Title:  Stochastic Three Points Method For Unconstrained Smooth Minimization

Date and Place: 9th April 2021 15:00 – link

Speaker: Dr El Hourcine Bergou (INRAE)

Abstract: 

In this work, we consider the unconstrained minimization problem of a smooth function in a setting where only function evaluations are possible. We design a novel randomized derivative-free algorithm—the stochastic three points (STP) method—and analyze its iteration complexity. At each iteration, STP generates a random search direction according to a certain fixed probability law. Our assumptions on this law are very mild: roughly speaking, all laws which do not concentrate all measure on any halfspace passing through the origin will work. Although, our approach is designed to not explicitly use derivatives, it covers some first order methods. For instance, if the probability law is chosen to be the Dirac distribution concentrated on the sign of the gradient, then STP recovers the Signed Gradient Descent method. If the probability law is the uniform distribution on the coordinates of the gradient, then STP recovers the Randomized Coordinate Descent Method.
The complexity of STP depends on the probability law via a simple characteristic closely related to the cosine measure which is used in the analysis of deterministic direct search (DDS) methods. Unlike in DDS, where $O(n)$ ($n$ is the dimension of the problem) function evaluations must be performed in each iteration in the worst case, our method only requires two new function evaluations per iteration. Consequently, while the complexity of DDS depends quadratically on $n$, our method depends linearly on $n$.

Biography:

Dr l Hourcine Bergou is a research scientist at INRAE. My research interests are in all areas that intersect with optimization, including algorithms, machine learning, statistics, and operations research. I am particularly interested in algorithms for large scale optimization including randomized and distributed optimization methods.

Title:  Molecular Communications using Astrocytes for Boolean logic gates implementation in mammalian cells

Date and Place: 1st April 2021 14:00 – link

Speaker: Dr Michael Barros (University of Essex, UK)

Abstract: 

In this talk we will show the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of Ca2+ ion fows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling Ca2+ signals that fow through the population. A reinforced learning platform is also presented in the paper to optimize the Ca2+ activated level and time slot of input signals Tb into the gate. This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the efectiveness of the reinforced learning platform, a Ca2+ signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the Ca2+ activated level and time slot of input signals Tb is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural–Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants.

Biography:

Dr Barros is an Assistant Professor (Lecturer) since June 2020 in the School of Computer Science and Electronic Engineering at the University of Essex, UK. He is also a MSCA-IF Research Fellow (part-time) at the Tampere University, Finland. He received the PhD in Computer Science at the Waterford Institute of Technology in 2016. He previously held multiple academic positions as a Research Fellow in the Waterford Institute of Technology, Ireland.
He has over 70 research peer-reviewed scientific publications in top journals and conferences such as Nature Scientific Reports, IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, in the areas of molecular and unconventional communications, biomedical engineering, bionano science and 6G. Since 2020, he is a review editor for the Frontiers in Communications and Networks journal in the area of unconventional communications. He also served as guest editor for the IEEE Transactions on Molecular, Biological and Multi-Scale Communications and Digital Communications Networks journals. He received the CONNECT Prof. Tom Brazil Excellence in Research Award in 2020. Dr Barros was awarded also the Irish Research Council’s (IRC) Government of Ireland Post-doc Fellow from 2016-2018 and the Enterprise Ireland’s (EI) Commercialization Funding from 2018-2019.

Title: Construction and properties of certain real multi-angle tight frames

Date and Place: 18th February 2021 14:00 – link

Speaker: Prof. Somantika Datta (Univ. Idaho, USA)

Abstract: 

Frames are now standard tools in signal processing, and have applications ranging from compressed sensing, to communication systems and quantum sensing. Designing frames with some special structure such as equiangularity and tightness is highly desirable in applications. However, constructing equiangular tight frames (ETFs) with a given size in a specific dimension can be difficult or impossible in some cases. This leads one to consider the construction of frames with few distinct angles among pairs of frame vectors. In the special case of d+1 vectors in a d-dimensional space, it is well known that the vertices of a regular simplex will give an ETF. Using this, we will show a specific construction which, for a given dimension d and integer 1 < k ≤ d, gives a real unit norm tight frame such that the number of distinct angles among the vectors is bounded above by k. We will present several properties of this multi-angle tight frame. We also show how one can strategically choose subsets of such a multi-angle tight frame that will be equiangular or orthogonal. This property is meaningful in the context of erasures. We will also discuss a connection between certain unit norm tight frames with three angles and adjacency matrices of regular graphs.

Biography:

Somantika Datta is an associate professor of mathematics at the University of Idaho. She received a Ph.D. in mathematics from the University of Maryland, College Park. This was followed by postdoctoral positions at Arizona State University and Princeton University. Her research interests lie in the area of applied harmonic analysis with focus on frame theory and applications in signal processing.

Title: Quantum Communications over Noisy Entanglement

Date and Place: 11th February 2021 14:00 – link

Speaker: Dr Daryus Chandra (University of Southampton, UK)

Abstract: 

Within the Quantum Internet framework, multiple quantum devices are interconnected via pre-shared maximally-entangled quantum states for enabling various applications, including the on-demand classical and quantum communication. Hence, the pre-shared entanglement, which is constituted by the EPR pair, can be viewed as the primary consumable resources within the Quantum Internet. However, the generation and the distribution of the EPR pairs are subject to quantum decoherence imposed by the quantum channels, which will manifest as quantum errors. Similar to the classical domain, the quantum errors imposed by the quantum channels can be mitigated using quantum error-correction codes. In this talk, we will explore two approaches for achieving reliable quantum communication over noisy entanglement by incorporating quantum error-correction codes. More specifically, the first approach is constituted by the consecutive steps of quantum entanglement distillation followed by quantum teleportation, while the second approach can be viewed as the direct quantum communication over noisy entanglement. We will also discuss the pros and the cons of each approach while examining their compatibilities for a broader range of applications for the Quantum Internet framework.

Biography:

Daryus Chandra is a research fellow at the Next-Generation Wireless Research Group, School of Electronics and Computer Science, University of Southampton, UK. He received the B.Eng. and M.Eng. degree from the Department of Electrical Engineering and Information Technology, Universitas Gadjah Mada, Indonesia, in 2013 and 2014, respectively. He obtained his PhD with the Next-Generation Wireless Research Group, School of Electronics and Computer Science, University of Southampton, UK, in 2020. He returned to Southampton in 2021 after completing a one-year postdoctoral research fellowship at Quantum Internet Research Group, University of Naples Federico II, Italy.

Title: Self trigger co-design using LASSO regression

Date and Place: 17th December 2020 14:00 – link

Speaker: Lucien Etienne (IMT Lille-Douai)

Abstract: 

Networked systems have become more and more pervasive in many modern industrial application. A good justification for their deployment is that they can be cheaper/faster to set in place as well are scalable while also enabling lower maintenance cost. In the past decade a new paradigm has been developed where the controller is not sampled periodically (i.e. with a time–triggered policy), but rather sampled when some condition has been met (Usually a stability or performance criterion being violated). After recalling some general element on classical control scheme ( Linear Quadratic regulator and model predictive control) In this talk, the control of a linear time invariant system with self triggered sampling is considered .
In order to address the controller computation and the future sampling schedule a sparse optimization problem will be considered. A relaxation of the optimal self triggered control can be formulated as a LASSO regression. Using the properties of the solution of the Lasso regression it is shown how to obtain a controller ensuring practical or asymptotic stability while reducing sampling of the control action.

Biography:

Dr. Lucien Etienne received a M.Sc. Degree in applied mathematics at the INSA Rouen in 2012 and a joint Ph.D. in automatic control from the university of L’aquila and the university of Cergy-Pontoise in 2016. From 2016 to 2017 he was a post doctoral researcher at Inria Lille-Nord Europe. Since 2017 He is an associate professor at Institut Mines-Télécom Lille Douai. His research interests include switched and hybrid systems, observer synthesis and sampled data systems.