Lam Si Tung Ho

Publication Activity (10 Years)

Years Active: 2012-2023
Publications (10 Years): 23

Top Topics

Generalization Bounds

Convergence Rate

Active Learning

Top Venues

J. Approx. Theory

Publications

Cuong N. Nguyen, Phong Tran, Lam Si Tung Ho, Vu C. Dinh, Anh T. Tran, Tal Hassner, Cuong V. Nguyen
Simple Transferability Estimation for Regression Tasks. UAI (2023)
Quan Huu Do, Binh T. Nguyen, Lam Si Tung Ho
A Generalization Bound of Deep Neural Networks for Dependent Data. CoRR (2023)
Cuong N. Nguyen, Phong Tran, Lam Si Tung Ho, Vu C. Dinh, Anh T. Tran, Tal Hassner, Cuong V. Nguyen
Simple Transferability Estimation for Regression Tasks. CoRR (2023)
Cuong N. Nguyen, Lam Si Tung Ho, Vu C. Dinh, Tal Hassner, Cuong V. Nguyen
Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy. CoRR (2022)
Esha Saha, Lam Si Tung Ho, Giang Tran
SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics. CoRR (2022)
Cuong V. Nguyen, Lam Si Tung Ho, Huan Xu, Vu C. Dinh, Binh T. Nguyen
Bayesian active learning with abstention feedbacks. Neurocomputing 471 (2022)
Lam Si Tung Ho, Binh T. Nguyen, Vu C. Dinh, Duy Nguyen
Posterior concentration and fast convergence rates for generalized Bayesian learning. CoRR (2021)
Lam Si Tung Ho, Vu C. Dinh
Searching for Minimal Optimal Neural Networks. CoRR (2021)
Binh T. Nguyen, Duy M. Nguyen, Lam Si Tung Ho, Vu C. Dinh
OASIS: An Active Framework for Set Inversion. CoRR (2021)
Lam Si Tung Ho, Giang Tran
Adaptive Group Lasso Neural Network Models for Functions of Few Variables and Time-Dependent Data. CoRR (2021)
Vu C. Dinh, Lam Si Tung Ho
Consistent Feature Selection for Analytic Deep Neural Networks. CoRR (2020)
Lam Si Tung Ho, Binh T. Nguyen, Vu C. Dinh, Duy M. H. Nguyen
Posterior concentration and fast convergence rates for generalized Bayesian learning. Inf. Sci. 538 (2020)
Lam Si Tung Ho, Vu C. Dinh
Consistent feature selection for neural networks via Adaptive Group Lasso. CoRR (2020)
Vu C. Dinh, Lam Si Tung Ho
Consistent feature selection for analytic deep neural networks. NeurIPS (2020)
Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel Ward
Recovery guarantees for polynomial coefficients from weakly dependent data with outliers. J. Approx. Theory 259 (2020)
Binh T. Nguyen, Duy M. H. Nguyen, Lam Si Tung Ho, Vu C. Dinh
An active learning framework for set inversion. Knowl. Based Syst. 185 (2019)
Cuong V. Nguyen, Lam Si Tung Ho, Huan Xu, Vu C. Dinh, Binh Nguyen
Bayesian Active Learning With Abstention Feedbacks. CoRR (2019)
Binh T. Nguyen, Duy M. H. Nguyen, Lam Si Tung Ho, Vu C. Dinh
OASIS: An Active Framework for Set Inversion. SoMeT (2018)
Lam Si Tung Ho, Hayden Schaeffer, Giang Tran, Rachel Ward
Recovery guarantees for polynomial approximation from dependent data with outliers. CoRR (2018)
Vu C. Dinh, Lam Si Tung Ho, Binh T. Nguyen, Duy M. H. Nguyen
Fast learning rates with heavy-tailed losses. NIPS (2016)
Vu C. Dinh, Lam Si Tung Ho, Duy M. H. Nguyen, Binh T. Nguyen
Fast learning rates with heavy-tailed losses. CoRR (2016)
Daniel Irving Bernstein, Lam Si Tung Ho, Colby Long, Mike A. Steel, Katherine St. John, Seth Sullivant
Bounds on the Expected Size of the Maximum Agreement Subtree. SIAM J. Discret. Math. 29 (4) (2015)
Vu C. Dinh, Lam Si Tung Ho, Viet Cuong Nguyen, Duy M. H. Nguyen, Binh T. Nguyen
Learning from Non-iid Data: Fast Rates for the One-vs-All Multiclass Plug-in Classifiers. TAMC (2015)
Cécile Ané, Lam Si Tung Ho, Sebastien Roch
Phase transition on the convergence rate of parameter estimation under an Ornstein-Uhlenbeck diffusion on a tree. CoRR (2014)
Daniel Irving Bernstein, Lam Si Tung Ho, Colby Long, Mike A. Steel, Katherine St. John, Seth Sullivant
Bounds on the Expected Size of the Maximum Agreement Subtree. CoRR (2014)
Viet Cuong Nguyen, Lam Si Tung Ho, Vu C. Dinh
Generalization and Robustness of Batched Weighted Average Algorithm with V-Geometrically Ergodic Markov Data. ALT (2013)
Viet Cuong Nguyen, Vu C. Dinh, Lam Si Tung Ho
Mel-frequency Cepstral Coefficients for Eye Movement Identification. ICTAI (2012)