e-commerce giant, Flipkart, is making a big push for artificial intelligence (AI). A new unit, AI For India, will use AI technologies to mine the consumer data that Flipkart has gathered over the last decade to strengthen its business offerings, a company blog post said on Dec. 21. Flipkart will invest "hundreds of millions of dollars" in AI For India over the next few years, co-founder and group chairman Sachin Bansal told the Mint newspaper. The new unit will be headed by Flipkart's chief data scientist Mayur Datar. Bansal, along with CEO Kalyan Krishnamurthy, will directly work on some key projects.