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Publication search results
found 298 matches
- 2024
- Shao-Lun Huang, Anuran Makur, Gregory W. Wornell, Lizhong Zheng:
Universal Features for High-Dimensional Learning and Inference. Found. Trends Commun. Inf. Theory 21(1-2): 1-299 (2024) - Yanjin Peng, Lei Wang:
Two-Stage Online Debiased Lasso Estimation and Inference for High-Dimensional Quantile Regression with Streaming Data. J. Syst. Sci. Complex. 37(3): 1251-1270 (2024) - Jed A. Duersch:
Projective Integral Updates for High-Dimensional Variational Inference. SIAM/ASA J. Uncertain. Quantification 12(1): 69-100 (2024) - Ansgar Steland:
Flexible nonlinear inference and change-point testing of high-dimensional spectral density matrices. J. Multivar. Anal. 199: 105245 (2024) - Aref Einizade, Sepideh Hajipour Sardouie:
Iterative Pseudo-Sparse Partial Least Square and Its Higher Order Variant: Application to Inference From High-Dimensional Biosignals. IEEE Trans. Cogn. Dev. Syst. 16(1): 296-307 (2024) - Guangdong Xue, Jian Wang, Kai Zhang, Nikhil R. Pal:
High-Dimensional Fuzzy Inference Systems. IEEE Trans. Syst. Man Cybern. Syst. 54(1): 507-519 (2024) - Md Musfiqur Rahman, Murat Kocaoglu:
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference. CoRR abs/2401.01426 (2024) - Daniel MacKinlay, Russell Tsuchida, Daniel Edward Pagendam, Petra Kuhnert:
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems. CoRR abs/2402.08193 (2024) - Daniel Andrade:
Stable Training of Normalizing Flows for High-dimensional Variational Inference. CoRR abs/2402.16408 (2024) - Yaxin Fang, Faming Liang:
Causal-StoNet: Causal Inference for High-Dimensional Complex Data. CoRR abs/2403.18994 (2024) - 2023
- Nikolai Jannik Podlesny:
Quasi-identifier discovery to prevent privacy violating inferences in large high dimensional datasets. University of Potsdam, Germany, 2023 - Aristidis K. Nikoloulopoulos:
Efficient and feasible inference for high-dimensional normal copula regression models. Comput. Stat. Data Anal. 179: 107654 (2023) - Pedro Roberto Barbosa Rocha, João Lucas de Sousa Almeida, Marcos Sebastião De Paula Gomes, Alberto Costa Nogueira Junior:
Reduced-order modeling of the two-dimensional Rayleigh-Bénard convection flow through a non-intrusive operator inference. Eng. Appl. Artif. Intell. 126: 106923 (2023) - Michael C. Abbott, Benjamin B. Machta:
Far from Asymptopia: Unbiased High-Dimensional Inference Cannot Assume Unlimited Data. Entropy 25(3): 434 (2023) - Zhenyu Wei, Thomas C. M. Lee:
High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference. J. Comput. Graph. Stat. 32(1): 226-240 (2023) - Abhishek Kaul, Hongjin Zhang, Konstantinos Tsampourakis, George Michailidis:
Inference on the Change Point under a High Dimensional Covariance Shift. J. Mach. Learn. Res. 24: 168:1-168:68 (2023) - Yingzhi Xia, Qifeng Liao, Jinglai Li:
VI-DGP: A Variational Inference Method with Deep Generative Prior for Solving High-Dimensional Inverse Problems. J. Sci. Comput. 97(1): 16 (2023) - Brittany Green, Heng Lian, Yan Yu, Tianhai Zu:
Semiparametric penalized quadratic inference functions for longitudinal data in ultra-high dimensions. J. Multivar. Anal. 196: 105175 (2023) - Feiyu Jiang, Runmin Wang, Xiaofeng Shao:
Robust inference for change points in high dimension. J. Multivar. Anal. 193: 105114 (2023) - Lucas Kock, Nadja Klein, David J. Nott:
Correction to : Variational inference and sparsity in high-dimensional deep Gaussian mixture models. Stat. Comput. 33(1): 24 (2023) - Wayne Isaac Tan Uy, Yuepeng Wang, Yuxiao Wen, Benjamin Peherstorfer:
Active Operator Inference for Learning Low-Dimensional Dynamical-System Models from Noisy Data. SIAM J. Sci. Comput. 45(4) (2023) - Fang Dong, Huitian Wang, Dian Shen, Zhaowu Huang, Qiang He, Jinghui Zhang, Liangsheng Wen, Tingting Zhang:
Multi-Exit DNN Inference Acceleration Based on Multi-Dimensional Optimization for Edge Intelligence. IEEE Trans. Mob. Comput. 22(9): 5389-5405 (2023) - Yuqing Hu, Stéphane Pateux, Vincent Gripon:
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification. AISTATS 2023: 5899-5917 - Jasper Tan, Daniel LeJeune, Blake Mason, Hamid Javadi, Richard G. Baraniuk:
A Blessing of Dimensionality in Membership Inference through Regularization. AISTATS 2023: 10968-10993 - Yosuke Oyama, Akihiro Tabuchi, Atsushi Tokuhisa:
Accelerating AlphaFold2 Inference of Protein Three-Dimensional Structure on the Supercomputer Fugaku. FlexScience@HPDC 2023: 1-9 - David Mohaisen:
Understanding the Privacy Dimension of Wearables through Machine Learning-enabled Inferences. SNTA@HPDC 2023: 1 - Dake Chen, Yuke Zhang, Souvik Kundu, Chenghao Li, Peter A. Beerel:
RNA-ViT: Reduced-Dimension Approximate Normalized Attention Vision Transformers for Latency Efficient Private Inference. ICCAD 2023: 1-9 - Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop:
Conditional score-based diffusion models for Bayesian inference in infinite dimensions. NeurIPS 2023 - Licong Lin, Mufang Ying, Suvrojit Ghosh, Koulik Khamaru, Cun-Hui Zhang:
Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference. NeurIPS 2023 - Jann Spiess, Guido Imbens, Amar Venugopal:
Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control. NeurIPS 2023
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