publications

Please see here for a full list of publications.

selected

  1. COLM
    LLM360: Towards Fully Transparent Open-Source LLMs
    Liu, Hector et al.
    In First Conference on Language Modeling 2024
    PDF Website
  2. NeurIPS
    Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
    Zheng, Lianmin, Chiang, Wei-Lin, Sheng, Ying, Zhuang, Siyuan, Wu, Zhanghao, Zhuang, Yonghao, Lin, Zi, Li, Zhuohan, Li, Dacheng, Xing, Eric, Zhang, Hao, Gonzalez, Joseph E., and Stoica, Ion
    In Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track 2023
    PDF
  3. HDSR
    Toward a ’Standard Model’ of Machine Learning
    Hu, Zhiting, and Xing, Eric P.
    Harvard Data Science Review Oct 2022
    PDF
  4. OSDI
    Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning
    Zheng, Lianmin, Li, Zhuohan, Zhang, Hao, Zhuang, Yonghao, Chen, Zhifeng, Huang, Yanping, Wang, Yida, Xu, Yuanzhong, Zhuo, Danyang, Xing, Eric P., Gonzalez, Joseph E., and Stoica, Ion
    In 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22) Jul 2022
    PDF
  5. OSDI
    Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning
    Qiao, Aurick, Choe, Sang Keun, Subramanya, Suhas Jayaram, Neiswanger, Willie, Ho, Qirong, Zhang, Hao, Ganger, Gregory R., and Xing, Eric P.
    In 15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21) Jul 2021
    PDF
  6. Ann. Stat
    Identifiability of nonparametric mixture models and Bayes optimal clustering
    Aragam, Bryon, Dan, Chen, Xing, Eric P., and Ravikumar, Pradeep
    The Annals of Statistics 2020
    PDF
  7. NeurIPS
    Learning Robust Global Representations by Penalizing Local Predictive Power
    Wang, Haohan, Ge, Songwei, Lipton, Zachary, and Xing, Eric P
    In Proceedings of the 33nd International Conference on Neural Information Processing Systems 2019
    PDF
  8. ICML
    Theoretically Principled Trade-off between Robustness and Accuracy
    Zhang, Hongyang, Yu, Yaodong, Jiao, Jiantao, Xing, Eric, Ghaoui, Laurent El, and Jordan, Michael
    In Proceedings of the 36th International Conference on Machine Learning 09–15 jun 2019
    PDF
  9. NeurIPS
    Neural architecture search with Bayesian optimisation and optimal transport
    Kandasamy, Kirthevasan, Neiswanger, Willie, Schneider, Jeff, Póczos, Barnabás, and Xing, Eric P.
    In Proceedings of the 32nd International Conference on Neural Information Processing Systems 2018
    PDF
  10. NeurIPS
    DAGs with NO TEARS: continuous optimization for structure learning
    Zheng, Xun, Aragam, Bryon, Ravikumar, Pradeep, and Xing, Eric P.
    In Proceedings of the 32nd International Conference on Neural Information Processing Systems 2018
    PDF
  11. ICML
    Toward controlled generation of text
    Hu, Zhiting, Yang, Zichao, Liang, Xiaodan, Salakhutdinov, Ruslan, and Xing, Eric P.
    In Proceedings of the 34th International Conference on Machine Learning - Volume 70 2017
    PDF
  12. ACL
    Harnessing Deep Neural Networks with Logic Rules
    Hu, Zhiting, Ma, Xuezhe, Liu, Zhengzhong, Hovy, Eduard, and Xing, Eric
    In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) Aug 2016
    PDF
  13. Engineering
    Strategies and Principles of Distributed Machine Learning on Big Data
    Xing, Eric P., Ho, Qirong, Xie, Pengtao, and Wei, Dai
    Engineering 2016
    PDF
  14. JMLR
    Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs
    Zhu, Jun, Chen, Ning, and Xing, Eric P.
    Journal of Machine Learning Research 2014
    PDF
  15. UAI
    Asymptotically exact, embarrassingly parallel MCMC
    Neiswanger, Willie, Wang, Chong, and Xing, Eric P.
    In Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence 2014
    PDF
  16. NeurIPS
    More effective distributed ML via a Stale Synchronous Parallel parameter server
    Ho, Qirong, Cipar, James, Cui, Henggang, Kim, Jin Kyu, Lee, Seunghak, Gibbons, Phillip B., Gibson, Garth A., Ganger, Gregory R., and Xing, Eric P.
    In Proceedings of the 26th International Conference on Neural Information Processing Systems - Volume 1 2013
    PDF
  17. Ann. Appl. Stat
    Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eQTL mapping
    Kim, Seyoung, and Xing, Eric P.
    The Annals of Applied Statistics 2012
    PDF
  18. Ann. Appl. Stat
    Estimating time-varying networks
    Kolar, Mladen, Song, Le, Ahmed, Amr, and Xing, Eric P.
    The Annals of Applied Statistics Mar 2010
    PDF
  19. EJS
    Discrete Temporal Models of Social Networks
    Hanneke, Steve, and Xing, Eric P.
    In SNA@ICML 2006
    PDF
  20. JMLR
    Mixed Membership Stochastic Blockmodels
    Airoldi, Edo M, Blei, David, Fienberg, Stephen, and Xing, Eric
    In Advances in Neural Information Processing Systems 2008
    PDF
  21. NeurIPS
    Distance Metric Learning with Application to Clustering with Side-Information
    Xing, Eric, Jordan, Michael, Russell, Stuart J, and Ng, Andrew
    In Advances in Neural Information Processing Systems 2002
    PDF

theses

  1. dissertation
    Understanding Training Data in Large-Scale Machine Learning
    Choe, Sang Keun
    2024
    PDF
  2. dissertation
    Toward Robust Machine Learning by Countering Superficial Features
    Wang, Haohan
    2021
    PDF
  3. dissertation
    Principles of Learning in Multitask Settings: A Probabilistic Perspective
    Al-Shedivat, Maruan
    2021
    PDF
  4. dissertation
    Towards Training AI Agents with All Types of Experiences: A Standardized ML Formalism
    Hu, Zhiting
    2021
    PDF
  5. dissertation
    Learning Embodied Agents with Scalably-Supervised Reinforcement Learning
    Lee, Lisa
    2021
    PDF
  6. dissertation
    Elastic Machine Learning Systems with Co-adaptation
    Qiao, Aurick
    2021
    PDF
  7. dissertation
    Sample-Specific Models for Precision Medicine
    Lengerich, Benjamin
    2020
    PDF
  8. dissertation
    Structured Sparse Regression Methods for Learning from High-Dimensional Genomic Data
    Marchetti-Bowick, Micol
    2020
    PDF
  9. dissertation
    Machine Learning Parallelism Could Be Adaptive, Composable and Automated
    Zhang, Hao
    2020
    PDF
  10. dissertation
    Learning DAGs with Continuous Optimization
    Zheng, Xun
    2020
    PDF
  11. dissertation
    Post-Inference Methods for Scalable Probabilistic Modeling and Sequential Decision Making
    Neiswanger, Willie
    2019
    PDF
  12. dissertation
    Towards Literate Artificial Intelligence
    Sachan, Mrinmaya
    2019
    PDF
  13. dissertation
    Scheduling for Efficient Large-Scale Machine Learning Training
    Wei, Jinliang
    2019
    PDF
  14. dissertation
    Learning with Staleness
    Dai, Wei
    2018
    PDF
  15. dissertation
    Framework Design for Improving Computational Efficiency and Programming Productivity for Distributed Machine Learning
    Kim, Jin Kyu
    2018
    PDF
  16. dissertation
    Diversity-promoting and Large-scale Machine Learning for Healthcare
    Xie, Pengtao
    2018
    PDF
  17. dissertation
    Spectral Probabilistic Modeling and Applications to Natural Language Processing
    Parikh, Ankur
    2015
    PDF
  18. dissertation
    Structured Sparse Models and Algorithms for Genetic Analaysis
    Lee, Seunghak
    2015
    Website
  19. dissertation
    Towards Scalable Analysis of Images and Videos
    Zhao, Bin
    2014
    PDF
  20. dissertation
    Modeling Large Social Networks in Context
    Ho, Qirong
    2014
    PDF
  21. dissertation
    An integrative computational framework for defining asthma endotypes
    Howrylak, JA
    2013
    PDF
  22. dissertation
    Reconstruction and Applications of Collective Storylines from Web Photo Collections
    Kim, Gunhee
    2013
    PDF
  23. dissertation
    Uncovering Structure in High-Dimensions: Networks and Multi-task Learning Problems
    Kolar, Mladen
    2013
    PDF
  24. dissertation
    Spatiotemporal gene networks from ISH images
    Puniyani, Kriti
    2013
    PDF
  25. dissertation
    The geometry of constrained structured prediction: applications to inference and learning of natural language syntax
    Martins, André Filipe Torres
    2012
    PDF
  26. dissertation
    Computational Methods for Analyzing the Architecture and Evolution of the Regulatory Genome
    Ray, Pradipta
    2012
    PDF
  27. dissertation
    Statistical Methods for studying Genetic Variation in Populations
    Shringarpure, Suyash
    2012
    PDF
  28. dissertation
    Modeling Content and Users: Structured Probabilistic Representation and Scalable Online Inference Algorithms
    Ahmed, Amr
    2011
    PDF
  29. dissertation
    Using Visualization and Automation to Accelerate Genetics Discovery
    Curtis, Ross Eugene
    2011
    PDF
  30. dissertation
    Structured Probabilistic Models of Proteins across Spatial and Fitness Landscapes
    Kamichetty, Hetunandan
    2011
    PDF
  31. dissertation
    Learning Ancestral Genetic Processes using Nonparametric Bayesian Models
    Sohn, Kyung-Ah
    2011
    PDF
  32. dissertation
    Theoretical foundations of active learning
    Hanneke, Steve
    2009
    PDF
  33. dissertation
    Statistical alignment models for translational equivalence
    Zhao, Bing
    2007
    PDF