BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Asia/Seoul BEGIN:STANDARD DTSTART:19881009T020000 TZOFFSETFROM:+1000 TZOFFSETTO:+0900 TZNAME:KST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20210720T230528Z UID:46943E6C-8892-4BA0-818C-F58C2B3819A4 DTSTART;TZID=Asia/Seoul:20210715T093000 DTEND;TZID=Asia/Seoul:20210716T122000 DESCRIPTION:Internet-of-Things (IoT) is a paradigm shifting technology that advances various aspects in our life in recent years. The proliferation o f Artificial Intelligence (AI) opens up the possibility of integrating int elligence into various IoT devices\, which creates many smart and efficien t solutions in areas such as healthcare\, security surveillance\, self-dri ve car\, human activity recognition\, transportation\, robots in manufactu ring\, and risk management to name a few. The IoT devices range from high- end computers to mobile devices and low-end microcontroller\, wherein many of them are resource-constrained in computation power and storage. Due to this reason\, it is challenging to apply deep learning (mostly computatio nally extensive and requiring high storage space) into resource-constraine d IoT devices. To address these challenges\, various approaches have been proposed to make deep learning lightweight and optimized for resource-cons trained devices. In this workshop\, we will review and discuss the represe ntative techniques on the hardware level (hardware acceleration techniques ) as well as on the software level (model compression techniques). We will also deal with the fundamental aspects of reinforcement learning\, challe nges and progresses in face recognition\, biometric applications and feder ated learning. Interesting research areas are presented to design future n etworks based on AI.\n\n*The detailed information about this workshop is a vailable at https://ai-security.github.io/summer-school-2021.\n\nCo-sponso red by: Institute of Electronics and Information Engineers\, Korea\n\nAgen da: \n15 July 2021\n\nTime\n\nProgram\n\nSpeaker\n\n09:30 – 10:20\n\nRei nforcement Learning and Stochastic Optimization: A unified framework for s equential decisions Part 1\n\nProf. Warren Powell\, Princeton University\, USA\n\n10:20 – 11:00\n\nNew Challenges to Face Recognition: Low-Resolut ion Face Recognition and Periocular Recognition\n\nDr. Cheng-Yaw Low\, Yon sei University\, Korea\n\n11:00 – 11:40\n\nAI for Information-Centric Ne tworks as a Future Network Technology\n\nProf. Byung Seo Kim\, Hongik Univ ersity\, Korea\n\n11:40 – 12:20\n\nDeep Review of Model Compression in K nowledge Distillation Side\n\nProf. Byung Chul Ko\, Keimyung University\, Korea\n\n12:20 – 14:00\n\nLunch break\n\n14:00 -14:40\n\nBiometric Crypt osystem: Progress and Challenge\n\nProf. Andrew Beng-Jin Teoh\, Yonsei Uni versity\, Korea\n\n14:40 – 15:20\n\nMaritime\, Underwater IoT and AI-bas ed First-order logic TUM-IoT Digtital Twin\n\n* TUM-IoT : Terristrial\, Un derwater\, Maritime - IoT\n\nProf. Soohyun Park\, Kookmin University\, Kor ea\n\n15:20\n\nEnd\n\n16 July 2021\n\nTime\n\nProgram\n\nSpeaker\n\n09:30 – 10:20\n\nReinforcement Learning and Stochastic Optimization: A unified framework for sequential decisions Part 2\n\nProf. Warren Powell\, Prince ton University\, USA\n\n10:20 – 11:00\n\nOverview of Model Compression a nd Quantization in Deep Learning\n\nDr. Jin-Chuan See\, Universiti Tunku A bdul Rahman\, Malaysia\n\n11:00 – 11:40\n\nEdge Federated Learning: Rece nt Advances and Open Research Problems\n\nDr. Rehmat Ullah\, Queen's Unive rsity\, UK\n\n11:40 – 12:20\n\nHardware Acceleration and Optimization of Deep Neural Networks\n\nProf. William Song\, Yonsei University\, Korea\n\ n12:20\n\nEnd\n\nVirtual: https://events.vtools.ieee.org/m/276276 LOCATION:Virtual: https://events.vtools.ieee.org/m/276276 ORGANIZER:bardic@naver.com SEQUENCE:9 SUMMARY:Summer School 2021 (Virtual) - Advances and Challenges of Artificia l Intelligence in the Internet-of-Things Era URL;VALUE=URI:https://events.vtools.ieee.org/m/276276 X-ALT-DESC:Description: <br /><p>Internet-of-Things (IoT) is a paradigm shi fting technology that advances various aspects in our life in recent years . The proliferation of Artificial Intelligence (AI) opens up the possibili ty of integrating intelligence into various IoT devices\, which creates ma ny smart and efficient solutions in areas such as healthcare\, security su rveillance\, self-drive car\, human activity recognition\, transportation\ , robots in manufacturing\, and risk management to name a few. The IoT dev ices range from high-end computers to mobile devices and low-end microcont roller\, wherein many of them are resource-constrained in computation powe r and storage. Due to this reason\, it is challenging to apply deep learni ng (mostly computationally extensive and requiring high storage space) int o resource-constrained IoT devices. To address these challenges\, various approaches have been proposed to make deep learning lightweight and optimi zed for resource-constrained devices. In this workshop\, we will review an d discuss the representative techniques on the hardware level (hardware ac celeration techniques) as well as on the software level (model compression techniques). We will also deal with the fundamental aspects of reinforcem ent learning\, challenges and progresses in face recognition\, biometric a pplications and federated learning. Interesting research areas are present ed to design future networks based on AI.</p>\n<p>*The detailed informatio n about this workshop is available at https://ai-security.github.io/summer -school-2021.</p><br /><br />Agenda: <br /><p>15 July 2021</p>\n<table wid th="0">\n<tbody>\n<tr>\n<td width="78">\n<p>Time</p>\n</td>\n<td width="36 6">\n<p>Program</p>\n</td>\n<td width="180">\n<p>Speaker</p>\n</td>\n</tr> \n<tr>\n<td width="78">\n<p>09:30 &ndash\; 10:20</p>\n</td>\n<td width="36 6">\n<p>Reinforcement Learning and Stochastic Optimization: A unified fram ework for sequential decisions Part 1</p>\n</td>\n<td width="180">\n<p>Pro f. Warren Powell\, Princeton University\, USA</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>10:20 &ndash\; 11:00</p>\n</td>\n<td width="366">\n<p>New Challenges to Face Recognition: Low-Resolution Face Recognition and Perio cular Recognition</p>\n</td>\n<td width="180">\n<p>Dr. Cheng-Yaw Low\, Yon sei University\, Korea</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>11:00 &ndash\; 11:40</p>\n</td>\n<td width="366">\n<p>AI for Information-Centric Networks as a Future Network Technology</p>\n</td>\n<td width="180">\n<p> Prof. Byung Seo Kim\, Hongik University\, Korea</p>\n</td>\n</tr>\n<tr>\n< td width="78">\n<p>11:40 &ndash\; 12:20</p>\n</td>\n<td width="366">\n<p>D eep Review of Model Compression in Knowledge Distillation Side</p>\n</td>\ n<td width="180">\n<p>Prof. Byung Chul Ko\, Keimyung University\, Korea</p >\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>12:20 &ndash\; 14:00</p>\n</td> \n<td width="366">\n<p>Lunch break</p>\n</td>\n<td width="180">\n<p>&nbsp\ ;</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>14:00 -14:40</p>\n</td>\n<t d width="366">\n<p>Biometric Cryptosystem: Progress and Challenge</p>\n</t d>\n<td width="180">\n<p>Prof. Andrew Beng-Jin Teoh\, Yonsei University\, Korea</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>14:40 &ndash\; 15:20</p >\n</td>\n<td width="366">\n<p>Maritime\, Underwater IoT and AI-based Firs t-order logic TUM-IoT Digtital Twin</p>\n<p>* TUM-IoT : Terristrial\, Unde rwater\, Maritime - IoT</p>\n</td>\n<td width="180">\n<p>Prof. Soohyun Par k\, Kookmin University\, Korea</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n< p>15:20</p>\n</td>\n<td width="366">\n<p>End</p>\n</td>\n<td width="180">\ n<p>&nbsp\;</p>\n</td>\n</tr>\n</tbody>\n</table>\n<p><strong><u>&nbsp\;</ u></strong></p>\n<p>16 July 2021</p>\n<table width="0">\n<tbody>\n<tr>\n<t d width="78">\n<p>Time</p>\n</td>\n<td width="366">\n<p>Program</p>\n</td> \n<td width="180">\n<p>Speaker</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n< p>09:30 &ndash\; 10:20</p>\n</td>\n<td width="366">\n<p>Reinforcement Lear ning and Stochastic Optimization: A unified framework for sequential decis ions Part 2</p>\n</td>\n<td width="180">\n<p>Prof. Warren Powell\, Princet on University\, USA</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>10:20 &nd ash\; 11:00</p>\n</td>\n<td width="366">\n<p>Overview of Model Compression and Quantization in Deep Learning</p>\n</td>\n<td width="180">\n<p>Dr. Ji n-Chuan See\, Universiti Tunku Abdul Rahman\, Malaysia</p>\n</td>\n</tr>\n <tr>\n<td width="78">\n<p>11:00 &ndash\; 11:40</p>\n</td>\n<td width="366" >\n<p>Edge Federated Learning: Recent Advances and Open Research Problems< /p>\n</td>\n<td width="180">\n<p>Dr. Rehmat Ullah\, Queen's University\, U K</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>11:40 &ndash\; 12:20</p>\n< /td>\n<td width="366">\n<p>Hardware Acceleration and Optimization of Deep Neural Networks</p>\n</td>\n<td width="180">\n<p>Prof. William Song\, Yons ei University\, Korea</p>\n</td>\n</tr>\n<tr>\n<td width="78">\n<p>12:20</ p>\n</td>\n<td width="366">\n<p>End</p>\n</td>\n<td width="180">\n<p>&nbsp \;</p>\n</td>\n</tr>\n</tbody>\n</table>\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR