Highlights of SYSU-CITW


Welcome to Sun Yat-sen University Coding and Information Theory Workshop (SYSU-CITW)

The Sun Yat-sen University Coding and Information Theory Workshop (SYSU-CITW) will take place in Sun Yat-sen University higher education megacenter campus on November 30, 2018, the day after ITW2018.

SYSU-CITW invites outstanding theorists in the fields of coding and information theory from the world to deliver talks and share their thoughts. All participants are also welcome to join the tour to the National Supercomputer Center in Guangzhou, where places the fastest supercomputer in the world during 2013 ~ 2016, Tianhe-II. The agenda of SYSU-CITW is available here.

Admission is free for SYSU-CITW. Shuttle buses will be arranged on the day picking up our participants from Sun Yat-sen Kaifeng Hotel to the workshop venue. More information can be found here.

SYSU-CITW provides a free and perfect chance for researchers around the world to communicate with each other, especially for those participants who are still hungry for knowledge after a 5-days brainstorming in ITW2018.

We look forward to welcoming you in Sun Yat-sen University, Guangzhou, China.


The general co-chairs,
Xiao Ma and Li Chen


Agenda


Time Titles Speakers Moderators
07:45-08:00 Gathering at the lobby of Sun Yat-sen Hotel, shuttle buses to SYSU depart at 8am*
08:45-09:00 Opening ceremony De-Pei Qian Xiao Ma
09:00-10:00 Channel Capacity from Waves to Particles Richard Blahut
10:00-10:20 Coffee break
10:20-11:10 Coded Caching Schemes with Reduced Subpacketization from Linear Block Codes Aditya Ramamoorthy Xiao Ma
11:10-12:00 Recent Advances in Cache-aided Wireless Networks Aylin Yener
12:00-13:20 Lunch*
13:20-14:00 A tour to the National Supercomputer Center/Group photo
14:00-14:50 Stopping Set Distributions of Linear Codes Fang-Wei Fu Li Chen
14:50-15:40 Information and Uncertainty in Learning Meir Feder
15:40-16:00 Coffee break
16:00-16:50 Graphical Models for Quantum Information Processing Pascal Vontobel Li Chen
16:50-17:40 On (Reliability, Latency, Rate) Tradeoffs for Downlink Wireless Systems Daniela Tuninetti
17:40-18:00 Gathering in front of the National Supercomputer Center, SYSU, shuttle buses to Sun Yat-sen Hotel depart at 6pm

*Ticket is needed. The shuttle buses and the lunches are for registrants only. Registrants can find their tickets in their ITW2018 bags.



Talks's Abstracts and Speakers' Biographies

Channel Capacity from Waves to Particles

The bandlimited channel capacity for the passband additive gaussian noise channel with signal power S, noise power N, and bandwidth B is given by the well known Shannon capacity formula. This fundamental information-theoretic ... (Read More >>)

The bandlimited channel capacity for the passband additive gaussian noise channel with signal power S, noise power N, and bandwidth B is given by the well known Shannon capacity formula. This fundamental information-theoretic expression for the bandlimited capacity leads to the conclusion that reliable communication in additive white gaussian noise with a power density spectrum N_0 is possible only if the ratio of bit energy to noise density is larger than -1.6dB. This statement is complete from the point of view of the mathematics, but fails to account for the physics of lightwaves, which asserts that light appears granular at low power levels. We will describe how the Shannon capacity formula morphs into the channel capacity of a photon particle channel. The conclusion unifies the capacity for the wave model and the particle model of light. (Read Less <<)


Richard Blahut

University of Illinois at Champaign-Urbana, USA

Richard E. Blahut is the Emeritus Henrik Magnuski Professor and former Head of Electrical and Computer Engineering at the University of Illinois, and an Adjunct Professor of Electrical and Systems Engineering at the University of Pennsylvania. He is an IBM Emeritus Fellow, a Fellow of the IEEE, and a member of the US National Academy of Engineering. He is a recipient of the Information Theory Society Claude Shannon Award and the IEEE Alexander Graham Bell Medal. He is the author of ten textbooks in the general area of informatics.



Coded Caching Schemes with Reduced Subpacketization from Linear Block Codes

Coded caching is a technique that generalizes conventional caching and promises significant reductions in traffic over caching networks. However, the basic coded caching scheme requires that each file hosted in the server be ... (Read More >>)

Coded caching is a technique that generalizes conventional caching and promises significant reductions in traffic over caching networks. However, the basic coded caching scheme requires that each file hosted in the server be partitioned into a large number (i.e., the subpacketization level) of non-overlapping subfiles. From a practical perspective, this is problematic as it means that prior schemes are only applicable when the size of the files is extremely large. In this work, we propose coded caching schemes based on combinatorial structures called resolvable designs. These structures can be obtained in a natural manner from linear block codes whose generator matrices possess certain rank properties. We obtain several schemes with subpacketization levels substantially lower than the basic scheme at the cost of an increased rate. Depending on the system parameters, our approach allows us to operate at various points on the subpacketization level vs. rate tradeoff. (Read Less <<)


Aditya Ramamoorthy

Iowa State University, USA

Aditya Ramamoorthy is a Professor of Electrical and Computer Engineering and (by courtesy) of Mathematics at Iowa State University. He received his B. Tech. degree in Electrical Engineering from the Indian Institute of Technology, Delhi in 1999 and the M.S. and Ph.D. degrees from the University of California, Los Angeles (UCLA) in 2002 and 2005 respectively. He was a systems engineer at Biomorphic VLSI Inc. till 2001. From 2005 to 2006 he was with the data storage signal processing group at Marvell Semiconductor Inc. His research interests are ... (Read More >>)

Aditya Ramamoorthy is a Professor of Electrical and Computer Engineering and (by courtesy) of Mathematics at Iowa State University. He received his B. Tech. degree in Electrical Engineering from the Indian Institute of Technology, Delhi in 1999 and the M.S. and Ph.D. degrees from the University of California, Los Angeles (UCLA) in 2002 and 2005 respectively. He was a systems engineer at Biomorphic VLSI Inc. till 2001. From 2005 to 2006 he was with the data storage signal processing group at Marvell Semiconductor Inc. His research interests are in the areas of network information theory, channel coding and signal processing for bioinformatics and nanotechnology. Dr, Ramamoorthy served as an editor for the IEEE Transactions on Communications from 2011 - 2015. He is currently serving as an associate editor for the IEEE Transactions on Information Theory. He is the recipient of the 2012 Iowa State University's Early Career Engineering Faculty Research Award, the 2012 NSF CAREER award, and the Harpole-Pentair professorship in 2009 and 2010. (Read Less <<)



Recent Advances in Cache-aided Wireless Networks

This talk overviews some of the recent advances in cache aided next generation wireless communication networks. The focus will be on coded caching, a recently introduced paradigm that aims to design transmission strategies that ... (Read More >>)

This talk overviews some of the recent advances in cache aided next generation wireless communication networks. The focus will be on coded caching, a recently introduced paradigm that aims to design transmission strategies that simultaneously benefit multiple nodes along with the design of their cache contents. Specifically, we will present results that emphasize the benefits of cache-aided networking in scenarios when (i) the nodes are of differing capabilities, (ii) intermediate nodes can assist with the cache memories, and (iii) information theoretic security is needed in addition to reliability. (Read Less <<)


Aylin Yener

Pennsylvania State University, USA

Aylin Yener is a professor of Electrical Engineering at The Pennsylvania State University since 2010, and a Dean's fellow since 2017. She joined Penn State's faculty as an assistant professor in 2002, and was an associate professor 2006-2010. She was a visiting professor of Electrical Engineering at Stanford University in 2016-2018 and a visiting associate professor in the same department in 2008-2009. ... (Read More >>)

Aylin Yener is a professor of Electrical Engineering at The Pennsylvania State University since 2010, and a Dean's fellow since 2017. She joined Penn State's faculty as an assistant professor in 2002, and was an associate professor 2006-2010. She was a visiting professor of Electrical Engineering at Stanford University in 2016-2018 and a visiting associate professor in the same department in 2008-2009.
She received the B.Sc. degree in electrical and electronics engineering, and the B.Sc. degree in physics, from Bogazici University, Istanbul, Turkey; and the M.S. and Ph.D. degrees in electrical and computer engineering from Wireless Information Network Laboratory (WINLAB), Rutgers University, New Brunswick, NJ. Yener's recognitions include the National Science Foundation CAREER award in 2003, 2014 IEEE Marconi paper award and 2018 WICE Outstanding Achievement Award. She is a distinguished lecturer for the IEEE Vehicular Technology Society and the Communications Society. She is a fellow of the IEEE.
Yener's research interests are in fundamental performance limits of networked systems, communications and information theory with applications to information theoretic physical layer security, energy harvesting communication networks, and caching systems.
Yener's service to IEEE includes having served as a technical program chair of various symposia for the IEEE Communication Society, an associate editor for the IEEE Transactions on Communications, an associate editor and an editorial advisory board member for the IEEE Transactions on Wireless Communications, and a senior editor for the Journal on Selected Areas in Communications. She is a member of the IEEE fellows committee.
Her service to IEEE Information Theory Society includes having served as the student committee chair, the treasurer, the information theory school committee chair, and a member of the Board of Governors. She is currently the second vice president of the IEEE Information Theory Society. (Read Less <<)



Stopping Set Distributions of Linear Codes

Stopping sets and stopping set distribution of a linear code are used to determine the performance of this code under iterative decoding over a binary erasure channel. We study stopping sets, stopping set distributions and BEC-optimal ... (Read More >>)

Stopping sets and stopping set distribution of a linear code are used to determine the performance of this code under iterative decoding over a binary erasure channel. We study stopping sets, stopping set distributions and BEC-optimal parity-check matrices of linear codes. We survey and present some new results on the stopping sets of linear codes, algebraic geometry codes and LDPC codes. We obtain the BEC-optimal parity-check matrices and then determine the stopping set distributions for the Simplex codes, the Hamming codes, the first order Reed-Muller codes, and the extended Hamming codes. Finally, we present some open and further research problems on the stopping sets of linear codes. (Read Less <<)


Fang-Wei Fu

Nankai University, China

Fang-Wei Fu received the B. S. degree in mathematics, the M. S. degree, and the Ph.D. degree in applied mathematics from Nankai University, Tianjin, China, in 1984, 1987 and 1990, respectively.
Since April 2007, he has been with the Chern Institute of Mathematics, Nankai University, Tianjin, China, where he is a Professor. From June 1987 to April 2007, he was with the School of Mathematical Science, Nankai University, Tianjin, China, and became a Professor there in 1995. From February 2002 to March 2007, he was ... (Read More >>)

Fang-Wei Fu received the B. S. degree in mathematics, the M. S. degree, and the Ph.D. degree in applied mathematics from Nankai University, Tianjin, China, in 1984, 1987 and 1990, respectively.
Since April 2007, he has been with the Chern Institute of Mathematics, Nankai University, Tianjin, China, where he is a Professor. From June 1987 to April 2007, he was with the School of Mathematical Science, Nankai University, Tianjin, China, and became a Professor there in 1995. From February 2002 to March 2007, he was a Research Scientist with the Temasek Laboratories, National University of Singapore, Republic of Singapore. From November 1989 to November 1990, he visited the Department of Mathematics, University of Bielefeld, Germany. From October 1996 to October 1997, he visited the Institute for Experimental Mathematics, University of Essen, Germany. From October 1998 to January 1999, from July 1999 to October 1999, from April 2000 to October 2000, and from July 2001 to February 2002, he visited the Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong. He visited the Department of Mathematics, University of California, Irvine, USA, one month in April 2013. His current research interests include coding theory, cryptography, and information theory. (Read Less <<)



Information and Uncertainty in Learning

An information theoretical approach to learning is presented based following the universal prediction/universal coding paradigms developed in the 90's.
This approach leads learning schemes that ... (Read More >>)

An information theoretical approach to learning is presented based following the universal prediction/universal coding paradigms developed in the 90's.
This approach leads learning schemes that are more stable and have precise optimality criteria, as compared to the standard approach based on empirical risk minimization (ERM) and the stochastic gradient (SGD). The comparison and advantages are shown on a variety on learning situation including on one hand basic linear regression and on the other hand deep neural networks (DNN).
Yet, one of the main strengths of this approach is a measure of learnability or uncertainty in the predictive power of learning.
We provide an information theoretic learnability measure, that depends on the specific training examples and the specific test features. We demonstrate how this measure let the learner know when it does not know.
The main results presented are for supervised learning. Towards the end of the talk we will also discuss unsupervised learning, active learning and model class selection and analysis problems. (Read Less <<)


Meir Feder

Tel-Aviv University, Israel

Meir Feder is a Chaired Professor (Information Theory Chair) at the School of Electrical Engineering, Tel-Aviv University. An internationally recognized authority in signal processing, communication and information theory, Professor Feder holds Sc.D. degree from the Massachusetts Institute of Technology (MIT) was a visiting Professor in MIT, and had visiting positions at Bell laboratories and Scripps Institute of Oceanography. He is an IEEE Fellow, and received several academic awards including the IEEE Information Theory society best paper award. ... (Read More >>)

Meir Feder is a Chaired Professor (Information Theory Chair) at the School of Electrical Engineering, Tel-Aviv University. An internationally recognized authority in signal processing, communication and information theory, Professor Feder holds Sc.D. degree from the Massachusetts Institute of Technology (MIT) was a visiting Professor in MIT, and had visiting positions at Bell laboratories and Scripps Institute of Oceanography. He is an IEEE Fellow, and received several academic awards including the IEEE Information Theory society best paper award.
During his academic career, Prof. Feder was closely involved in the high-tech industry with numerous companies, including working with Intel on the MMX architecture and designing efficient multimedia algorithms for it. In 1998 he co-founded Peach Networks, a provider of server-based interactive TV system via the cable network, acquired in 2000 by Microsoft. He then co-founded Bandwiz, a provider of massive content delivery systems for enterprise networks. In 2004 he co-founded Amimon, a leading provider of low latency, perfect quality wireless high-definition A/V connectivity for consumer and professional market. This year he cofounded Run.Ai, to enable efficient, highly distributed, deep learning solution in the cloud. (Read Less <<)



Graphical Models for Quantum Information Processing

Graphical models have proven very useful for classical information processing. For example, some of the best performing channel coding schemes are based on factor graphs and suitable message-passing iterative decoding algorithms operating ... (Read More >>)

Graphical models have proven very useful for classical information processing. For example, some of the best performing channel coding schemes are based on factor graphs and suitable message-passing iterative decoding algorithms operating on them. In this presentation, we discuss graphical models that are suitable for tasks in quantum information processing. Importantly, these graphical models are compatible with graphical models used in classical information processing.
(Based on joint work with Michael Cao, July Li, and Andi Loeliger.) (Read Less <<)


Pascal Vontobel

Chinese University of Hong Kong, Hong Kong SAR, China

Pascal O. Vontobel received the Diploma degree in electrical engineering in 1997, the Post-Diploma degree in information techniques in 2002, and the Ph.D. degree in electrical engineering in 2003, all from ETH Zurich, Switzerland.
From 1997 to 2002 he was a research and teaching assistant at the Signal and Information Processing Laboratory at ETH Zurich, from 2006 to 2013 he was a research scientist with the Information Theory Research Group at Hewlett-Packard Laboratories in Palo Alto, CA, USA, and since 2014 he has been an ... (Read More >>)

Pascal O. Vontobel received the Diploma degree in electrical engineering in 1997, the Post-Diploma degree in information techniques in 2002, and the Ph.D. degree in electrical engineering in 2003, all from ETH Zurich, Switzerland.
From 1997 to 2002 he was a research and teaching assistant at the Signal and Information Processing Laboratory at ETH Zurich, from 2006 to 2013 he was a research scientist with the Information Theory Research Group at Hewlett-Packard Laboratories in Palo Alto, CA, USA, and since 2014 he has been an Associate Professor at the Department of Information Engineering at the Chinese University of Hong Kong. Besides this, he was a postdoctoral research associate at the University of Illinois at Urbana-Champaign (2002-2004), a visiting assistant professor at the University of Wisconsin-Madison (2004-2005), a postdoctoral research associate at the Massachusetts Institute of Technology (2006), and a visiting scholar at Stanford University (2014). His research interests lie in information and coding theory, quantum information processing, data science, communications, and signal processing.
Dr. Vontobel has been an Associate Editor for the IEEE Transactions on Information Theory (2009-2012), an Awards Committee Member of the IEEE Information Theory Society (2013-2014), a Distinguished Lecturer of the IEEE Information Theory Society (2014-2015), and an Associate Editor for the IEEE Transactions on Communications. Moreover, he has been a TPC co-chair of the 2016 IEEE International Symposium on Information Theory, the 2018 IEICE International Symposium on Information Theory and its Applications, and the 2018 IEEE Information Theory Workshop, along with co-organizing several topical workshops and being on the technical program committees of many international conferences. Moreover, he has been three times a plenary speaker at international information and coding theory conferences and has been awarded the ETH medal for his Ph.D. dissertation. (Read Less <<)



On (Reliability, Latency, Rate) Tradeoffs for Downlink Wireless Systems

Delay in wireless networks is intertwined with reliability (the probability with which one achieves communication goals) and rate (the amount of data per unit time communicated). Motivated by ... (Read More >>)

Delay in wireless networks is intertwined with reliability (the probability with which one achieves communication goals) and rate (the amount of data per unit time communicated). Motivated by the recent push for low-latency \& high-reliability wireless systems (required by, among others, tele-medicine, interactive-gaming, delay-sensitive control applications, spectrum sharing, real-time energy management, and autonomous vehicles), we study the fundamental tradeoffs involved over the last-hop of wireless downlink broadcast channels, where one base-station wishes to communicate independent messages to many users. Classical Shannon's capacity results ignore latency constraints present in practical systems. To shade light into the fading Gaussian BC (AWGN-BC) with latency constraints, we first study the Layered Packet Erasure BC (LPE-BC) model, recently introduced by Tse and Yates to determined the capacity region of the AWGN-BC to within a constant gap for any the fading distribution. The LPE-BC generalizes another channel model widely used in the networking literature: the (single-layer) Binary Erasure Channel, where at each channel use a packet is sent, and the packet is either received or erased at each receiver.
In this talk we look explicitly at the multi-layer LPE-BC with causal CSIT and without latency requirements and provide: (i) an outer bound for any number of receivers and layers, and (ii) several achievable rate regions obtained by using schemes that employ network coding per-layer and/or across layers in case retransmissions are needed, and which match the outer bound for certain channel parameters. Then, we incorporate hard-deadline into the LPE-BC and show: (iii) scheduling algorithms that are optimal with full-lookahead CSIT and current CSIT. Finally, we move to the AWGN-BC setting when hard deadlines are imposed and show that (iv) commonly used broadcast strategies must be carefully re-thought in the finite latency setting.

Joint work with:
Dr. Natasha Devroye and Dr. Besma Smida

Related publications:
-- Siyao Li, Daniela Tuninetti, and Natasha Devroye, "On the Capacity Region of the Layered Packet Erasure Broadcast Channel with Feedback," Proceedings of the 2019 IEEE International Conference on Communications (ICC 2019), pp. 1-5, Shanghai, China, May 2019. SUBMITTED.
-- Daniela Tuninetti, Besma Smida, Hulya Seferoglu, and Natasha Devroye "On Gaussian Broadcast Channels with Hard Deadlines," Proceedings of the 2018 IEEE International Conference on Communications (ICC 2018), pp. 1-5, Kansas City, MO USA, May 2018. DOI:10.1109/ICCW.2018.8403488. PUBLISHED.
-- Zohreh Ovasi, Natasha Devroye, Besma Smida, Hulya Seferoglu and Daniela Tuninetti "On Erasure Broadcast Channels with Hard Deadlines," Proceedings of the 2018 IEEE International Conference on Communications (ICC 2018), Workshop: 5G & Beyond - Enabling Technologies and Applications focus on the Tactile Internet (5G TACNET), pp. 1-7, Kansas City, MO USA, May 2018. DOI:10.1109/ICCW.2018.8403488. PUBLISHED. (Read Less <<)


Daniela Tuninetti

University of Illinois at Chicago, USA

Daniela Tuninetti is currently a Professor within the Department of Electrical and Computer Engineering (ECE) at the University of Illinois at Chicago (UIC), which she joined in 2005. Dr. Tuninetti got her Ph.D. in Electrical Engineering in 2002 from ENST/Telecom ParisTech (Paris, France, with work done at the Eurecom Institute in Sophia Antipolis, France), and she was a postdoctoral research associate at the School of Communication and Computer Science at the Swiss Federal Institute of Technology ... (Read More >>)

Daniela Tuninetti is currently a Professor within the Department of Electrical and Computer Engineering (ECE) at the University of Illinois at Chicago (UIC), which she joined in 2005. Dr. Tuninetti got her Ph.D. in Electrical Engineering in 2002 from ENST/Telecom ParisTech (Paris, France, with work done at the Eurecom Institute in Sophia Antipolis, France), and she was a postdoctoral research associate at the School of Communication and Computer Science at the Swiss Federal Institute of Technology in Lausanne (EPFL, Lausanne, Switzerland) from 2002 to 2004. Dr. Tuninetti is a recipient of a best paper award at the European Wireless Conference in 2002, of an NSF CAREER award in 2007, and named UIC University Scholar in 2015. Dr. Tuninetti was the editor-in-chief of the IEEE Information Theory Society Newsletter from 2006 to 2008; she was an editor for IEEE COMMUNICATION LETTERS from 2006 to 2009, for IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS from 2011 to 2014, and for IEEE TRANSACTIONS ON INFORMATION THEORY from 2015 to 2017. Dr. Tuninetti's research interests are in the ultimate performance limits of wireless interference networks (with special emphasis on cognition and user cooperation), coexistence between radar and communication systems, multi-relay networks, content-type coding, and caching systems. (Read Less <<)



General Information

Address

Room 212, Building B, National Supercomputer Center, Sun Yat-sen University Higher Education Megacenter, Guangzhou, China

广州市大学城中山大学国家超级计算中心B栋212


Organizers

School of Data and Computer Science

School of Electronics and Communication Engineering


Committee

Xiao Ma, Li Chen, Ting-Yi Wu, Jiong-Yue Xing, Jing-Qiao Fu


Contacts

Ting-Yi Wu: wutingyi@mail.sysu.edu.cn (+86 13126467811)

Jiong-Yue Xing: xingjyue@mail2.sysu.edu.cn (+86 13580529389)

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