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2020 – today
- 2023
[j46]Ryuta Yamaguchi, Kanami Ikeda
, Osanori Koyama, Makoto Yamada:
Features and Properties of Single-Pixel Imaging Using Speckle Patterns Generated by Multi-Core Fiber. IEEE Access 11: 55326-55333 (2023)- [j45]Yanbin Liu, Girish Dwivedi, Farid Boussaïd, Frank M. Sanfilippo, Makoto Yamada, Mohammed Bennamoun:
Inflating 2D convolution weights for efficient generation of 3D medical images. Comput. Methods Programs Biomed. 240: 107685 (2023) - [j44]Qiang Huang, Makoto Yamada, Yuan Tian, Dinesh Singh, Yi Chang:
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 35(7): 6968-6972 (2023) - [j43]Yuki Takezawa, Kenta Niwa, Makoto Yamada:
Communication Compression for Decentralized Learning With Operator Splitting Methods. IEEE Trans. Signal Inf. Process. over Networks 9: 581-595 (2023) - [c96]Ryuichiro Hataya, Makoto Yamada:
Nyström Method for Accurate and Scalable Implicit Differentiation. AISTATS 2023: 4643-4654 - [c95]Mari Saito, Takato Okudo, Makoto Yamada, Seiji Yamada:
Identifying Visitor's Paintings Appreciation for AI Audio Guide in Museums. ICAART (2) 2023: 55-64 - [c94]Weijie Liu, Jiahao Xie, Chao Zhang, Makoto Yamada, Nenggan Zheng, Hui Qian:
Robust Graph Dictionary Learning. ICLR 2023 - [c93]Dinesh Singh, Héctor Climente-González, Mathis Petrovich, Eiryo Kawakami, Makoto Yamada:
FsNet: Feature Selection Network on High-dimensional Biological Data. IJCNN 2023: 1-9 - [i56]Ayato Toyokuni, Makoto Yamada:
Structural Explanations for Graph Neural Networks using HSIC. CoRR abs/2302.02139 (2023) - [i55]Marco Fiorucci, Peter Naylor, Makoto Yamada:
Optimal Transport for Change Detection on LiDAR Point Clouds. CoRR abs/2302.07025 (2023) - [i54]Ryuichiro Hataya, Makoto Yamada:
Nystrom Method for Accurate and Scalable Implicit Differentiation. CoRR abs/2302.09726 (2023) - [i53]Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada:
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence. CoRR abs/2305.11420 (2023) - [i52]Peter Naylor, Diego Di Carlo, Arianna Traviglia, Makoto Yamada, Marco Fiorucci:
Implicit neural representation for change detection. CoRR abs/2307.15428 (2023) - 2022
- [j42]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Poincare: Recommending Publication Venues via Treatment Effect Estimation. J. Informetrics 16(2): 101283 (2022) - [j41]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Constant Time Graph Neural Networks. ACM Trans. Knowl. Discov. Data 16(5): 92:1-92:31 (2022) - [j40]Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi:
Approximating 1-Wasserstein Distance with Trees. Trans. Mach. Learn. Res. 2022 (2022) - [c92]Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada:
Fixed Support Tree-Sliced Wasserstein Barycenter. AISTATS 2022: 1120-1137 - [c91]Benjamin Poignard, Peter J. Naylor, Héctor Climente-González, Makoto Yamada:
Feature screening with kernel knockoffs. AISTATS 2022: 1935-1974 - [c90]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CIKM 2022: 4444-4448 - [c89]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Re-evaluating Word Mover's Distance. ICML 2022: 19231-19249 - [c88]Makoto Yamada, Tsunenori Mine:
Modality estimation methods in internal training reflection texts using BERT. IIAI-AAI 2022: 118-123 - [c87]Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada:
Feature-Robust Optimal Transport for High-Dimensional Data. ECML/PKDD (5) 2022: 291-307 - [c86]Yoichi Chikahara, Makoto Yamada, Hisashi Kashima:
Feature selection for discovering distributional treatment effect modifiers. UAI 2022: 400-410 - [i51]Yuki Takezawa, Kenta Niwa, Makoto Yamada:
Communication Compression for Decentralized Learning with Operator Splitting Methods. CoRR abs/2205.03779 (2022) - [i50]Yuki Takezawa, Kenta Niwa, Makoto Yamada:
Theoretical Analysis of Primal-Dual Algorithm for Non-Convex Stochastic Decentralized Optimization. CoRR abs/2205.11979 (2022) - [i49]Yoichi Chikahara, Makoto Yamada, Hisashi Kashima:
Feature Selection for Discovering Distributional Treatment Effect Modifiers. CoRR abs/2206.00516 (2022) - [i48]Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi:
Approximating 1-Wasserstein Distance with Trees. CoRR abs/2206.12116 (2022) - [i47]Peter Naylor, Yao-Hung Hubert Tsai, Marick Laé, Makoto Yamada:
Scale dependant layer for self-supervised nuclei encoding. CoRR abs/2207.10950 (2022) - [i46]Yanbin Liu, Girish Dwivedi, Farid Boussaïd, Frank M. Sanfilippo, Makoto Yamada, Mohammed Bennamoun:
Inflating 2D Convolution Weights for Efficient Generation of 3D Medical Images. CoRR abs/2208.03934 (2022) - [i45]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CoRR abs/2208.09862 (2022) - [i44]Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada:
Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data. CoRR abs/2209.15505 (2022) - 2021
- [c85]Tam Le, Nhat Ho, Makoto Yamada:
Flow-based Alignment Approaches for Probability Measures in Different Spaces. AISTATS 2021: 3934-3942 - [c84]Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada:
Computationally Efficient Wasserstein Loss for Structured Labels. EACL (Student Research Workshop) 2021: 1-7 - [c83]Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada:
Post-selection inference with HSIC-Lasso. ICML 2021: 3439-3448 - [c82]Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne:
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. ICML 2021: 8084-8095 - [c81]Yuki Takezawa, Ryoma Sato, Makoto Yamada:
Supervised Tree-Wasserstein Distance. ICML 2021: 10086-10095 - [c80]Hiroaki Yamada, Makoto Yamada:
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares. NeurIPS 2021: 14645-14655 - [c79]Tam Le, Truyen Nguyen, Makoto Yamada, Jose H. Blanchet, Viet Anh Nguyen:
Adversarial Regression with Doubly Non-negative Weighting Matrices. NeurIPS 2021: 16964-16976 - [c78]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 - [c77]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Random Features Strengthen Graph Neural Networks. SDM 2021: 333-341 - [i43]Yuki Takezawa, Ryoma Sato, Makoto Yamada:
Supervised Tree-Wasserstein Distance. CoRR abs/2101.11520 (2021) - [i42]Hiroaki Yamada, Makoto Yamada:
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares. CoRR abs/2102.04108 (2021) - [i41]Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada:
Computationally Efficient Wasserstein Loss for Structured Labels. CoRR abs/2103.00899 (2021) - [i40]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Re-evaluating Word Mover's Distance. CoRR abs/2105.14403 (2021) - [i39]Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada:
Fixed Support Tree-Sliced Wasserstein Barycenter. CoRR abs/2109.03431 (2021) - [i38]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) - [i37]Hardik Tankaria, Dinesh Singh, Makoto Yamada:
Nys-Curve: Nyström-Approximated Curvature for Stochastic Optimization. CoRR abs/2110.08577 (2021) - 2020
- [j39]Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka:
Scaled Coupled Norms and Coupled Higher-Order Tensor Completion. Neural Comput. 32(2): 447-484 (2020) - [c76]Qiang Huang, Tingyu Xia, Huiyan Sun, Makoto Yamada, Yi Chang:
Unsupervised Nonlinear Feature Selection from High-Dimensional Signed Networks. AAAI 2020: 4182-4189 - [c75]Benjamin Poignard, Makoto Yamada:
Sparse Hilbert-Schmidt Independence Criterion Regression. AISTATS 2020: 538-548 - [c74]Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira:
More Powerful Selective Kernel Tests for Feature Selection. AISTATS 2020: 820-830 - [c73]Yanbin Liu, Linchao Zhu, Makoto Yamada, Yi Yang:
Semantic Correspondence as an Optimal Transport Problem. CVPR 2020: 4462-4471 - [c72]Luu Huu Phuc, Koh Takeuchi, Makoto Yamada, Hisashi Kashima:
Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport. DSAA 2020: 245-254 - [c71]Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada:
Topological Bayesian Optimization with Persistence Diagrams. ECAI 2020: 1483-1490 - [c70]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Fast Unbalanced Optimal Transport on a Tree. NeurIPS 2020 - [c69]Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Neural Methods for Point-wise Dependency Estimation. NeurIPS 2020 - [i36]Qiang Huang, Makoto Yamada, Yuan Tian, Dinesh Singh, Dawei Yin, Yi Chang:
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks. CoRR abs/2001.06216 (2020) - [i35]Dinesh Singh, Makoto Yamada:
FsNet: Feature Selection Network on High-dimensional Biological Data. CoRR abs/2001.08322 (2020) - [i34]Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima:
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces. CoRR abs/2002.01615 (2020) - [i33]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Random Features Strengthen Graph Neural Networks. CoRR abs/2002.03155 (2020) - [i32]Mathis Petrovich, Makoto Yamada:
Fast local linear regression with anchor regularization. CoRR abs/2003.05747 (2020) - [i31]Ziyin Liu, Zihao Wang, Makoto Yamada, Masahito Ueda:
Volumization as a Natural Generalization of Weight Decay. CoRR abs/2003.11243 (2020) - [i30]Mathis Petrovich, Chao Liang, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada:
Feature Robust Optimal Transport for High-dimensional Data. CoRR abs/2005.12123 (2020) - [i29]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Fast Unbalanced Optimal Transport on Tree. CoRR abs/2006.02703 (2020) - [i28]Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Neural Methods for Point-wise Dependency Estimation. CoRR abs/2006.05553 (2020) - [i27]Vu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne:
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search. CoRR abs/2006.07593 (2020) - [i26]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Poincare: Recommending Publication Venues via Treatment Effect Estimation. CoRR abs/2010.09157 (2020)
2010 – 2019
- 2019
- [j38]Héctor Climente-González, Chloé-Agathe Azencott, Samuel Kaski, Makoto Yamada:
Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data. Bioinform. 35(14): i427-i435 (2019) - [j37]Heewon Park, Makoto Yamada, Seiya Imoto, Satoru Miyano:
Robust Sample-Specific Stability Selection with Effective Error Control. J. Comput. Biol. 26(3): 202-217 (2019) - [c68]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Learning to Sample Hard Instances for Graph Algorithms. ACML 2019: 503-518 - [c67]Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel. EMNLP/IJCNLP (1) 2019: 4343-4352 - [c66]Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu:
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. ICLR (Poster) 2019 - [c65]Kiyosato Someya, Yuichi Hiroi, Makoto Yamada, Yuta Itoh:
OSTNet: Calibration Method for Optical See-Through Head-Mounted Displays via Non-Parametric Distortion Map Generation. ISMAR Adjunct 2019: 259-260 - [c64]Makoto Yamada, Tomoya Sato, Hiroyuki Chishiro, Shinpei Kato:
Vision-based Localization using a Monocular Camera in the Rain. ITSC 2019: 293-298 - [c63]Daiki Tanaka, Makoto Yamada, Hisashi Kashima, Takeshi Kishikawa, Tomoyuki Haga, Takamitsu Sasaki:
In-Vehicle Network Intrusion Detection and Explanation Using Density Ratio Estimation. ITSC 2019: 2238-2243 - [c62]Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum:
Kernel Stein Tests for Multiple Model Comparison. NeurIPS 2019: 2240-2250 - [c61]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. NeurIPS 2019: 4083-4092 - [c60]Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi:
Tree-Sliced Variants of Wasserstein Distances. NeurIPS 2019: 12283-12294 - [c59]Yohei Kameyama, Kanami Ikeda, Osanori Koyama, Makoto Yamada:
Single-pixel Imaging using a Multi-core Fiber. OECC/PSC 2019: 1-3 - [c58]Keigo Minou, Seiya Aso, Osanori Koyama, Minoru Yamaguchi, Yudai Tomioka, Yuki Ogura, Kanami Ikeda, Makoto Yamada:
OpenFlow-based Remote Control of Optical Switch Employing IoT Device in AWG-STAR with Loop-back Function. OECC/PSC 2019: 1-3 - [c57]Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima:
Context-Regularized Neural Collaborative Filtering for Game App Recommendation. RecSys (Late-Breaking Results) 2019: 16-20 - [c56]Naotaka Tomita, Kouki Nagamune, Makoto Yamada:
Effect of Cutting Maneuvers on Center of Foot Pressure Movement in University Tennis Players. SMC 2019: 1177-1181 - [i25]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Constant Time Graph Neural Networks. CoRR abs/1901.07868 (2019) - [i24]Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi:
Tree-Sliced Approximation of Wasserstein Distances. CoRR abs/1902.00342 (2019) - [i23]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Learning to Find Hard Instances of Graph Problems. CoRR abs/1902.09700 (2019) - [i22]Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada:
Topological Bayesian Optimization with Persistence Diagrams. CoRR abs/1902.09722 (2019) - [i21]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. CoRR abs/1905.10261 (2019) - [i20]Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov:
Transformer Dissection: An Unified Understanding for Transformer's Attention via the Lens of Kernel. CoRR abs/1908.11775 (2019) - [i19]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) - [i18]Tam Le, Nhat Ho, Makoto Yamada:
Computationally Efficient Tree Variants of Gromov-Wasserstein. CoRR abs/1910.04462 (2019) - [i17]Tam Le, Viet Huynh, Nhat Ho, Dinh Q. Phung, Makoto Yamada:
On Scalable Variant of Wasserstein Barycenter. CoRR abs/1910.04483 (2019) - [i16]Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira:
More Powerful Selective Kernel Tests for Feature Selection. CoRR abs/1910.06134 (2019) - [i15]Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum:
Kernel Stein Tests for Multiple Model Comparison. CoRR abs/1910.12252 (2019) - 2018
- [j36]Toshinori Murakami, Osanori Koyama, Akihiro Kusama, Makoto Matsui, Makoto Yamada:
Loss peak adjustment of long period fiber grating fabricated with CO2 laser by applying tension. IEICE Electron. Express 15(23): 20180844 (2018) - [j35]Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka:
Convex Coupled Matrix and Tensor Completion. Neural Comput. 30(11) (2018) - [j34]Makoto Yamada, Jiliang Tang, Jose Lugo-Martinez, Ermin Hodzic, Raunak Shrestha, Avishek Saha, Hua Ouyang, Dawei Yin, Hiroshi Mamitsuka, Süleyman Cenk Sahinalp, Predrag Radivojac, Filippo Menczer, Yi Chang:
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data. IEEE Trans. Knowl. Data Eng. 30(7): 1352-1365 (2018) - [j33]Yue Wang, Dawei Yin, Luo Jie, Pengyuan Wang, Makoto Yamada, Yi Chang, Qiaozhu Mei:
Optimizing Whole-Page Presentation for Web Search. ACM Trans. Web 12(3): 19:1-19:25 (2018) - [c55]Makoto Yamada, Yuta Umezu, Kenji Fukumizu, Ichiro Takeuchi:
Post Selection Inference with Kernels. AISTATS 2018: 152-160 - [c54]Tanmoy Mukherjee, Makoto Yamada, Timothy M. Hospedales:
Learning Unsupervised Word Translations Without Adversaries. EMNLP 2018: 627-632 - [c53]Kosuke Kikui, Yuta Itoh, Makoto Yamada, Yuta Sugiura, Maki Sugimoto:
Intra-/inter-user adaptation framework for wearable gesture sensing device. UbiComp 2018: 21-24 - [c52]Yao-Hung Hubert Tsai, Denny Wu, Makoto Yamada, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu:
Selecting the Best in GANs Family: a Post Selection Inference Framework. ICLR (Workshop) 2018 - [c51]Tam Le, Makoto Yamada:
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams. NeurIPS 2018: 10028-10039 - [c50]Kouki Nagamune, Makoto Yamada:
A Wearable Measurement System for Sole Pressure to Calculate Center of Pressure in Sports Activity. SMC 2018: 1333-1336 - [c49]Makoto Yamada, Kouki Nagamune:
A Development of Measurement System for Foot Pressure by Using Optical Force Sensors. WAC 2018: 1-5 - [i14]Tam Le, Makoto Yamada:
Riemannian Manifold Kernel for Persistence Diagrams. CoRR abs/1802.03569 (2018) - [i13]Denny Wu, Yixiu Zhao, Yao-Hung Hubert Tsai, Makoto Yamada, Ruslan Salakhutdinov:
"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study. CoRR abs/1802.05408 (2018) - [i12]Yao-Hung Hubert Tsai, Makoto Yamada, Denny Wu, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu:
Selecting the Best in GANs Family: a Post Selection Inference Framework. CoRR abs/1802.05411 (2018) - 2017
- [c48]Makoto Yamada, Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski:
Localized Lasso for High-Dimensional Regression. AISTATS 2017: 325-333 - [c47]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 - [i11]Makoto Yamada, Song Liu, Samuel Kaski:
Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation. CoRR abs/1702.06354 (2017) - [i10]Tanmoy Mukherjee, Makoto Yamada, Timothy M. Hospedales:
Deep Matching Autoencoders. CoRR abs/1711.06047 (2017) - 2016
- [j32]Makoto Yamada, Tsukasa Kondo, Kai Wakasa:
High Efficiency Machining for Integral Shaping from Simplicity Materials Using Five-Axis Machine Tools. Int. J. Autom. Technol. 10(5): 804-812 (2016) - [j31]Yi Chang, Makoto Yamada, Antonio Ortega, Yan Liu:
Lifecycle Modeling for Buzz Temporal Pattern Discovery. ACM Trans. Knowl. Discov. Data 11(2): 20:1-20:24 (2016) - [c46]Zornitsa Kozareva, Makoto Yamada:
Which Tumblr Post Should I Read Next? ACL (2) 2016 - [c45]Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu:
A Robust Convex Formulation for Ensemble Clustering. IJCAI 2016: 1476-1482 - [c44]Yi Chang, Jiliang Tang, Dawei Yin, Makoto Yamada, Yan Liu:
Timeline Summarization from Social Media with Life Cycle Models. IJCAI 2016: 3698-3704 - [c43]Tomoharu Iwata, Makoto Yamada:
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models. NIPS 2016: 1136-1144 - [c42]Takayuki Mizuno, Kohki Shibahara, Hirotaka Ono, Y. Abe, Yutaka Miyamoto, Feihong Ye, Toshio Morioka, Yusuke Sasaki, Yoshimichi Amma, Katsuhiro Takenaga, S. Matsuo, Kazuhiko Aikawa, Kunimasa Saitoh, Yongmin Jung, David J. Richardson, Klaus Pulverer, Marc Bohn, Makoto Yamada:
32-core Dense SDM unidirectional transmission of PDM-16QAM signals over 1600 km using crosstalk-managed single-mode heterogeneous multicore transmission line. OFC 2016: 1-3 - [c41]Kohki Shibahara, Takayuki Mizuno, Hidehiko Takara, H. Kawakami, D. Lee, Yutaka Miyamoto, S. Matsuo, Kunimasa Saitoh, Makoto Yamada:
Space-time coding-assisted transmission for mitigation of MDL impact on mode-division multiplexed signals. OFC 2016: 1-3 - [c40]Yue Wang, Dawei Yin, Luo Jie, Pengyuan Wang, Makoto Yamada, Yi Chang, Qiaozhu Mei:
Beyond Ranking: Optimizing Whole-Page Presentation. WSDM 2016: 103-112 - [i9]