Bailis, Peter

9 publications

NeurIPS 2024 Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems Lingjiao Chen, Jared Davis, Boris Hanin, Peter Bailis, Ion Stoica, Matei Zaharia, James Zou

ICML 2024 Break the Sequential Dependency of LLM Inference Using Lookahead Decoding Yichao Fu, Peter Bailis, Ion Stoica, Hao Zhang

ICML 2024 Online Speculative Decoding Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang

AAAI 2022 Similarity Search for Efficient Active Learning and Search of Rare Concepts Cody Coleman, Edward Chou, Julian Katz-Samuels, Sean Culatana, Peter Bailis, Alexander C. Berg, Robert D. Nowak, Roshan Sumbaly, Matei Zaharia, I. Zeki Yalniz

ICLR 2020 Selection via Proxy: Efficient Data Selection for Deep Learning Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia

ICML 2019 Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data Vatsal Sharan, Kai Sheng Tai, Peter Bailis, Gregory Valiant

ICML 2019 Equivariant Transformer Networks Kai Sheng Tai, Peter Bailis, Gregory Valiant

ICML 2019 LIT: Learned Intermediate Representation Training for Model Compression Animesh Koratana, Daniel Kang, Peter Bailis, Matei Zaharia

ICML 2019 Rehashing Kernel Evaluation in High Dimensions Paris Siminelakis, Kexin Rong, Peter Bailis, Moses Charikar, Philip Levis