output
20072026
most citedLINE: Large-scale Information Network Embedding

4.8k citations

Showing 2016Show all

37 papers · 1 filter

math.OC2016★ 3 cited

Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems

Quanming Yao, James T. Kwok, Fei Gao +2

The proximal gradient algorithm has been popularly used for convex optimization. Recently, it has also been extended for nonconvex problems, and the current state-of-the-art is the…

cs.CL2016★ 9 cited

Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots

Yu Wu, Wei Wu, Chen Xing +2

We study response selection for multi-turn conversation in retrieval-based chatbots. Existing work either concatenates utterances in context or matches a response with a highly abs…

cs.CV2016★ 23 cited

End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance

Yan Xu, Siyuan Shan, Ziming Qiu +5

In this paper, we propose an innovative end-to-end subtitle detection and recognition system for videos in East Asian languages. Our end-to-end system consists of multiple stages.…

cs.CV2016★ 483 cited

An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data

Sijie Song, Cuiling Lan, Junliang Xing +2

Human action recognition is an important task in computer vision. Extracting discriminative spatial and temporal features to model the spatial and temporal evolutions of different…

cs.CV2016★ 37 cited

Fully Convolutional Instance-aware Semantic Segmentation

Yi Li, Haozhi Qi, Jifeng Dai +2

We present the first fully convolutional end-to-end solution for instance-aware semantic segmentation task. It inherits all the merits of FCNs for semantic segmentation and instanc…

cs.CV2016

Learning Multi-level Features For Sensor-based Human Action Recognition

Yan Xu, Zhengyang Shen, Xin Zhang +5

This paper proposes a multi-level feature learning framework for human action recognition using a single body-worn inertial sensor. The framework consists of three phases, respecti…