Berivan Isik
Berivan Isik is a research scientist at Google, focusing on developing efficient and trustworthy large models. She earned her PhD from Stanford University in 2024. See her personal page for more up-to-date information.
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Scaling Laws for Downstream Task Performance in Machine Translation
Natalia Ponomareva
Hussein Hazimeh
Sanmi Koyejo
International Conference on Learning Representations (ICLR) (2025) (to appear)
Sketching for Distributed Deep Learning: A Sharper Analysis
Mayank Shrivastava
Qiaobo Li
Sanmi Koyejo
Arindam Banerjee
Conference on Neural Information Processing Systems (NeurIPS) (2024)
Improved Communication-Privacy Trade-offs in L2 Mean Estimation under Streaming Differential Privacy
Wei-Ning Chen
Albert No
Sewoong Oh
International Conference on Machine Learning (ICML) (2024)
Sandwiched Compression: Repurposing Standard Codecs with Neural Network Wrappers
Phil A. Chou
Hugues Hoppe
Danhang Tang
Jonathan Taylor
Philip Davidson
arXiv:2402.05887 (2024)
Sandwiched Video Compression: An Efficient Learned Video Compression Approach
Danhang "Danny" Tang
Jonathan Taylor
Phil Chou
IEEE International Conference on Image Processing (2023)
LVAC: Learned Volumetric Attribute Compression for Point Clouds using Coordinate Based Networks
Phil Chou
Sung Jin Hwang
Journal of Frontiers in Signal Processing (2022)
