Publications (17)
LIT: Block-wise Intermediate Representation Training for Model Compression
Animesh Koratana, Daniel Kang, Peter Bailis +1
Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science
Kexin Rong, Clara E. Yoon, Karianne J. Bergen +4
Sketching Linear Classifiers over Data Streams
Kai Sheng Tai, Vatsal Sharan, Peter Bailis +1
Asynchronous Complex Analytics in a Distributed Dataflow Architecture
Joseph E. Gonzalez, Peter Bailis, Michael I. Jordan +4
CrossTrainer: Practical Domain Adaptation with Loss Reweighting
Justin Chen, Edward Gan, Kexin Rong +2
Infrastructure for Usable Machine Learning: The Stanford DAWN Project
Peter Bailis, Kunle Olukotun, Christopher Re +1
Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries
Edward Gan, Jialin Ding, Kai Sheng Tai +2
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data
Vatsal Sharan, Kai Sheng Tai, Peter Bailis +1
Equivariant Transformer Networks
Kai Sheng Tai, Peter Bailis, Gregory Valiant
NoScope: Optimizing Neural Network Queries over Video at Scale
Daniel Kang, John Emmons, Firas Abuzaid +2
MacroBase: Prioritizing Attention in Fast Data
Peter Bailis, Edward Gan, Samuel Madden +3
The Missing Piece in Complex Analytics: Low Latency, Scalable Model Management and Serving with Velox
Daniel Crankshaw, Peter Bailis, Joseph E. Gonzalez +5
Coordination Avoidance in Database Systems (Extended Version)
Peter Bailis, Alan Fekete, Michael J. Franklin +3
Probabilistically Bounded Staleness for Practical Partial Quorums
Peter Bailis, Shivaram Venkataraman, Michael J. Franklin +2
To Index or Not to Index: Optimizing Exact Maximum Inner Product Search
Firas Abuzaid, Geet Sethi, Peter Bailis +1
Highly Available Transactions: Virtues and Limitations (Extended Version)
Peter Bailis, Aaron Davidson, Alan Fekete +3
ASAP: Prioritizing Attention via Time Series Smoothing
Kexin Rong, Peter Bailis