Difference between revisions of "Resource:Seminar"

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{{SemNote
{{SemNote
|time='''Friday 10:30-12:00'''
|time='''2025-04-11 10:30-12:00'''
|addr=4th Research Building A518
|addr=4th Research Building A518
|note=Useful links: [[Resource:Reading_List|Readling list]]; [[Resource:Seminar_schedules|Schedules]]; [[Resource:Previous_Seminars|Previous seminars]].
|note=Useful links: [[Resource:Reading_List|📚 Readling list]]; [[Resource:Seminar_schedules|📆 Schedules]]; [[Resource:Previous_Seminars|🧐 Previous seminars]].
}}
}}


===Latest===
===Latest===
{{Latest_seminar
{{Latest_seminar
|abstract=LoRa Wide Area Network (LoRaWAN) has emerged as a dominant technology for Low Power Wide Area Networks (LPWAN). However, due to the ever-growing network size, packet collisions caused by concurrent transmissions have become a serious challenge in LoRa Wan.Existing studies have either ignored the issue by exploring only a few inaccurate features or addressed it using a complex receiver with up to eight antennas. To strike a better balance between implementation cost and system performance, we propose Hi 2 LoRa, which leverages highly dimensional and highly accurate features for LoRa concurrent decoding with only two receiving antennas. The feature dimensions are extended by exploring various types of hardware imperfections and channel state information inherent to each transceiver pair. To improve feature accuracy, low pass filters and BiLSTM networks are employed to trace and learn their temporal patterns. Additionally, an effective collision suppression strategy is introduced to combat feature corruption from other concurrent packets. Extensive evaluations on real-world testbeds show that the achievable concurrency in Hi2LoRa is either close to that of state-of-the-art approaches with much higher complexity (e.g., using eight antennas) or 2.7 x of prior work with comparable complexity (e.g., using two antennas).
|abstract = 在AI革命汹涌来袭的当下连续创业者如何实现底层认知的进化？AI对技术的影响又如何影响到企业决策？报告人何仲潇系云起老和科技有限公司创始人/CEO，四川浙大校友会理事，浙大企业导师，成都市金熊猫B类人才。让我们跟随云起老和的视角感受AI浪潮中的创业进化历程！
|confname=ICNP'23
|confname = 创新创业分享会
|link=https://ieeexplore.ieee.org/abstract/document/10355583
|link = https://mobinets.cn/site/Resource:Seminar
|title=Hi2LoRa: Exploring Highly Dimensional and Highly Accurate Features to Push LoRaWAN Concurrency Limits with Low Implementation Cost
|title= AI革命浪潮中的进化--连续创业者的底层认知进化与创业选择
|speaker=Jiyi
|speaker= 何仲潇
|date=2024-07-05}}
|date=2025-04-11
{{Latest_seminar
}}
|abstract=Centralized approaches for multi-robot coverage planning problems suffer from the lack of scalability. Learning-based distributed algorithms provide a scalable avenue in addition to bringing data-oriented feature generation capabilities to the table, allowing integration with other learning-based approaches. To this end, we present a learning-based, differentiable distributed coverage planner (D2CoP LAN ) which scales efficiently in runtime and number of agents compared to the expert algorithm, and performs on par with the classical distributed algorithm. In addition, we show that D2CoP LAN can be seamlessly combined with other learning methods to learn end-to-end, resulting in a better solution than the individually trained modules, opening doors to further research for tasks that remain elusive with classical methods.
 
|confname=ICRA'23
|link=https://ieeexplore.ieee.org/abstract/document/10160341
|title=D2CoPlan: A Differentiable Decentralized Planner for Multi-Robot Coverage
|speaker=Xianyang
|date=2024-07-05}}
{{Resource:Previous_Seminars}}
{{Resource:Previous_Seminars}}

Latest revision as of 09:27, 11 April 2025

Time: 2025-04-11 10:30-12:00
Address: 4th Research Building A518
Useful links: 📚 Readling list; 📆 Schedules; 🧐 Previous seminars.

Latest

  1. [创新创业分享会] AI革命浪潮中的进化--连续创业者的底层认知进化与创业选择, 何仲潇
    Abstract: 在AI革命汹涌来袭的当下连续创业者如何实现底层认知的进化？AI对技术的影响又如何影响到企业决策？报告人何仲潇系云起老和科技有限公司创始人/CEO，四川浙大校友会理事，浙大企业导师，成都市金熊猫B类人才。让我们跟随云起老和的视角感受AI浪潮中的创业进化历程！

History

2024

2023

2022

2021

2020

  • [Topic] [ The path planning algorithm for multiple mobile edge servers in EdgeGO], Rong Cong, 2020-11-18

2019

2018

2017

Instructions

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