In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

In this paper, a neural network-based stock price prediction and trading system using technical analysis indicators is presented. The model developed first converts the financial time series data into a series of buy-sell-hold trigger signals using the most commonly preferred technical analysis indicators. Then, a Multilayer Perceptron (MLP) artificial neural network (ANN) model is trained in the learning stage on the daily stock prices between 1997 and 2007 for all of the Dow30 stocks. Apache Spark big data framework is used in the training stage. The trained model is then tested with data from 2007 to 2017. The results indicate that by choosing the most appropriate technical indicators, the neural network model can achieve comparable results against the Buy and Hold strategy in most of the cases. Furthermore, fine tuning the technical indicators and/or optimization strategy can enhance the overall trading performance.

Reza Zadeh will be keynoting and speaking at the AI Conference in Beijing, April 10-13, 2018. Hurry--best price ends January 26. A gigantic shift in computing is about to dawn upon us, one that is as significant as only two other moments in computing history. First came the "desktop era" of computing, powered by central processing units (CPUs), followed by the "mobile era" of computing, powered by more power-efficient mobile processors. Now, there is a new computing stack that is moving all of software with it, fueled by artificial intelligence (AI) and chips specifically designed to accommodate its grueling computations.

Over the past few weeks Fortune colleagues and I have written at length about China's rise as an "innovation superpower," particularly in sectors involving the Internet, e-commerce and mobile payment. We've marveled at the scale of China's two largest tech giants, Alibaba Group and Tencent Holdings, and extolled the creativity and convenience of the multitude of the services they offer. Some of you have written to remind us of Beijing's strict censorship of the Internet. Even so, my view remains that China has emerged as the biggest, liveliest and most sophisticated digital marketplace in the world. But I've also expressed unease in this space about the fact that in China's tech sector, even more than in America's, an enormous amount of market power is concentrated in the hands of a few giant firms, with few safeguards for individual privacy.

Apple confirmed a theory many users have had for years: the iPhone gets slower with age. The confirmation comes after Reddit users noticed their devices were getting slower as the batteries in their iPhones got weaker. Apple heads into the new year with some unusually downbeat news: its new iPhone X isn't proving to be quite the sales darling that some of its previous smartphones have been. Shares of Cupertino tech giant were down 3% in early trading Tuesday after several market analysts forecast lower than expected demand for the latest iPhone, with its edge-to-edge screen, face-recognition software and lofty price. Apple could cut its sales forecast for the first quarter of 2018 to 30 million units, down from an initial target of 50 million, according to a report in Taiwan's Economic Daily News cited by Reuters.

Kai-Fu Lee, one of China's best-known technologists and investors, thinks artificial intelligence is about to supplant many millions of the country's office workers. "This replacement is happening now, and it's happening in a true, complete decimation," Lee told a conference at MIT last week. "In my opinion, the white-collar workforce gets challenged first--blue-collar work later." Lee pointed to several of the investments made by his company, Sinovation Ventures, as clear signs of how routine office work is already being transformed by AI. For example, Lee has backed Smart Finance Group, a company that uses machine learning to determine a person's eligibility for a payday loan. Sinovation has also invested in companies that automate customer service, training, and other routine office services.

We've all heard or read about how robots are going to take away our jobs. Saudi Arabia even went as far as granting citizenship to "Sophia the robot" back in October (See the video below). With crytocurrency at the top of daily headlines, 2017 may be remembered as the year artificial intelligence (AI, pronounced AYE-EYE) goes mainstream with more organizations adopting AI than ever. Two weeks ago, we wrote about Professor Geoffrey Hinton, known worldwide as the Godfather of AI, and how his research work in the area of Neuro Net was used in speech recognition and Android voice search. Yes, we've made a lot of progress since AI started as an academic discipline in 1956.

PARACHINAR, Pakistan (Reuters) - A suspected U.S. drone attack along the Pakistani-Afghan border killed an Islamist militant commander and one of his associates on Tuesday, a Pakistani official in the remote area said.

You've eaten all the turkey, the trimmings, and the mince pies, and you're starting to turn your mind to new years resolutions. Rather than the usual resolutions of hitting the gym more, giving up chocolate, or watching less TV how about a resolution to stay ahead of the AI trends of 2018? Throughout 2018 not only are we bringing the RE•WORK AI Summits to new locations such as Hong Kong, Toronto and New York, but we have brand new topics: Deep Learning for Robotics Summit, and AI in Industrial Automation. We will also be hosting stand alone dinners and workshops throughout the year. For one week only we are offering 25% off all RE•WORK events in 2018 using the code NEWYEAR (excluding dinners).

AI-powered concierge service startup, Laiye, received tens of millions of USD for Series B on December 21 to promote its enterprise concierge service, wul.ai. Laiye is an AI-powered concierge service startup that provides enterprise customers with AI-oriented concierge service solutions, and provides individual users with a variety of services including smart calendars, ride hailing, business travel, express delivery, etc. Laiye takes the form of both a service account inside the WeChat messaging app and an individual app for individual users. Its app looks a bit like a messaging app. Once users make specific requests by speaking or texting, such as "get me a coffee" or "book me a flight", then the app will connect to other services to fulfill users' demands. Meanwhile, users can also realize their demands through Laiye's WeChat Official Account, which is like chatting with a person.