1 citations · 2 across the 3 of their papers we have counts for
6 papers
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
Yiwei Lyu, Paul Pu Liang, Hai Pham +4
Text style transfer aims to controllably generate text with targeted stylistic changes while maintaining core meaning from the source sentence constant. Many of the existing style…
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
Quang Minh Hoang, Trong Nghia Hoang, Hai Pham +1
We introduce a new scalable approximation for Gaussian processes with provable guarantees which hold simultaneously over its entire parameter space. Our approximation is obtained f…
Robust Handwriting Recognition with Limited and Noisy Data
Hai Pham, Amrith Setlur, Saket Dingliwal +7
Despite the advent of deep learning in computer vision, the general handwriting recognition problem is far from solved. Most existing approaches focus on handwriting datasets that…
Adaptive Sampling Distributed Stochastic Variance Reduced Gradient for Heterogeneous Distributed Datasets
Ilqar Ramazanli, Han Nguyen, Hai Pham +2
We study distributed optimization algorithms for minimizing the average of \emph{heterogeneous} functions distributed across several machines with a focus on communication efficien…
Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities
Hai Pham, Paul Pu Liang, Thomas Manzini +2
Multimodal sentiment analysis is a core research area that studies speaker sentiment expressed from the language, visual, and acoustic modalities. The central challenge in multimod…
Seq2Seq2Sentiment: Multimodal Sequence to Sequence Models for Sentiment Analysis
Hai Pham, Thomas Manzini, Paul Pu Liang +1
Multimodal machine learning is a core research area spanning the language, visual and acoustic modalities. The central challenge in multimodal learning involves learning representa…