Indoor localization approaches offer solutions for detecting locations in areas where technologies such as GPS (which are successful in outdoor environments) are inadequate. In this seminar, different approaches used in indoor localization, solutions proposed using the fingerprinting technique, innovations and future trends will be discussed. The main topics to be examined include solutions based on the use of singular and hybrid technologies, the use of filters in the pre-processing stages, design of deep architectures in the classification stage, and dual band WiFi based strategies.
Dr. Mateusz Nowak, Software Architect at Intel (and our former colleague) will talk about his work at Intel as a "software first" company. He will focus on oneAPI - open source products for high performance computing and AI, with special attention to the Distributed Ranges project, in which he is personally involved. He will also share his thoughts on collaboration between academia and industry, and his personal experience of moving from a small research institute to the corporate world (and why it was less challenging than expected).
In this talk, we shortly introduce the emerging field quantum software (quantum programming and quantum machine learning), and then we discuss how we can be involved and then shape the field. We explain why education is our primary focus and how we can use pedagogical tools to attract new generation and people to the field. We share our own experiences, our ongoing projects, and also our upcoming projects. At the end, we discuss possible collaborations.
The central limit theorem (CLT) and the law of the iterated logarithm (LIL) are, along the strong law of large numbers (SLLN), the most common limit theorems. Some well-known results concerning limit theorems, obtained mainly due to the martingale method, are gathered in [1]. Although the asymptotic behaviour of stationary and ergodic Markov chains is already well investigated, limit theorems for a wider class of Markov processes are still the subject of research. Together with D. Czapla and K.
We present a link between the combinatorial notion of orthogonal arrays and k-uniform states, i.e., multipartite pure states such that every reduction to k parties is maximally mixed. As consequence, simple constructions of 1 and 2 uniform states for homogeneous (N qudits) and heterogeneous systems (e.g. N qubits + M qutrits) are derived.
Classical methods for processing and analysis of multidimensional signals – such as color videos and hyperspectral images – do not exploit full information contained in inner their factors. On the other hand, recently developed tensor based methods allow for data representation and analysis which directly account for data multidimensionality. Examples can be found in many applications such as face recognition, image synthesis, video analysis, surveillance systems, sensor networks, data stream analysis, marketing and medical data analysis, to name a few.
Quantum walks are quantum counterparts of classical random walks.
They have been useful for designing quantum algorithms that outperform their classical versions for a variety of search problems.
Most of the results, however, consider a search space containing a single marked element only.
We show that if the search space contains more than one marked element the quantum speed-up may disappear.
Rafal Demkowicz-Dobrzański, Uniwersytet Warszawski
Date:
07/12/2016 - 12:15
Abstract:
In atomic clocks, the frequency of a local oscillator is stabilized based on the feedback signal obtained by periodically interrogating an atomic reference system...
