PhD in Computer Science
University of California, Los Angeles, 2021
Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation
Conference paper
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
Conference paper
Identification of the Adversary from a Single Adversarial Example
Conference paper
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks
Conference paper
A Review of Adversarial Attack and Defense for Classification Methods
Article
Article
CAT: Customized Adversarial Training for Improved Robustness
Conference paper
Concurrent Adversarial Learning for Large-Batch Training
Conference paper
Efficient Non-Parametric Optimizer Search for Diverse Tasks
Conference paper
Random Sharpness-Aware Minimization
Conference paper
DrNAS: Dirichlet Neural Architecture Search
Conference paper
RANK-NOSH: Efficient Predictor-Based NAS via Non-Uniform Successive Halving
Conference paper
Rethinking Architecture Selection in Differentiable NAS
Conference paper
Self-Progressing Robust Training
Conference paper
Conference paper
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples
Conference paper
Sign-OPT: A Query-Efficient Hard-label Adversarial Attack
Conference paper
Evaluating and enhancing the robustness of dialogue systems: A case study on a negotiation agent
Conference paper
Fast training for Large-Scale One-versus-All linear classifiers using Tree-Structured initialization
Conference paper
On the robustness of self-attentive models
Conference paper
Query-efficient hard-label black-box attack: An optimization-based approach
Conference paper
Distributed primal-dual optimization for non-uniformly distributed data
Conference paper
Extreme learning to rank via low rank assumption
Conference paper
Learning from group comparisons: Exploiting higher order interactions
Conference paper
Towards robust neural networks via random self-ensemble
Conference paper
A hyperplane-based algorithm for semi-supervised dimension reduction
Conference paper
Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
Identification of the Adversary from a Single Adversarial Example
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks
A hyperplane-based algorithm for semi-supervised dimension reduction
A hyperplane-based algorithm for semi-supervised dimension reduction
Conference paper
COMP4971A | Independent Work |
COMP4981 | Final Year Project |
COMP5212 | Machine Learning |
COMP4971A | Independent Work |
COMP4981 | Final Year Project |
UROP1000 | Undergraduate Research Opportunities |
UROP1100J | Undergraduate Research Opportunities Series 1 |
COMP4971A | Independent Work |
COMP6211I | Trustworthy Machine Learning |
RMBI4980 | Risk Management and Business Intelligence Capstone Project I |
RMBI4990 | Risk Management and Business Intelligence Capstone Project II |
COMP5212 | Machine Learning |
RMBI4980 | Risk Management and Business Intelligence Capstone Project I |
UROP1100H | Undergraduate Research Opportunities Series 1 |
No Teaching Assignments |
No Teaching Assignments |
LI, Kuan
Computer Science and Engineering
MIN, Rui
Computer Science and Engineering
CHEN, Mingyang
(co-supervision)
Individualized Interdisciplinary Program (Data Science and Analytics)
HUANG, Bo
(co-supervision)
Individualized Interdisciplinary Program (Data Science and Analytics)
QIN, Zeyu
Computer Science and Engineering
LI, Sen
Computer Science and Engineering
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