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2020 – today
- 2024
[j3]Tam Le:
Nonsmooth Nonconvex Stochastic Heavy Ball. J. Optim. Theory Appl. 201(2): 699-719 (2024)- [c25]Tam Le, Truyen Nguyen, Kenji Fukumizu:
Optimal Transport for Measures with Noisy Tree Metric. AISTATS 2024: 3115-3123 - [c24]Thong Pham, Shohei Shimizu, Hideitsu Hino, Tam Le:
Scalable Counterfactual Distribution Estimation in Multivariate Causal Models. CLeaR 2024: 1118-1140 - [c23]Tam Le, Truyen Nguyen, Kenji Fukumizu:
Generalized Sobolev Transport for Probability Measures on a Graph. ICML 2024 - [c22]Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho:
Sliced Wasserstein with Random-Path Projecting Directions. ICML 2024 - [i22]Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho:
Sliced Wasserstein with Random-Path Projecting Directions. CoRR abs/2401.15889 (2024) - [i21]Tam Le, Truyen Nguyen, Kenji Fukumizu:
Generalized Sobolev Transport for Probability Measures on a Graph. CoRR abs/2402.04516 (2024) - [i20]Samuel Kessler, Tam Le, Vu Nguyen:
SAVA: Scalable Learning-Agnostic Data Valuation. CoRR abs/2406.01130 (2024) - [i19]Viet-Hoang Tran, Trang Pham, Tho Tran, Tam Le, Tan M. Nguyen:
Tree-Sliced Wasserstein Distance on a System of Lines. CoRR abs/2406.13725 (2024) - 2023
- [j2]Jérôme Bolte, Tam Le, Edouard Pauwels
:
Subgradient Sampling for Nonsmooth Nonconvex Minimization. SIAM J. Optim. 33(4): 2542-2569 (2023) - [c21]Tam Le, Truyen Nguyen, Kenji Fukumizu:
Scalable Unbalanced Sobolev Transport for Measures on a Graph. AISTATS 2023: 8521-8560 - [c20]Xinru Hua, Truyen Nguyen, Tam Le, Jose H. Blanchet, Viet Anh Nguyen:
Dynamic Flows on Curved Space Generated by Labeled Data. IJCAI 2023: 3803-3811 - [i18]Xinru Hua, Truyen Nguyen, Tam Le, Jose H. Blanchet, Viet Anh Nguyen:
Dynamic Flows on Curved Space Generated by Labeled Data. CoRR abs/2302.00061 (2023) - [i17]Tam Le, Truyen Nguyen, Kenji Fukumizu:
Scalable Unbalanced Sobolev Transport for Measures on a Graph. CoRR abs/2302.12498 (2023) - [i16]Anh-Khoa Nguyen Vu, Thanh-Toan Do, Vinh-Tiep Nguyen, Tam Le, Minh-Triet Tran, Tam V. Nguyen:
Few-Shot Object Detection via Synthetic Features with Optimal Transport. CoRR abs/2308.15005 (2023) - [i15]Tam Le, Truyen Nguyen, Kenji Fukumizu:
Optimal Transport for Measures with Noisy Tree Metric. CoRR abs/2310.13653 (2023) - [i14]Thong Pham, Shohei Shimizu, Hideitsu Hino, Tam Le:
Scalable Counterfactual Distribution Estimation in Multivariate Causal Models. CoRR abs/2311.00927 (2023) - 2022
- [c19]Tam Le, Truyen Nguyen, Dinh Phung, Viet Anh Nguyen:
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics. AISTATS 2022: 9844-9868 - [i13]Tam Le, Truyen Nguyen, Dinh Q. Phung, Viet Anh Nguyen:
Sobolev Transport: A Scalable Metric for Probability Measures with Graph Metrics. CoRR abs/2202.10723 (2022) - 2021
- [c18]Tam Le, Truyen Nguyen:
Entropy Partial Transport with Tree Metrics: Theory and Practice. AISTATS 2021: 3835-3843 - [c17]Tam Le, Nhat Ho, Makoto Yamada:
Flow-based Alignment Approaches for Probability Measures in Different Spaces. AISTATS 2021: 3934-3942 - [c16]Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua:
Point-set Distances for Learning Representations of 3D Point Clouds. ICCV 2021: 10458-10467 - [c15]Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne:
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. ICML 2021: 8084-8095 - [c14]Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls:
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization. NeurIPS 2021: 13537-13549 - [c13]Tam Le, Truyen Nguyen, Makoto Yamada, Jose H. Blanchet, Viet Anh Nguyen:
Adversarial Regression with Doubly Non-negative Weighting Matrices. NeurIPS 2021: 16964-16976 - [c12]Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang:
LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport. ECML/PKDD (1) 2021: 655-670 - [i12]Tam Le, Truyen Nguyen:
Entropy Partial Transport with Tree Metrics: Theory and Practice. CoRR abs/2101.09756 (2021) - [i11]Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua:
Point-set Distances for Learning Representations of 3D Point Clouds. CoRR abs/2102.04014 (2021) - [i10]Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls:
Nonsmooth Implicit Differentiation for Machine Learning and Optimization. CoRR abs/2106.04350 (2021) - [i9]Tam Le, Truyen Nguyen, Makoto Yamada, Jose H. Blanchet, Viet Anh Nguyen:
Adversarial Regression with Doubly Non-negative Weighting Matrices. CoRR abs/2109.14875 (2021) - 2020
- [c11]Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada:
Topological Bayesian Optimization with Persistence Diagrams. ECAI 2020: 1483-1490 - [i8]Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne:
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. CoRR abs/2006.07593 (2020)
2010 – 2019
- 2019
- [c10]Eugène Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi:
Safe Grid Search with Optimal Complexity. ICML 2019: 4771-4780 - [c9]Tam Le, Matt W. Mutka:
Access control with delegation for smart home applications. IoTDI 2019: 142-147 - [c8]Tam Le, Matt W. Mutka:
PPCA: privacy-preserving conditional actions for IoT environments using smart contracts. MobiQuitous 2019: 172-179 - [c7]Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi:
Tree-Sliced Variants of Wasserstein Distances. NeurIPS 2019: 12283-12294 - [c6]Tam Le, Matt W. Mutka:
A Lightweight Block Validation Method for Resource-Constrained IoT Devices in Blockchain-Based Applications. WOWMOM 2019: 1-9 - [i7]Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi:
Tree-Sliced Approximation of Wasserstein Distances. CoRR abs/1902.00342 (2019) - [i6]Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada:
Topological Bayesian Optimization with Persistence Diagrams. CoRR abs/1902.09722 (2019) - [i5]Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang:
LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport. CoRR abs/1909.02373 (2019) - [i4]Tam Le, Nhat Ho, Makoto Yamada:
Computationally Efficient Tree Variants of Gromov-Wasserstein. CoRR abs/1910.04462 (2019) - [i3]Tam Le, Viet Huynh, Nhat Ho, Dinh Q. Phung, Makoto Yamada:
On Scalable Variant of Wasserstein Barycenter. CoRR abs/1910.04483 (2019) - 2018
- [c5]Tam Le, Makoto Yamada:
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams. NeurIPS 2018: 10028-10039 - [c4]Tam Le, Matt W. Mutka:
CapChain: A Privacy Preserving Access Control Framework Based on Blockchain for Pervasive Environments. SMARTCOMP 2018: 57-64 - [i2]Tam Le, Makoto Yamada:
Riemannian Manifold Kernel for Persistence Diagrams. CoRR abs/1802.03569 (2018) - [i1]Eugène Ndiaye, Tam Le, Olivier Fercoq, Joseph Salmon, Ichiro Takeuchi:
Safe Grid Search with Optimal Complexity. CoRR abs/1810.05471 (2018) - 2016
- [c3]Abdelhakim Ahmim, Tam Le, Esther Ososanya, Sasan Haghani:
Design and implementation of a home automation system for smart grid applications. ICCE 2016: 538-539 - 2015
- [j1]Tam Le, Marco Cuturi:
Adaptive Euclidean maps for histograms: generalized Aitchison embeddings. Mach. Learn. 99(2): 169-187 (2015) - [c2]Tam Le, Marco Cuturi:
Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations. ICML 2015: 2002-2011 - 2013
- [c1]Tam Le, Marco Cuturi:
Generalized Aitchison Embeddings for Histograms. ACML 2013: 293-308
Coauthor Index
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