Starting in January 2023 on Leave as:
New and Recent Events:
, Urumqi, China, Ocotber 18-20, 2024.
Plenary Talk, Hong Kong China
Friendship Association Forum, August 28, 2024.
Plenary Talk, CCF BigData,
Qingdao, China, August 10, 2024.
Plenary Talk, the International Conference on
Mathematical Theory of Deep Learning, Academy of Mathematics and
Systems Science of CAS, Beijing, China,
August 5-9, 2024.
Keynote speech, Basic Science
and Artificial Intelligence Forum, International Congress of Basic
Science, Beijing, China, July 21, 2024.
"Learning Deep
Low-Dim Models from High-Dim Data: From Theory to Practice", CVPR,
Seattle, June 17-21, 2024.
Tutorial at BIRS Workshop "Mathematics of Deep
Learning", the Casa Matematica Oaxaca (CMO), Mexico, June 9-14,
2024.
Keynote, Huawei Strategic Forum, Shenzhen, May 21, 2024.
APAC Keynote, Goldman Sachs Engineering Conference, May
13, 2024.
Invited talk at San-Ya-Po Forum, Huawei, Shenzhen, May 11, 2024.
Invited talk at the HKU Business School Global CEO
program, May 10, 2024.
Invited talk on "Transparent and
Consistent Deep Representation Learning" at Alibaba Cloud, Hong Kong,
May 7, 2024.
Tutorial "Building White-Box Deep Neural Networks",
ICASSP, Seoul, Korea, April 14-19, 2024.
Guest of Honor and Speaker at
the 2024 Annual Joint High Table dinner, by the HKU student residence,
April 12, 2024.
Talk on "Transparent and
Consistent Deep Representation Learning" at the College of Engineering
and Computer Science, VinUniversity, Hanoi, Vietnam, April
8th, 2024.
Talk on "Transparent and
Consistent Deep Representation Learning" at the Department of
Statistics, Stanford University, March 7th, 2024.
Recorded Talk on "Transparent and
Consistent Deep Representation Learning" at the Department of
Mathematics, UC Davis, March 6th, 2024.
A Distinguished Lecture at the Masters Forum of the
Chinese University of Hong Kong, Shenzhen, January 16, 2024.
A Tutorial Lecture on ReduNet at the International Conference on
Parsimony and Learning, Hong Kong, January 6, 2024.
General Chair of the International Conference on
Parsimony and Learning, Hong Kong, January 3-6, 2024.
Recent Releases:
- A New Website: Sclaing White-Box Transformers
for Vision.
- A New Website: White-Box Transformers
via Sparse Rate Reduction.
- A New International Conference: Conference on Parsimony and
Learning (CPAL) (Hong Kong, Jan. 3-6, 2024).
- ACDL2023 Plenary Lectures on Deep Networks and
Intelligence.
- A New Textbook: High-Dimensional Data
Analysis with Low-Dimensional Models (or a mirror site
for download
in China).
- A New Position Paper:
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 Course EECS208: Computational
Principles for High-Dimensional Data Analysis
(with a Course Website and Lecture Slides).
- Recorded video of talk: Transparent and
Consistent Deep Representation Learning, Mathematics of UC Davis,
March 6, 2024.
- 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.
Project Websites:
- Whitebox
Transformers via Sparse Rate Reduction (with
Yaodong Yu et. al.).
- ReduNet: Whitebox
Deep Networks
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
Sam Buchanan).
- 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
Jitendra Malik).
- 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
Vidal).
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©2017 Yi Ma
Last modified: Wed Sep 4 21:56:25 HKT 2024
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University of California,
Berkeley 
