Research

Research

Our research aims to advance our understanding of the fundamentals in Machine Learning, Deep Learning, and to investigate how they enable new AI methods in Computer Vision and Language Understanding. As part of the VinGroup ecosystem, we are well positioned to be at the forefront of the digitalization of customer experience via AI-based systems that can understand human natural interaction through voices, gestures, behaviors, or from smart sensors and devices. Due to our unique location, we are also naturally drawn towards important problems in developing countries that might otherwise be overlooked in the research community.

Publications

Bootstrapping Upper Confidence Bound

Hao, Botao , Abbasi-Yadkori, Yasin , Wen, Zheng , Cheng, Guang  (2019) NeurIPS 2019 (to appear)

Thompson Sampling and Approximate Inference

Phan, My , Abbasi-Yadkori, Yasin , Domke, Justin  (2019) NeurIPS 2019 (to appear)

Training Variational Autoencoders with Buffered Stochastic Variational Inference

Shu R. , Bui H. , Whang J. and Ermon S.  (2019) AISTATS 2019

WorkingHands: A Hand-Tool Assembly Dataset for Image Segmentation and Activity Mining.

Roy Shilkrot , Supreeth Narasimhaswamy , Saif Vazir , Minh Hoai  (2019) Proceedings of British Machine Vision Conference (BMVC)

Contextual Attention for Hand Detection in the Wild

Supreeth Narasimhaswamy , Zhengwei Wei , Yang Wang , Justin Zhang , Minh Hoai  (2019) International Conference on Computer Vision (ICCV)

Transferability and Hardness of Supervised Classification Tasks

Tuan Tran, Anh , Viet Cuong, Nguyen , Hassner, Tal  (2019) The IEEE International Conference on Computer Vision (ICCV)