Papers
Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features
Xiang Wang, Shaodi You, Xi Li et al.
Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing
Zilong Huang, Xinggang Wang, Jiasi Wang et al.
Weakly-supervised Video Summarization using Variational Encoder-Decoder and Web Prior
Sijia Cai, Wangmeng Zuo, Larry S. Davis et al.
Webly Supervised Learning Meets Zero-Shot Learning: A Hybrid Approach for Fine-Grained Classification
Li Niu, Ashok Veeraraghavan, Ashutosh Sabharwal
WECA: A WordNet-Encoded Collocation-Attention Network for Homographic Pun Recognition
Yufeng Diao, Hongfei Lin, Di Wu et al.
Weeding out Conventionalized Metaphors: A Corpus of Novel Metaphor Annotations
Erik-Lân Do Dinh, Hannah Wieland, Iryna Gurevych
Weighted Bipolar Argumentation Graphs: Axioms and Semantics
Leila Amgoud, Jonathan Ben-Naim
Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning
Jiyan Yang, Yin-Lam Chow, Christopher Ré et al.
Weighted Tensor Decomposition for Learning Latent Variables with Partial Data
Omer Gottesman, Weiwei Pan, Finale Doshi-Velez
Weighting of Coda Voicing Cues: Glottalisation and Vowel Duration
Joshua Penney, Felicity Cox, Anita Szakay
Weighting Pitch Contour and Loudness Contour in Mandarin Tone Perception in Cochlear Implant Listeners
Qinglin Meng, Nengheng Zheng, Ambika Prasad Mishra et al.
Weighting Time-Frequency Representation of Speech Using Auditory Saliency for Automatic Speech Recognition
Cong-Thanh Do, Yannis Stylianou
Weightless: Lossy weight encoding for deep neural network compression
Brandon Reagan, Udit Gupta, Bob Adolf et al.
WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling
Hao Zhang, Bo Chen, Dandan Guo et al.
What Action Causes This? Towards Naive Physical Action-Effect Prediction
Qiaozi Gao, Shaohua Yang, Joyce Chai et al.
What can we learn from Semantic Tagging?
Mostafa Abdou, Artur Kulmizev, Vinit Ravishankar et al.
What do character-level models learn about morphology? The case of dependency parsing
Clara Vania, Andreas Grivas, Adam Lopez
What Do Classifiers Actually Learn? a Case Study on Emotion Recognition Datasets
Patrick Meyer, Eric Buschermöhle, Tim Fingscheidt
What Do Deep Networks Like to See?
Sebastian Palacio, Joachim Folz, Jörn Hees et al.
What do I Annotate Next? An Empirical Study of Active Learning for Action Localization
Fabian Caba Heilbron, Joon-Young Lee, Hailin Jin et al.
What do RNN Language Models Learn about Filler–Gap Dependencies?
Ethan Wilcox, Roger Levy, Takashi Morita et al.
What Game Are We Playing? End-to-end Learning in Normal and Extensive Form Games
Chun Kai Ling, Fei Fang, J. Zico Kolter
What Have We Learned From Deep Representations for Action Recognition?
Christoph Feichtenhofer, Axel Pinz, Richard P. Wildes et al.
What It Takes to Achieve 100% Condition Accuracy on WikiSQL
Semih Yavuz, Izzeddin Gur, Yu Su et al.