Papers
Tangent Convolutions for Dense Prediction in 3D
Maxim Tatarchenko, Jaesik Park, Vladlen Koltun et al.
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
Amartya Sanyal, Matt Kusner, Adria Gascon et al.
Targeted Syntactic Evaluation of Language Models
Rebecca Marvin, Tal Linzen
Target Foresight Based Attention for Neural Machine Translation
Xintong Li, Lemao Liu, Zhaopeng Tu et al.
Target-Sensitive Memory Networks for Aspect Sentiment Classification
Shuai Wang, Sahisnu Mazumder, Bing Liu et al.
Task-Aware Image Downscaling
Heewon Kim, Myungsub Choi, Bee Lim et al.
Task-Driven Convolutional Recurrent Models of the Visual System
Aran Nayebi, Daniel Bear, Jonas Kubilius et al.
Task-driven Webpage Saliency
Quanlong Zheng, Jianbo Jiao, Ying Cao et al.
Task-Embedded Control Networks for Few-Shot Imitation Learning
Stephen James, Michael Bloesch, Andrew J. Davison
Task-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference
Chuxu Zhang, Lu Yu, Xiangliang Zhang et al.
Taskonomy: Disentangling Task Transfer Learning
Amir R. Zamir, Alexander Sax, William Shen et al.
Task-oriented Dialogue System for Automatic Diagnosis
Zhongyu Wei, Qianlong Liu, Baolin Peng et al.
Task-oriented Word Embedding for Text Classification
Qian Liu, Heyan Huang, Yang Gao et al.
Task Specific Sentence Embeddings for ASR Error Detection
Sahar Ghannay, Yannick Estève, Nathalie Camelin
Taylor’s law for Human Linguistic Sequences
Tatsuru Kobayashi, Kumiko Tanaka-Ishii
TBN: Convolutional Neural Network with Ternary Inputs and Binary Weights
Diwen Wan, Fumin Shen, Li Liu et al.
TCS Research at SemEval-2018 Task 1: Learning Robust Representations using Multi-Attention Architecture
Hardik Meisheri, Lipika Dey
TDNN: A Two-stage Deep Neural Network for Prompt-independent Automated Essay Scoring
Cancan Jin, Ben He, Kai Hui et al.
TDNN-based Multilingual Speech Recognition System for Low Resource Indian Languages
Noor Fathima, Tanvina Patel, Mahima C et al.
TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning
Artemij Amiranashvili, Alexey Dosovitskiy, Vladlen Koltun et al.
Teacher Improves Learning by Selecting a Training Subset
Yuzhe Ma, Robert Nowak, Philippe Rigollet et al.
Teaching Categories to Human Learners With Visual Explanations
Oisin Mac Aodha, Shihan Su, Yuxin Chen et al.
Teaching Inverse Reinforcement Learners via Features and Demonstrations
Luis Haug, Sebastian Tschiatschek, Adish Singla
Teaching Machines to Ask Questions
Kaichun Yao, Libo Zhang, Tiejian Luo et al.
Teaching Machines to Understand Baseball Games: Large-Scale Baseball Video Database for Multiple Video Understanding Tasks
Minho Shim, Young Hwi Kim, Kyungmin Kim et al.