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Kishan Wimalawarne
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2020 – today
- 2024
- [i5]Christian Clemm, Lutz Stobbe, Kishan Wimalawarne, Jan Druschke:
Towards Green AI: Current status and future research. CoRR abs/2407.10237 (2024) - 2023
- [i4]Kishan Wimalawarne, Taiji Suzuki, Sophie Langer:
Learning Green's Function Efficiently Using Low-Rank Approximations. CoRR abs/2308.00350 (2023) - 2022
- [c5]Kishan Wimalawarne, Taiji Suzuki:
Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank. ACML 2022: 1117-1132 - [i3]Kishan Wimalawarne, Taiji Suzuki:
Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs. CoRR abs/2209.05020 (2022) - 2021
- [j4]Kishan Wimalawarne, Hiroshi Mamitsuka:
Reshaped tensor nuclear norms for higher order tensor completion. Mach. Learn. 110(3): 507-531 (2021) - [i2]Kishan Wimalawarne, Taiji Suzuki:
Adaptive and Interpretable Graph Convolution Networks Using Generalized Pagerank. CoRR abs/2108.10636 (2021) - 2020
- [j3]Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka:
Scaled Coupled Norms and Coupled Higher-Order Tensor Completion. Neural Comput. 32(2): 447-484 (2020)
2010 – 2019
- 2018
- [j2]Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka:
Convex Coupled Matrix and Tensor Completion. Neural Comput. 30(11) (2018) - [c4]Kishan Wimalawarne, Hiroshi Mamitsuka:
Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms. NeurIPS 2018: 6902-6910 - 2017
- [c3]Makoto Yamada, Wenzhao Lian, Amit Goyal, Jianhui Chen, Kishan Wimalawarne, Suleiman A. Khan, Samuel Kaski, Hiroshi Mamitsuka, Yi Chang:
Convex Factorization Machine for Toxicogenomics Prediction. KDD 2017: 1215-1224 - 2016
- [j1]Kishan Wimalawarne, Ryota Tomioka, Masashi Sugiyama:
Theoretical and Experimental Analyses of Tensor-Based Regression and Classification. Neural Comput. 28(4): 686-715 (2016) - 2015
- [i1]Kishan Wimalawarne, Ryota Tomioka, Masashi Sugiyama:
Theoretical and Experimental Analyses of Tensor-Based Regression and Classification. CoRR abs/1509.01770 (2015) - 2014
- [c2]Kishan Wimalawarne, Masashi Sugiyama, Ryota Tomioka:
Multitask learning meets tensor factorization: task imputation via convex optimization. NIPS 2014: 2825-2833 - 2013
- [c1]Mahendra Piraveenan, Kishan Wimalawarne, Dharshana Kasthurirathna:
Centrality and Composition of Four-Node Motifs in Metabolic Networks. ICCS 2013: 409-418
Coauthor Index
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