I am a second year PhD student in the CS Department at Cornell advised by Chris De Sa. My research focuses on efficient machine learning. Previously, I worked on autonomous last-mile delivery vehicles as a ML Engineer on the ML Research team at Nuro. I recieved my BS in Computer Science with a minor in Information and Data Sciences from Caltech, where I also worked on machine learning research in Yisong Yue’s group. |
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and
Lattice Codebooks
Albert Tseng*, Jerry Chee*, Qingyao Sun, Volodymyr
Kuleshov, Christopher De Sa.
International Conference on Machine Learning (ICML), July
2024.
Shadow Cones: A Generalized Framework for Partial Order
Embeddings
Tao Yu*, Toni J.B. Liu*, Albert Tseng, Christopher De
Sa.
International Conference on Learning Representations (ICLR),
May 2024.
Coneheads: Hierarchy Aware Attention.
Albert Tseng, Tao Yu, Toni J.B. Liu, Christopher De
Sa.
Advances in Neural Information Processing Systems (NeurIPS),
December 2023.
Automatic Synthesis of Diverse Weak Supervision Sources for
Behavior Analysis.
Albert Tseng, Jennifer J. Sun, Yisong Yue.
IEEE Conference on Computer Vision and Pattern Recognition
(CVPR), June 2022.
Learning Calibratable Policies using Programmatic
Style-Consistency.
Eric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan,
Matthew Hausknecht.
International Conference on Machine Learning (ICML), July
2020.
* equal contribution
Last updated May 2024.