Cascading bandit (CB) is a variant of both the multi-armed bandit (MAB) and the cascade model (CM), where a learning agent aims to maximize the total reward by recommending $K$ out of $L$ items to a user. We focus on a common real-world scenario where the user's preference can change in a piecewise-stationary manner. Two efficient algorithms, \texttt{GLRT-CascadeUCB} and \texttt{GLRT-CascadeKL-UCB}, are developed. The key idea behind the proposed algorithms is incorporating an almost parameter-free change-point detector, the Generalized Likelihood Ratio Test (GLRT), within classical upper confidence bound (UCB) based algorithms. Gap-dependent regret upper bounds of the proposed algorithms are derived and both match the lower bound $\Omega(\sqrt{T})$ up to a poly-logarithmic factor $\sqrt{\log{T}}$ in the number of time steps $T$. We also present numerical experiments on both synthetic and real-world datasets to show that \texttt{GLRT-CascadeUCB} and \texttt{GLRT-CascadeKL-UCB} outperform state-of-the-art algorithms in the literature.

Beyond sharing datasets or simulations, we believe the Recommender Systems (RS) community should share Task Environments. In this work, we propose a high-level logical architecture that will help to reason about the core components of a RS Task Environment, identify the differences between Environments, datasets and simulations; and most importantly, understand what needs to be shared about Environments to achieve reproducible experiments. The work presents itself as valuable initial groundwork, open to discussion and extensions.

It seems like artificial intelligence is taking over the world, leaving many of us non-techies feeling terrified. Yet when you stop to think about it, we all use artificial intelligence (AI) every day. When we Google something, use Siri on our smartphones or ask Alexa a question, we are using AI. Hollywood has certainly featured AI in many movies from "The Terminator" series to "Robocop" and "I, Robot." In "Minority Report," algorithms predict who is going to commit a crime, and the person is arrested before the crime can be committed.

I'm an undergraduate data scientist, about to start work on my dissertation project. I thought I'd create a system that, given someone's career history and education, predicts what job they're likely to get, and at what company. Essentially this is to help focus the efforts of job seekers, and help them get to where they belong. Originally I planned to do this by scraping data from LinkedIn profiles. From the LinkedIn profile, you can obtain information about someone's current job and employer, as well as their career history and education. Therefore you can see what education and career history (the input) resulted in their current job (the output - the thing I'm trying to predict).

One of Google's Home smart speakers is seen above. Q: So, do YOU have an Amazon Echo or Google Home smart speaker in your house? I am freaked out that it's always listening. A: Yes, smart speakers are handy. Yes, they can be fabulous for people with physical challenges.

The term artificial intelligence has been around since 1956; however many people don't truly understand what it means or how it affects their lives on a daily basis. Visions of robot overlords and sentient computers, no doubt the product of science fiction and pop culture, seem to always be attached to AI. But today, AI permeates all manner of things, from spam filters, to personalized recommendations, to voice assistants like Siri, Alexa and Cortana. While AI and machine learning are extraordinarily useful for completing manual tasks faster and more efficiently than human beings, science is always pushing the boundaries of what AI can do. In the business world, large enterprises are under constant pressure to close the gap with customers, to innovate how they engage, and to act with empathy – as a means to develop deeper (and ultimately more valuable) relationships.

Since Siri debuted on the iPhone 4s back in 2011, voice assistants have gone from unworkable gimmick to the basis for smart speaker technology found in one in six American homes. "Before Siri, when I talked about [what I do] there were blank stares," Tom Hebner, head of innovation at Nuance Communications, which develops cutting edge A.I. voice technology, told Digital Trends. "People would say, 'Do you build those horrible phone systems? That was one group of people's only interaction with voice technology." According to eMarketer forecasts, almost 100 million smartphone users will be using voice assistants by 2020.

These startups are applying AI to discover new drugs, remotely monitor patients, securely transfer patient data, and more. Healthcare has become a crucial area for artificial intelligence research and applications. Startups in the space are leveraging AI technology to help individual consumers, clinicians, and hospital systems improve everything from fitness to clinical trials to diagnostics. For example, consumers are adopting virtual assistants to inquire about symptoms and using applications to track fitness metrics. Meanwhile, radiologists are using computer vision to discern between malignant and benign cells, while hospital systems are deploying AI-driven software to analyze the financial risk of individual patients on behalf of insurers.

We cannot deny that this technology has made its place in many people's heart. But still, we will tell you a brief introduction to machine learning. Machine learning or ML usually defines as an application of Artificial Intelligence. It has the ability to make computers predict something automatically. There are two major types of machine learning algorithms.

With smartphones becoming an integral part of everyone's daily use, it is difficult to function without it. The smart features like checking emails, video conferencing, calls, instant messaging, etc. are all making life more comfortable. The business owners can reach out to their employees and clients within a few seconds. Below is the list of 7 significant smartest AI apps for your Android and iOS platforms that will change your lives for the better. ELSA or English Smart Speech Assistant is a popular app used by both Android and iOS users.