Xiangxi Mo

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 13

Top Topics

Context Aware Ubiquitous Learning

Overlay Multicast

Relational Query Languages

Top Venues

Proc. VLDB Endow.

Publications

Shu Liu, Asim Biswal, Audrey Cheng, Xiangxi Mo, Shiyi Cao, Joseph E. Gonzalez, Ion Stoica, Matei Zaharia
Optimizing LLM Queries in Relational Workloads. CoRR (2024)
Xiaoxuan Liu, Cade Daniel, Langxiang Hu, Woosuk Kwon, Zhuohan Li, Xiangxi Mo, Alvin Cheung, Zhijie Deng, Ion Stoica, Hao Zhang
Optimizing Speculative Decoding for Serving Large Language Models Using Goodput. CoRR (2024)
Sarah Wooders, Shu Liu, Paras Jain, Xiangxi Mo, Joseph E. Gonzalez, Vincent Liu, Ion Stoica
Cloudcast: High-Throughput, Cost-Aware Overlay Multicast in the Cloud. NSDI (2024)
Sarah Wooders, Xiangxi Mo, Amit Narang, Kevin Lin, Ion Stoica, Joseph M. Hellerstein, Natacha Crooks, Joseph E. Gonzalez
RALF: Accuracy-Aware Scheduling for Feature Store Maintenance. Proc. VLDB Endow. 17 (3) (2023)
Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal, Xiangxi Mo, Sukrit Kalra, Peter Schafhalter, Eric Leong, Xin Wang, Bharathan Balaji, Joseph Gonzalez, Ion Stoica
Context-Aware Streaming Perception in Dynamic Environments. CoRR (2022)
Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal, Xiangxi Mo, Sukrit Kalra, Peter Schafhalter, Eric Leong, Xin Wang, Bharathan Balaji, Joseph Gonzalez, Ion Stoica
Context-Aware Streaming Perception in Dynamic Environments. ECCV (38) (2022)
Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran
Towards Scalable Dataframe Systems. Proc. VLDB Endow. 13 (11) (2020)
Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, Alexey Tumanov
InferLine: latency-aware provisioning and scaling for prediction serving pipelines. SoCC (2020)
Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran
Towards Scalable Dataframe Systems. CoRR (2020)
Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica
The OoO VLIW JIT Compiler for GPU Inference. CoRR (2019)
Paras Jain, Xiangxi Mo, Ajay Jain, Harikaran Subbaraj, Rehan Sohail Durrani, Alexey Tumanov, Joseph Gonzalez, Ion Stoica
Dynamic Space-Time Scheduling for GPU Inference. CoRR (2019)
Xiangxi Mo, Ruizhe Cheng, Tianyi Fang
Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning. CoRR (2019)
Daniel Crankshaw, Gur-Eyal Sela, Corey Zumar, Xiangxi Mo, Joseph E. Gonzalez, Ion Stoica, Alexey Tumanov
InferLine: ML Inference Pipeline Composition Framework. CoRR (2018)