565 citations · 1.7k across the 68 of their papers we have counts for
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Factorized Multimodal Transformer for Multimodal Sequential Learning
Amir Zadeh, Chengfeng Mao, Kelly Shi +4
The complex world around us is inherently multimodal and sequential (continuous). Information is scattered across different modalities and requires multiple continuous sensors to b…
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization
Paul Pu Liang, Zhun Liu, Yao-Hung Hubert Tsai +3
There has been an increased interest in multimodal language processing including multimodal dialog, question answering, sentiment analysis, and speech recognition. However, natural…
Deep Gamblers: Learning to Abstain with Portfolio Theory
Liu Ziyin, Zhikang Wang, Paul Pu Liang +3
We deal with the \textit{selective classification} problem (supervised-learning problem with a rejection option), where we want to achieve the best performance at a certain level o…
Strong and Simple Baselines for Multimodal Utterance Embeddings
Paul Pu Liang, Yao Chong Lim, Yao-Hung Hubert Tsai +2
Human language is a rich multimodal signal consisting of spoken words, facial expressions, body gestures, and vocal intonations. Learning representations for these spoken utterance…
Multimodal Transformer for Unaligned Multimodal Language Sequences
Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang +3
Human language is often multimodal, which comprehends a mixture of natural language, facial gestures, and acoustic behaviors. However, two major challenges in modeling such multimo…
Variational Auto-Decoder: A Method for Neural Generative Modeling from Incomplete Data
Amir Zadeh, Yao-Chong Lim, Paul Pu Liang +1
Learning a generative model from partial data (data with missingness) is a challenging area of machine learning research. We study a specific implementation of the Auto-Encoding Va…