most citedDeep Heterogeneous Autoencoders for Collaborative Filtering

6 citations · 11 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG2019

Learning Classifiers on Positive and Unlabeled Data with Policy Gradient

Tianyu Li, Chien-Chih Wang, Yukun Ma +4

Existing algorithms aiming to learn a binary classifier from positive (P) and unlabeled (U) data generally require estimating the class prior or label noises ahead of building a cl…

econ.EM2019

Multiway Cluster Robust Double/Debiased Machine Learning

Harold D. Chiang, Kengo Kato, Yukun Ma +1

This paper investigates double/debiased machine learning (DML) under multiway clustered sampling environments. We propose a novel multiway cross fitting algorithm and a multiway DM…

cs.CV2019

Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization

Zhuoran Yu, Aojun Zhou, Yukun Ma +3

Standard convolutional neural networks(CNNs) require consistent image resolutions in both training and testing phase. However, in practice, testing with smaller image sizes is nece…

cs.CL20195 cited

Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning

Haiyun Peng, Yukun Ma, Soujanya Poria +2

The Chinese pronunciation system offers two characteristics that distinguish it from other languages: deep phonemic orthography and intonation variations. We are the first to argue…

cs.LG20186 cited

Deep Heterogeneous Autoencoders for Collaborative Filtering

Tianyu Li, Yukun Ma, Jiu Xu +3

This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems. We propose a model that learns a shared feature space from het…

cs.CL2018

Concept-Based Embeddings for Natural Language Processing

Yukun Ma, Erik Cambria

In this work, we focus on effectively leveraging and integrating information from concept-level as well as word-level via projecting concepts and words into a lower dimensional spa…