Starting in January 2023:
New and Recent Events:
, March 20, 2023.
- A New Conference: International Conference on
Parsimony and Learning, January 3-6, 2024.
- AI Seminar of the EECS Department, Oregon State
University, October 13, 2023.
- Distinguished Seminar at Hong Kong Unversity of
Science and Technology (HKUST), September 15, 2023.
- Keynote at ICT Workshop, Huawei, Shenzhen, July 28, 2023.
- Summer Course at TBSI on Computational Principles for High-Dimensional Data Analysis, July 11--27, 2022.
- Keynote Talk at the Workshop on
Mathematical Theory for Emergent Intelligence, July 17, 2023.
- Plenary Talk at the Chinese SIAM Conference on Big Data and
AI (CSIAM-BDAI), China, July 8, 2023.
- Keynoge Speech at Tsinghua Alumni Academia Club of
North America annual meeting, July 7, 2023.
- Keynote Speech International
Workshop on Learning and Information Theory, Shen Zhen &
Hong Kong, China, July 3, 2023.
- Invited talk on deep networks
as white boxes in Professor Alan Yuille's lab at Johns Hopkins
University, June 30, 2023.
- Keynote Speech at IEEE Fellow
Forum of the Global AI Product & Application Expo, Shuzhou, China,
June 26, 2023.
- Plenary Lectures at Advanced Course on Data Science
and Machine Learning (ACDL), Tuscany, Italy, June 10-14, 2023.
- ICASSP 2023 Short Course on Low-dimensional Models
and Deep Networks, Rhodes Island, Greece, June 1-7,
- Keynote Speech at the
Construction Industry Concil of Hong Kong, May 30, 2023.
- Keynote Speech at the Asian
Engineering Deans' Summit, Hong Kong University, May 17, 2023.
- Berkeley Semiautonomous Seminar, April 21, 2023.
- Invited Lecture at the HKU Global CEO Program, Beijing, April 8, 2023.
- Invited Talk and Panels at NSF-IEEE Machine Learning Workshop
Invited Lecture at Harvard University Chinese Arcademic Saloon
in Mandarin (with Slides), March
Invited Talk at the Institute for China Business of
the University of Hong Kong, March 8, 2023.
Invited Talk at the 1st Presidential Scholars Symposium of the
University of Hong Kong, March 7, 2023.
Berkeley EECS Seminar, February 16, 2023.
Keynote Speech at the International School on
Deep Learning (DeepLearn 2023 Winter), United Kingdom, January
The Third Workshop on Seeking Low-Dimensionality
in Deep Neural Networks, MBZUAI, Abu Dhabi,
Jan. 3-7, 2023.
- A New Website: White-Box Transformers via Sparse Rate Reduction.
- ACDL2023 Plenary Lectures on Deep Networks and
- A New Textbook: High-Dimensional Data
Analysis with Low-Dimensional Models (or a mirror site
- A New Manuscript:
On the Principles of Parsimony and Self-Consistency for the Emergence of Intelligence.
- A New Presentation & Roundtable Video: On Parsimony and Self-Consistency: the Origin and Nature of Intelligence.
- A New Tutorial: ICASSP 2023 Short Course on Low-dimensional Models
and Deep Networks (a seven-lecture short course).
- A New Workshop: Seeking Low-Dimensionality
in Deep Neural Networks (Abu Dhabi, Jan. 3-7, 2023).
- A New Course EECS208: Computational
Principles for High-Dimensional Data Analysis
(with a Course Website and Lecture Slides).
- Recorded videos on Youtube of From Artificial
Intelligence to Autonomous Inelligence, in Mandarin (with Slides), Harvard Academic Saloon, March 10, 2023.
- Recorded videos on Youtube of Tutorial and Lectures
of the 3rd SLowDNN Workshop, Abu Dhabi,
January 3-6, 2023.
- Recorded video on On the Principles of Parsimony and Self-Consistency:
Structured Compressive Closed-loop
Transcription, IDS HKU, Nov. 25, 2022.
- Recorded video on On Parsimony and Self-Consistency, the Origin and Nature of Intelligence
Workshop, BAAI, September 21, 2022.
- Recorded video on Closed-Loop Data Transcription
via Minimaxing Rate Reduction (with
Paper and Slides), Berkeley Neuroscience Redwood
Center, December 2, 2021.
- Recorded video on ReduNet: Deep
(Convolution) Networks from First Principles
(with Paper ), at CMSA of
Harvard University, April 16, 2021.
- Recorded video on Learning to Detect Geometric
Structures from Images, CVPR 3D Scene Understanding Workshop, June 19, 2021.
- Recorded video of An Overview of
Reinforcement Learning and Optimal Control (with Slides),
February 17, 2021.
Transformers via Sparse Rate Reduction (with
Yaodong Yu et. al.).
- ReduNet: Whitebox
from the Principle of Rate Reduction (with Ryan Chan,
Yaodong Yu, Chong You, John Wright).
- Canonical Factors
for Hybrid Neural Fields (with Brent Yi, Weijia Zeng, and
- General In-hand Object
Rotation with Vision and Touch (with Haozhi Qi, Brent Yi, Jitendra Malik, etc.)
- Dexterous Robot
Hand Manipulation (with Haozhi Qi, Roberto Calandra, and
- Pursuit of
Large-Scale 3D Structures and Geometry (with Yichao Zhou,
Xili Dai, Haozhi Qi).
- UIUC/MSRA: Low-Rank Matrix Recovery
via Convex Optimization (with Wright, Lin and
Candes et. al.).
- UIUC: Face Recognition via
Sparse Representation (with Wright, Ganesh, Yang, Zhou
and Wagner et. al.).
- UIUC: Clustering and
Classification via Lossy Compression (with Wright Yang,
Mobahi, and Rao et. al.).
UIUC: Generalized Principal Component Analysis (with Huang and
©2017 Yi Ma
Last modified: Tue Sep 19 18:09:51 HKT 2023