Kai Sheng Tai

According to our database, Kai Sheng Tai authored at least 13 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

uCAP: An Unsupervised Prompting Method for Vision-Language Models.

A. Tuan Nguyen, Kai Sheng Tai, Bor-Chun Chen, Satya Narayan Shukla, Hanchao Yu, Philip Torr, Tai-Peng Tian, Ser-Nam Lim

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Multi-entity Video Transformers for Fine-Grained Video Representation Learning.

Matthew Walmer, Rose Catherine Kanjirathinkal, Kai Sheng Tai, Keyur Muzumdar, Tai-Peng Tian, Abhinav Shrivastava

CoRR, 2023

Analyzing Populations of Neural Networks via Dynamical Model Embedding.

Jordan Cotler, Kai Sheng Tai, Felipe Hernández, Blake Elias, David Sussillo

CoRR, 2023

2022

Spartan: Differentiable Sparsity via Regularized Transportation.

Kai Sheng Tai, Tai-Peng Tian, Ser Nam Lim

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Statistical learning under resource constraints.

Kai Sheng Tai

PhD thesis, 2021

Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training.

Kai Sheng Tai, Peter Bailis, Gregory Valiant

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

Equivariant Transformer Networks.

Kai Sheng Tai, Peter Bailis, Gregory Valiant

Proceedings of the 36th International Conference on Machine Learning, 2019

Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data.

Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries.

Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis

Proc. VLDB Endow., 2018

Sketching Linear Classifiers over Data Streams.

Kai Sheng Tai, Vatsal Sharan, Peter Bailis, Gregory Valiant

Proceedings of the 2018 International Conference on Management of Data, 2018

2017

Finding Heavily-Weighted Features in Data Streams.

Kai Sheng Tai, Vatsal Sharan, Peter Bailis, Gregory Valiant

CoRR, 2017

There and Back Again: A General Approach to Learning Sparse Models.

Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant

CoRR, 2017

2015

Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks.

Kai Sheng Tai, Richard Socher, Christopher D. Manning

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015