607 citations · 1.2k across the 36 of their papers we have counts for
8 papers · 1 filter
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning
Zheng Li, Xin Li, Ying Wei +3
Joint extraction of aspects and sentiments can be effectively formulated as a sequence labeling problem. However, such formulation hinders the effectiveness of supervised methods d…
L2RS: A Learning-to-Rescore Mechanism for Automatic Speech Recognition
Yuanfeng Song, Di Jiang, Xuefang Zhao +4
Modern Automatic Speech Recognition (ASR) systems primarily rely on scores from an Acoustic Model (AM) and a Language Model (LM) to rescore the N-best lists. With the abundance of…
Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction
Wenyi Xiao, Huan Zhao, Haojie Pan +3
An effective content recommendation in modern social media platforms should benefit both creators to bring genuine benefits to them and consumers to help them get really interestin…
Easy Transfer Learning By Exploiting Intra-domain Structures
Jindong Wang, Yiqiang Chen, Han Yu +2
Transfer learning aims at transferring knowledge from a well-labeled domain to a similar but different domain with limited or no labels. Unfortunately, existing learning-based meth…
Learning to Transfer Examples for Partial Domain Adaptation
Zhangjie Cao, Kaichao You, Mingsheng Long +2
Domain adaptation is critical for learning in new and unseen environments. With domain adversarial training, deep networks can learn disentangled and transferable features that eff…
AutoML @ NeurIPS 2018 challenge: Design and Results
Hugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon +5
We organized a competition on Autonomous Lifelong Machine Learning with Drift that was part of the competition program of NeurIPS 2018. This data driven competition asked participa…