| 2021 | An Aligned Subgraph Kernel Based on Discrete-Time Quantum Walk. | Kai Liu, Lulu Wang, Yi Zhang |
| 2021 | A Partial Label Metric Learning Algorithm for Class Imbalanced Data. | Wenpeng Liu, Li Wang, Jie Chen, Yu Zhou, Ruirui Zheng, Jianjun He |
| 2021 | An online semi-definite programming with a generalised log-determinant regularizer and its applications. | Yaxiong Liu, Ken-ichiro Moridomi, Kohei Hatano, Eiji Takimoto |
| 2021 | Multi-factor Memory Attentive Model for Knowledge Tracing. | Congjie Liu, Xiaoguang Li |
| 2021 | CTS2: Time Series Smoothing with Constrained Reinforcement Learning. | Yongshuai Liu, Xin Liu |
| 2021 | Expert advice problem with noisy low rank loss. | Yaxiong Liu, Xuanke Jiang, Kohei Hatano, Eiji Takimoto |
| 2021 | Multi-Branch Network for Cross-Subject EEG-based Emotion Recognition. | Guang Lin, Li Zhu, Bin Ren, Yiteng Hu, Jianhai Zhang |
| 2021 | Speaker Diarization as a Fully Online Bandit Learning Problem in MiniVox. | Baihan Lin, Xinxin Zhang |
| 2021 | Dynamic Popularity-Aware Contrastive Learning for Recommendation. | Fangquan Lin, Wei Jiang, Jihai Zhang, Cheng Yang |
| 2021 | Robust Regression for Monocular Depth Estimation. | Julian Lienen, Nils Nommensen, Ralph Ewerth, Eyke Hllermeier |
| 2021 | Lifelong Learning with Sketched Structural Regularization. | Haoran Li, Aditya Krishnan, Jingfeng Wu, Soheil Kolouri, Praveen K. Pilly, Vladimir Braverman |
| 2021 | DPOQ: Dynamic Precision Onion Quantization. | Bowen Li, Kai Huang, Siang Chen, Dongliang Xiong, Luc Claesen |
| 2021 | Scaling Average-Linkage via Sparse Cluster Embeddings. | Thomas Lavastida, Kefu Lu, Benjamin Moseley, Yuyan Wang |
| 2021 | Open Images V5 Text Annotation and Yet Another Mask Text Spotter. | Ilya Krylov, Sergei Nosov, Vladislav Sovrasov |
| 2021 | Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning. | Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski |
| 2021 | Geometric Value Iteration: Dynamic Error-Aware KL Regularization for Reinforcement Learning. | Toshinori Kitamura, Lingwei Zhu, Takamitsu Matsubara |
| 2021 | Augmenting Imbalanced Time-series Data via Adversarial Perturbation in Latent Space. | Beomsoo Kim, Jang-Ho Choi, Jaegul Choo |
| 2021 | Improving Hashing Algorithms for Similarity Search \textitvia MLE and the Control Variates Trick. | Keegan Kang, Sergey Kushnarev, Wong Wei Pin, Rameshwar Pratap, Haikal Yeo, Yijia Chen |
| 2021 | Contrastive Neural Processes for Self-Supervised Learning. | Konstantinos Kallidromitis, Denis A. Gudovskiy, Kazuki Kozuka, Ohama Iku, Luca Rigazio |
| 2021 | Collaborative Novelty Detection for Distributed Data by a Probabilistic Method. | Akira Imakura, Xiucai Ye, Tetsuya Sakurai |
| 2021 | calibrated adversarial training. | Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy |
| 2021 | Feature Convolutional Networks. | He Hu |
| 2021 | Multi-stream based marked point process. | Sujun Hong, Hirotaka Hachiya |
| 2021 | NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters. | Yoichi Hirose, Nozomu Yoshinari, Shinichi Shirakawa |
| 2021 | Meta-Model-Based Meta-Policy Optimization. | Takuya Hiraoka, Takahisa Imagawa, Voot Tangkaratt, Takayuki Osa, Takashi Onishi, Yoshimasa Tsuruoka |