Papers
Knowing-How under Uncertainty (Extended Abstract)
Pavel Naumov, Jia Tao
Knowledge-Based Regularization in Generative Modeling
Naoya Takeishi, Yoshinobu Kawahara
Knowledge Enhanced Event Causality Identification with Mention Masking Generalizations
Jian Liu, Yubo Chen, Jun Zhao
Knowledge Graphs Enhanced Neural Machine Translation
Yang Zhao, Jiajun Zhang, Yu Zhou et al.
Knowledge Hypergraphs: Prediction Beyond Binary Relations
Bahare Fatemi, Perouz Taslakian, David Vazquez et al.
KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge
Peng Zhang, Jianye Hao, Weixun Wang et al.
k-SDPP: Fixed-Size Video Summarization via Sequential Determinantal Point Processes
Jiping Zheng, Ganfeng Lu
Label-Attended Hashing for Multi-Label Image Retrieval
Yanzhao Xie, Yu Liu, Yangtao Wang et al.
Label Distribution for Learning with Noisy Labels
Yun-Peng Liu, Ning Xu, Yu Zhang et al.
Label Enhancement for Label Distribution Learning via Prior Knowledge
Yongbiao Gao, Yu Zhang, Xin Geng
Lagrangian Decomposition for Classical Planning (Extended Abstract)
Florian Pommerening, Gabriele Röger, Malte Helmert et al.
Language Independent Sequence Labelling for Opinion Target Extraction (Extended Abstract)
Rodrigo Agerri, German Rigau
Large Scale Audiovisual Learning of Sounds with Weakly Labeled Data
Haytham M. Fayek, Anurag Kumar
Latent Regularized Generative Dual Adversarial Network For Abnormal Detection
Chengwei Chen, Jing Liu, Yuan Xie et al.
Learning and Solving Regular Decision Processes
Eden Abadi, Ronen I. Brafman
Learning Bayesian Networks Under Sparsity Constraints: A Parameterized Complexity Analysis
Niels Grüttemeier, Christian Komusiewicz
Learning Data-Driven Drug-Target-Disease Interaction via Neural Tensor Network
Huiyuan Chen, Jing Li
Learning for Graph Matching and Related Combinatorial Optimization Problems
Junchi Yan, Shuang Yang, Edwin Hancock
Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data
Rémi Viola, Rémi Emonet, Amaury Habrard et al.
Learning From Multi-Dimensional Partial Labels
Haobo Wang, Weiwei Liu, Yang Zhao et al.
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation
Tao He, Lianli Gao, Jingkuan Song et al.
Learning Interpretable Models in the Property Specification Language
Rajarshi Roy, Dana Fisman, Daniel Neider
Learning Interpretable Representations with Informative Entanglements
Ege Beyazıt, Doruk Tuncel, Xu Yuan et al.
Learning in the Wild with Incremental Skeptical Gaussian Processes
Andrea Bontempelli, Stefano Teso, Fausto Giunchiglia et al.
Learning Large Logic Programs By Going Beyond Entailment
Andrew Cropper, Sebastijan Dumančic