Albert Tseng

I am a second year PhD student in the CS Department at Cornell advised by Chris De Sa. My research focuses on geometrically motivated methods toward 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.

Research

• QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
  Albert Tseng*, Jerry Chee*, Qingyao Sun, Volodymyr Kuleshov, Christopher De Sa.
  [arXiv] [Website] [Code]

• 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 February 2024.