618 citations · 2.3k across the 40 of their papers we have counts for
42 papers
Multimodal Intelligence: Representation Learning, Information Fusion, and Applications
Chao Zhang, Zichao Yang, Xiaodong He +1
Deep learning methods have revolutionized speech recognition, image recognition, and natural language processing since 2010. Each of these tasks involves a single modality in their…
From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation
Yu Liu, Li Deng, Jianshu Chen +1
Many important classification problems, such as object classification, speech recognition, and machine translation, have been tackled by the supervised learning paradigm in the pas…
Attentive Tensor Product Learning
Qiuyuan Huang, Li Deng, Dapeng Wu +2
This paper proposes a new architecture - Attentive Tensor Product Learning (ATPL) - to represent grammatical structures in deep learning models. ATPL is a new architecture to bridg…
BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems
Zachary Lipton, Xiujun Li, Jianfeng Gao +3
We present a new algorithm that significantly improves the efficiency of exploration for deep Q-learning agents in dialogue systems. Our agents explore via Thompson sampling, drawi…
A Neural-Symbolic Approach to Design of CAPTCHA
Qiuyuan Huang, Paul Smolensky, Xiaodong He +2
CAPTCHAs based on reading text are susceptible to machine-learning-based attacks due to recent significant advances in deep learning (DL). To address this, this paper promotes imag…
Tensor Product Generation Networks for Deep NLP Modeling
Qiuyuan Huang, Paul Smolensky, Xiaodong He +2
We present a new approach to the design of deep networks for natural language processing (NLP), based on the general technique of Tensor Product Representations (TPRs) for encoding…