Deep Learning for Classical Japanese Literature

3 December 2018

Papers citing "Deep Learning for Classical Japanese Literature"

50 / 144 papers shown

Title
Exploiting the Potential Supervision Information of Clean Samples in Partial Label Learning Guangtai Wang Chi-man Vong Jintao Huang 27 0 0 14 May 2025
Dynamic Tsetlin Machine Accelerators for On-Chip Training at the Edge using FPGAs Gang Mao Tousif Rahman Sidharth Maheshwari Bob Pattison Zhuang Shao R. Shafik Alex Yakovlev 29 0 0 28 Apr 2025
FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization Hao Mark Chen S. Hu Wayne Luk Timothy M. Hospedales Hongxiang Fan MoMe 77 0 0 16 Mar 2025
Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model Moritz A. Zanger Pascal R. van der Vaart Wendelin Bohmer M. Spaan UQCV BDL 233 0 0 14 Mar 2025
Logit Disagreement: OoD Detection with Bayesian Neural Networks Kevin Raina UQCV BDL UD PER 66 0 0 24 Feb 2025
Efficient Learning Under Density Shift in Incremental Settings Using Cramér-Rao-Based Regularization Behraj Khan Behroz Mirza Nouman Durrani T. Syed 60 0 0 18 Feb 2025
Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks Jon Vadillo Roberto Santana J. A. Lozano Marta Z. Kwiatkowska BDL AAML 73 0 0 17 Feb 2025
Kolmogorov-Arnold Fourier Networks Jusheng Zhang Yijia Fan Kaitong Cai Keze Wang 68 0 0 09 Feb 2025
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification Ashim Dahal Saydul Akbar Murad Nick Rahimi 42 0 0 27 Jan 2025
Towards Scalable Topological Regularizers Hiu-Tung Wong Darrick Lee Hong Yan BDL 67 0 0 24 Jan 2025
On Accelerating Deep Neural Network Mutation Analysis by Neuron and Mutant Clustering Lauren Lyons Ali Ghanbari 78 0 0 22 Jan 2025
Task Singular Vectors: Reducing Task Interference in Model Merging Antonio Andrea Gargiulo Donato Crisostomi Maria Sofia Bucarelli Simone Scardapane Fabrizio Silvestri Emanuele Rodolà MoMe 95 9 0 26 Nov 2024
Understanding Generalization in Quantum Machine Learning with Margins Tak Hur Daniel K. Park AI4CE 39 1 0 11 Nov 2024
Breaking the Reclustering Barrier in Centroid-based Deep Clustering Lukas Miklautz Timo Klein Kevin Sidak Collin Leiber Thomas Lang Andrii Shkabrii Sebastian Tschiatschek Claudia Plant 44 1 0 04 Nov 2024
Conformal Risk Minimization with Variance Reduction Sima Noorani Orlando Romero Nicolò Dal Fabbro Hamed Hassani George Pappas 43 3 0 03 Nov 2024
Wolf2Pack: The AutoFusion Framework for Dynamic Parameter Fusion Bowen Tian Songning Lai Yutao Yue MoMe 35 0 0 08 Oct 2024
Expressivity of Neural Networks with Random Weights and Learned Biases Ezekiel Williams Avery Hee-Woon Ryoo Thomas Jiralerspong Alexandre Payeur M. Perich Luca Mazzucato Guillaume Lajoie 43 2 0 01 Jul 2024
Jacobian Descent for Multi-Objective Optimization Pierre Quinton Valérian Rey 41 3 0 23 Jun 2024
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport Jeonghwan Cheon Sang Wan Lee Se-Bum Paik OOD 242 1 0 27 May 2024
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation Pei Liu Luping Ji EDL 36 4 0 07 May 2024
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions Khai Nguyen Nhat Ho 47 3 0 23 Apr 2024
LancBiO: dynamic Lanczos-aided bilevel optimization via Krylov subspace Bin Gao Yan Yang Ya-xiang Yuan 46 2 0 04 Apr 2024
TaylorGrid: Towards Fast and High-Quality Implicit Field Learning via Direct Taylor-based Grid Optimization Renyi Mao Qingshan Xu Peng Zheng Ye Wang Tieru Wu Rui Ma 42 0 0 22 Feb 2024
Graph Cuts with Arbitrary Size Constraints Through Optimal Transport Chakib Fettal Lazhar Labiod M. Nadif OT 21 1 0 07 Feb 2024
Second-Order Uncertainty Quantification: Variance-Based Measures Yusuf Sale Paul Hofman Lisa Wimmer Eyke Hüllermeier Thomas Nagler PER UQCV UD 39 8 0 30 Dec 2023
Continual Invariant Risk Minimization Francesco Alesiani Shujian Yu Mathias Niepert OOD 31 1 0 21 Oct 2023
Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks Jun Guo Aishan Liu Xingyu Zheng Siyuan Liang Yisong Xiao Yichao Wu Xianglong Liu AAML 38 12 0 02 Aug 2023
Quantification of Uncertainty with Adversarial Models Kajetan Schweighofer L. Aichberger Mykyta Ielanskyi Günter Klambauer Sepp Hochreiter UQCV 42 14 0 06 Jul 2023
MNISQ: A Large-Scale Quantum Circuit Dataset for Machine Learning on/for Quantum Computers in the NISQ era Leonardo Placidi Ryuichiro Hataya Toshio Mori Koki Aoyama Hayata Morisaki K. Mitarai Keisuke Fujii 21 8 0 29 Jun 2023
A Universal Unbiased Method for Classification from Aggregate Observations Zixi Wei Lei Feng Bo Han Tongliang Liu Gang Niu Xiaofeng Zhu H. Shen 39 2 0 20 Jun 2023
Recognition of Handwritten Japanese Characters Using Ensemble of Convolutional Neural Networks Angel I. Solis Justin Zarkovacki J. Ly A. Atyabi 18 1 0 06 Jun 2023
Neural Fourier Transform: A General Approach to Equivariant Representation Learning Masanori Koyama Kenji Fukumizu Kohei Hayashi Takeru Miyato 44 8 0 29 May 2023
AUC Optimization from Multiple Unlabeled Datasets Zheng Xie Yu Liu Ming Li 73 1 0 25 May 2023
Training Energy-Based Normalizing Flow with Score-Matching Objectives Chen-Hao Chao Wei-Fang Sun Yen-Chang Hsu Z. Kira Chun-Yi Lee 33 3 0 24 May 2023
Utility-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning Xiaoli Tang Han Yu FedML 38 17 0 11 May 2023
Rubik's Optical Neural Networks: Multi-task Learning with Physics-aware Rotation Architecture Yingjie Li Weilu Gao Cunxi Yu 30 3 0 25 Apr 2023
Learning Fractals by Gradient Descent Cheng-Hao Tu Hong-You Chen David Carlyn Wei-Lun Chao 25 2 0 14 Mar 2023
Inversion dynamics of class manifolds in deep learning reveals tradeoffs underlying generalisation Simone Ciceri Lorenzo Cassani Matteo Osella P. Rotondo P. Pizzochero M. Gherardi 44 7 0 09 Mar 2023
U-Statistics for Importance-Weighted Variational Inference Javier Burroni Kenta Takatsu Justin Domke Daniel Sheldon 18 1 0 27 Feb 2023
A Gradient Boosting Approach for Training Convolutional and Deep Neural Networks S. Emami Gonzalo Martínez-Munoz 20 6 0 22 Feb 2023
Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics Nihal Murali A. Puli Ke Yu Rajesh Ranganath Kayhan Batmanghelich AAML 43 8 0 18 Feb 2023
Algorithm Selection for Deep Active Learning with Imbalanced Datasets Jifan Zhang Shuai Shao Saurabh Verma Robert D. Nowak 26 20 0 14 Feb 2023
Variational Information Pursuit for Interpretable Predictions Aditya Chattopadhyay Kwan Ho Ryan Chan B. Haeffele D. Geman René Vidal DRL 24 11 0 06 Feb 2023
Learning Functional Transduction Mathieu Chalvidal Thomas Serre Rufin VanRullen AI4CE 50 2 0 01 Feb 2023
LegendreTron: Uprising Proper Multiclass Loss Learning Kevin Lam Christian J. Walder S. Penev Richard Nock 55 0 0 27 Jan 2023
Noncommutative $C^$ -algebra Net: Learning Neural Networks with Powerful Product Structure in $C^$ -algebra Ryuichiro Hataya Yuka Hashimoto 52 4 0 26 Jan 2023
Learning Compact Features via In-Training Representation Alignment X. Li Xiangrui Li Deng Pan Yao Qiang D. Zhu OOD 21 3 0 23 Nov 2022
Impact of Redundancy on Resilience in Distributed Optimization and Learning Shuo Liu Nirupam Gupta Nitin H. Vaidya 39 2 0 16 Nov 2022
IRNet: Iterative Refinement Network for Noisy Partial Label Learning Zheng Lian Ming Xu Lang Chen Guoying Zhao B. Liu Jianhua Tao NoLa 24 4 0 09 Nov 2022
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models Songsong Xiong Georgios Tziafas Hamidreza Kasaei ViT 31 3 0 03 Oct 2022