Assistant Professor in the Computer Science Department at Purdue.
Assistant Professor in the Statistics Department (by courtesy) at Purdue.
Lawson Building 2142-J, West Lafayette, IN 47907, phone: 765-496-6757
e-mail: jhonorio at purdue.edu
Modern machine learning (ML) problems are combinatorial and non-convex, for which theoretical guarantees are quite limited. Furthermore, while quantitative guarantees (e.g., small test error) have been studied, qualitative guarantees (e.g., correctness of clustering) are mostly lacking. My long-term research goal is to uncover the general foundations of ML and optimization that drives the empirical success across many specific combinatorial and non-convex ML problems. I aim to develop a set of optimization-theoretic frameworks and tools to bridge the aforementioned gaps, to further our understanding of continuous (possibly non-convex) relaxations of combinatorial problems, as well as our knowledge of non-convexity. [vita]
Prior to joining Purdue, I was a postdoctoral associate at MIT CSAIL, working with Tommi Jaakkola.
My Erdős number is 3: Jean Honorio → Tommi Jaakkola → Noga Alon → Paul Erdős.
- 11/22. a brief visit to MIT.
- 09/22. 1 paper accepted at NeurIPS (Hanbyul).
- 09/22. 1 paper accepted at JMLR (Chuyang).
- 09/22. visiting National University of Singapore.
- 05/22. talk at University of Oxford.
- 05/22. 2 papers accepted at ICML (Adarsh, Wenjie/Adarsh).
- 04/22. 1 paper accepted at ISIT (Hanbyul/Kevin).
- 04/22. Siya Goel (highschool student I have mentored) accepted to Stanford.
- 03/22. talk at National University of Singapore.
- 02/22. 7 professors from different departments + 5 corporate partners are sponsoring Capstone projects.
- 01/22. 3 papers accepted at ICASSP (Chuyang, Adarsh:2).
- 01/22. 2 papers accepted at AISTATS (Chuyang, Kevin/Chuyang).
- 10/21. talks at Columbia and Hebrew University of Jerusalem.
- 09/21. 2 papers accepted at NeurIPS (Adarsh, Gregory/Kevin).
- 09/21. talks at UMass Amherst and University College London.
- 08/21. NSF DMS:Collaborative grant awarded to do research on deep learning.
- 06/21. CI fellowship awarded to Kevin to do a postdoc in UChicago & CMU.
- 06/21. talk at CalTech.
- 05/21. 2 papers accepted at ICML (Abi, Qian/Yilin).
- 04/21. 6 papers accepted at ISIT (Kevin/Qiuling, Donald/Adarsh, Jiajun/Chuyang, Zitao, Krishna, Abdulrahman).
- 04/21. talk at CMU.
- 03/21. talks at MIT, UCSD and University of Wisconsin-Madison.
- 02/21. talks at Virginia Tech and Alan Turing Institute.
- 01/21. 2 papers accepted at AISTATS (Zhanyu, Yuki).
- 09/20. 1 paper accepted at NeurIPS (Kevin).
- 01/20. 1 paper accepted at AISTATS (Kevin).
- 09/19. 3 papers accepted at NeurIPS (Kevin, Adarsh, Abi).
- 04/19. 1 paper accepted at ICML (Raphael).
- 09/18. 3 papers accepted at NeurIPS (Kevin:2, Chuyang).
- 05/18. 1 paper accepted at ICML (Asish).
- 12/17. 3 papers accepted at AISTATS (Asish:2, Yixi).
- 09/17. 1 paper accepted at NeurIPS (Asish).
- 08/17. NSF RI:Small grant awarded to do research on structured prediction.
Selected Publications (see all)
- CS 49000-DSC. Data Science Capstone: Spring 2022.
- CS 69000-SML. Statistical Machine Learning II: Fall 2021, also offered on Spring 2019 and Spring 2017.
- CS 59200-HLT / STAT 59800-HLT. Hands-On Learning Theory: Fall 2021, also offered on Fall 2020, Fall 2019, Fall 2018, Fall 2017, Fall 2016 and Fall 2015.
- CS 37300. Data Mining and Machine Learning: Spring 2021, also offered on Fall 2019 and Fall 2018.
- CS 57800. Statistical Machine Learning: Fall 2020, also offered on Spring 2020, Spring 2018, Fall 2017 and Fall 2016.
- CS 52000. Computational Methods In Optimization: Spring 2016.