Papers
Transductive Zero-Shot Learning with Visual Structure Constraint
Ziyu Wan, Dongdong Chen, Yan Li et al.
Transferable Normalization: Towards Improving Transferability of Deep Neural Networks
Ximei Wang, Ying Jin, Mingsheng Long et al.
Transfer Anomaly Detection by Inferring Latent Domain Representations
Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara
Transfer Learning via Minimizing the Performance Gap Between Domains
Boyu Wang, Jorge Mendez, Mingbo Cai et al.
Transfusion: Understanding Transfer Learning for Medical Imaging
Maithra Raghu, Chiyuan Zhang, Jon Kleinberg et al.
Tree-Sliced Variants of Wasserstein Distances
Tam Le, Makoto Yamada, Kenji Fukumizu et al.
Triad Constraints for Learning Causal Structure of Latent Variables
Ruichu Cai, Feng Xie, Clark Glymour et al.
Trivializations for Gradient-Based Optimization on Manifolds
Mario Lezcano Casado
Trust Region-Guided Proximal Policy Optimization
Yuhui Wang, Hao He, Xiaoyang Tan et al.
Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels
Yihan Jiang, Hyeji Kim, Himanshu Asnani et al.
Twin Auxilary Classifiers GAN
Mingming Gong, Yanwu Xu, Chunyuan Li et al.
Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test
Lizhong Ding, Mengyang Yu, Li Liu et al.
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples
Tengyu Xu, Shaofeng Zou, Yingbin Liang
Ultra Fast Medoid Identification via Correlated Sequential Halving
Tavor Baharav, David Tse
Ultrametric Fitting by Gradient Descent
Giovanni Chierchia, Benjamin Perret
Uncertainty-based Continual Learning with Adaptive Regularization
Hongjoon Ahn, Sungmin Cha, Donggyu Lee et al.
Uncertainty on Asynchronous Time Event Prediction
Marin Biloš, Bertrand Charpentier, Stephan Günnemann
Unconstrained Monotonic Neural Networks
Antoine Wehenkel, Gilles Louppe
Uncoupled Regression from Pairwise Comparison Data
Liyuan Xu, Junya Honda, Gang Niu et al.
Understanding and Improving Layer Normalization
Jingjing Xu, Xu Sun, Zhiyuan Zhang et al.
Understanding Attention and Generalization in Graph Neural Networks
Boris Knyazev, Graham W. Taylor, Mohamed Amer
Understanding Sparse JL for Feature Hashing
Meena Jagadeesan
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
Nima Dehmamy, Albert-Laszlo Barabasi, Rose Yu
Understanding the Role of Momentum in Stochastic Gradient Methods
Igor Gitman, Hunter Lang, Pengchuan Zhang et al.
Unified Language Model Pre-training for Natural Language Understanding and Generation
Li Dong, Nan Yang, Wenhui Wang et al.