Papers
Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation
Zhi Tian, Tong He, Chunhua Shen et al.
Decoding EEG by Visual-guided Deep Neural Networks
Zhicheng Jiao, Haoxuan You, Fan Yang et al.
Decomposable Neural Paraphrase Generation
Zichao Li, Xin Jiang, Lifeng Shang et al.
Decomposed Local Models for Coordinate Structure Parsing
Hiroki Teranishi, Hiroyuki Shindo, Yuji Matsumoto
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
Kaspar Märtens, Kieran Campbell, Christopher Yau
Decomposing Textual Information For Style Transfer
Ivan P. Yamshchikov, Viacheslav Shibaev, Aleksander Nagaev et al.
Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction
Debela Gemechu, Chris Reed
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
Hattie Zhou, Janice Lan, Rosanne Liu et al.
Deconstructing Supertagging into Multi-Task Sequence Prediction
Zhenqi Zhu, Anoop Sarkar
Decontamination of Mutual Contamination Models
Julian Katz-Samuels, Gilles Blanchard, Clayton Scott
Decorrelated Adversarial Learning for Age-Invariant Face Recognition
Hao Wang, Dihong Gong, Zhifeng Li et al.
Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering
Soravit Changpinyo, Bo Pang, Piyush Sharma et al.
Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering
Soravit Changpinyo, Bo Pang, Piyush Sharma et al.
Decoupled Weight Decay Regularization
Ilya Loshchilov, Frank Hutter
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses
Jerome Rony, Luiz G. Hafemann, Luiz S. Oliveira et al.
Decoupling Sparsity and Smoothness in the Dirichlet Variational Autoencoder Topic Model
Sophie Burkhardt, Stefan Kramer
Deep Active Learning for Anchor User Prediction
Anfeng Cheng, Chuan Zhou, Hong Yang et al.
Deep Active Learning with Adaptive Acquisition
Manuel Haussmann, Fred Hamprecht, Melih Kandemir
Deep Active Learning with a Neural Architecture Search
Yonatan Geifman, Ran El-Yaniv
Deep Adversarial Learning for NLP
William Yang Wang, Sameer Singh, Jiwei Li
Deep Adversarial Multi-view Clustering Network
Zhaoyang Li, Qianqian Wang, Zhiqiang Tao et al.
Deep Adversarial Social Recommendation
Wenqi Fan, Tyler Derr, Yao Ma et al.
DeepAnalyzer at SemEval-2019 Task 6: A deep learning-based ensemble method for identifying offensive tweets
Gretel Liz De la Peña, Paolo Rosso
Deep Anomaly Detection with Outlier Exposure
Dan Hendrycks, Mantas Mazeika, Thomas Dietterich
DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation
Huan Yan, Xiangning Chen, Chen Gao et al.