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The Department of Probability and Statistics organizes the "The Probability and Statistics Seminar August 2024" featuring a presentation by Dr. Clément Elvira from Centrale Supélec, Rennes, France. Detailed information about the presentation and the speaker is as follows:

  • Speaker: Assist. Prof. Ph.D. Clément Elvira - CentraleSupélec (CS), Rennes, France.
  • Time: 9:00 am, Tuesday, August 19, 2024.
  • Venue: Room F207 - University of Science, Campus 1, 227 Nguyen Van Cu, District 5, Ho Chi Minh City.
  • Title: Safe Screening: An introduction and perspectives
  • Abstract: 
    Convex optimization problems with additive penalty terms arise in numerous applications, including Signal Processing and Machine Learning. A key factor underlying their success is their ability to promote solutions with a desired structure, such as sparsity. This talk will delve into the fundamental concepts behind "safe screening", an acceleration technique for sparsity-promoting optimization problems. Specifically, safe screening involves designing tests to detect zero entries in the solution of the problem. We will then present the latest contributions in this field and discuss future perspectives.

The students, master’s students and Ph.D. students and anyone interested are invited to participate in the meeting. To attend, please click on the link.

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The Department of Optimization organizes the "Optimization Seminar August 2024" with content covering from the theory of Convex Analysis to practical applications such as machine learning and image reconstruction. Details are as follows:

  • Speaker: Prof. Dr. Nguyen Mau Nam - Portland State University, USA.
  • Time: 9:00 am, Tuesday, August 13, 2024.
  • Venue: Room F207 - University of Science, Campus 1, 227 Nguyen Van Cu, District 5, Ho Chi Minh City.
  • Title: Generalized Differentiation and Applications to Optimization: from Convexity to Nonconvexity
  • Abstract: 
    In this presentation, we introduce recent advances in developing calculus rules of generalized differentiation for nonsmooth functions and set-valued mappings in both finite and infinite dimensions, spanning from convexity to nonconvexity. We also explore how generalized differentiation can address convex and nonconvex optimization challenges, particularly those that are of a nonsmooth nature. Our focus includes studying multifacility location, machine learning, and image reconstructions from both theoretical and numerical perspectives. We introduce optimization techniques to design algorithms for solving the optimization problems arising in these areas.

The students, master’s students and Ph.D. students and anyone interested are invited to participate in the meeting. To attend, please click on the link.

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Poster_MK60Conf_16-20Sept2024.png

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TMA Tech Group is a leading technology group in Vietnam with 27 years of development, more than 4,000 talented engineers, clients in over 30 countries, and 16 years of winning the Gold Medal for software export.

 

Currently, TMA Tech Group is looking for potential candidates for the Internship Program in August 2024 for students. Detailed information is in the poster below.

Positions: 

  • AI Engineer
  • Data Engineer
  • Back-end Developer (Java, Python, .Net, NodeJS)
  • Embedded Engineer (C++)
  • Mobile Developer (Flutter, iOS, Swift)
  • Front-end Developer (ReactJS, Angular)
  • Automation Tester
  • Business Analyst
  • Business Development
  • UX/UI Designer

Requirements : 

  • Students from the end of their 3rd year
  • Minimum internship duration of 3 months starting from August 2024
  • GPA >= 7.0

Benerfits:  

  • Opportunity for part-time contracts with salary
  • Direct guidance from Subject Matter Experts (SME)
  • Training in advanced technology and basic working skills
  • Provided with necessary working equipment

Application Documents:

  • English CV
  • TOEIC or IELTS certificate (if available)
  • Latest academic transcript with confirmation from the university (soft copy)

Submit applications to: This email address is being protected from spambots. You need JavaScript enabled to view it.

Application deadline: 15/08/2024

Contact Information: Industry Internship

  • TMA Building, No. 10, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, HCMC
  • Phone: 028 3997 8000 - Ext: 5615 / 028 3891 2532
  • Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

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"Probability - Statistics Seminar in January 2024" is going to be organized with a report by Dr. Nguyen Hung Minh Tan.

Dr. Tan Nguyen is currently an Assistant Professor of Mathematics (Presidential Young Professor) at the National University of Singapore (NUS). Before joining NUS, he was a postdoctoral scholar in the Department of Mathematics at the University of California, Los Angeles, working with Dr. Stanley J. Osher. He obtained his Ph.D. in Machine Learning from Rice University, where he was advised by Dr. Richard G. Baraniuk. Dr. Nguyen is an organizer of the 1st Workshop on Integration of Deep Neural Models and Differential Equations at ICLR 2020. He also had two awesome long internships with Amazon AI and NVIDIA Research. He is the recipient of the prestigious Computing Innovation Postdoctoral Fellowship (CIFellows) from the Computing Research Association (CRA), the NSF Graduate Research Fellowship, and the IGERT Neuroengineering Traineeship. He received his M.S. and B.S. in Electrical and Computer Engineering from Rice University in May 2018 and May 2014, respectively.

Undergraduate, Master and Ph.D. students and interested people are invited to participate the seminar.

    • Time:  09:30 a.m. Wendsday, June 26, 2024.
    • Location: Room E202B, Campus 1- University of Science (227 Nguyen Van Cu St., District 5, Ho Chi Minh City).

Title: Principled Frameworks for Designing Deep Learning Models: Efficiency, Expressivity, and Robustness

Summary of the report is as follows:

Designing deep learning models for practical applications, including those in computer vision, natural language processing, and mathematical modeling, is an art that often involves an expensive search over candidate architectures. In this talk, the speaker will introduce two novel optimization frameworks to facilitate the process of designing efficient and expressive deep learning models including the neural ordinary differential equations (Neural ODEs) and transformers.
 

Scan the QR code below or click on the link before June 25, 2024 to register to attend.

seminar_26.6_thay_Tan.png

  1. Lectures by Thomas Koberda
  2. Mathematical Analysis Seminar Academic Year 2023-2024
  3. Workshop on "Writing Scientific Papers Using LaTeX"
  4. Global Young Leaders Program by POSCO & POSTECH