Research & News
Our Research Thrust
foundations of machine learning
- Deep Learning and Optimization
- Reinforcement Learning and Control
- Machine Learning and Logic
high-dimensional data analysis and inference
- Networks and Statistical Inference
- High-dimensional and Complex Data Analysis
data science and society
- Trustworthy and Reliable Data Science
- Interpretability, Privacy, and Fairness
- Data Science and Strategic Agents
news
News & Updates
Xiaorui Sun Featured in Quanta Magazine Article for Finding New Algorithm
IDEAL scholar Xiaorui Sun's groundbreaking algorithm for the group isomorphism problem was featured in an article in Quanta Magazine. The article reads: "A paper by Xiaorui Sun of the University of Illinois, Chicago has presented a new, faster algorithm for...
Vishesh Jain receives NSF CAREER award for 2023-28
IDEAL faculty Vishesh Jain(UIC) has received an NSF CAREER (Faculty Early Career Development Program) award. CAREER is an NSF (National Science Foundation) award that supports early-career faculty that may serve as academic role model in research and education and...
Forging New Connections Within IDEAL
A team of 80 faculty members, postdocs, students, and industry representatives gathered for the daylong Institute for Data, Econometrics, Algorithms, and Learning (IDEAL) annual meeting this month at Northwestern’s Simpson Querrey Biomedical Research Center in...
Encouraging Undergraduate Students to Pursue Data Science Research
A cohort of 30 first- and second-year undergraduate students from colleges and universities across the country attended the three-day “Get Ready for Research Workshop” this month, hosted by the Institute for Data, Econometrics, Algorithms, and Learning (IDEAL) at the...
Exploring the Connections Among Machine Learning, Interpretability, and Logic
On April 10-14, the five participating universities of the Institute for Data, Econometrics, Algorithms, and Learning hosted a workshop examining multiple areas of interpretability. Article...
Samir Khuller Elected to CRA Board of Directors
Khuller aims to help better integrate research and educational activities through strong partnerships between academia and industry Article link:...
published research
Publications
H. Shao, L. Cohen, A. Blum, Y. Mansour, A. Saha, M. Walter, Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. (2023).
K. Makarychev, Y. Makarychev, L. Shan, A. Vijayaraghavan, Higher-Order Cheeger Inequality for Partitioning with Buffers. (2023).
C. Carlson, J. Jafarov, K. Makarychev, Y. Makarychev, L. Shan, Approximation Algorithm for Norm Multiway Cut. (2023).
I. Hong, S. Na, M. Mahoney, M. Kolar, Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching. (2023).
S. Yang, S. Khuller, S. Choudhary, S. Mitra, K. Mahadik, Correlated Stochastic Knapsack with a Submodular Objective. (2022)
S. Ahmadi; P. Awasthi; S. Khuller; M. Kleindessner; J. Morgenstern; P. Sukprasert, Individual Preference Stability for Clustering. (2022)
S. Yang, S. Khuller, S. Choudhary, S. Mitra, K. Mahadik, Scheduling ML training on unreliable spot instances. UCC ’21: Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion- December 2021.
Available here.
Lang, H., Reddy, A., Sontag, D., & Vijayaraghavan, A. (2021). Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances. AISTATS. ArXiv, abs/2103.00034.
Available here.
Ren, J., Liu, C., Yu, G., & Guo, D. (2021). A New Distributed Method for Training Generative Adversarial Networks. ArXiv, abs/2107.0868.
Available here.
Chen, A., De, A. & Vijayaraghavan, A.. (2021). Learning a mixture of two subspaces over finite fields. Proceedings of the 32nd International Conference on Algorithmic Learning Theory, in Proceedings of Machine Learning Research 132:481-504. ArXiv, abs/2010.02841.
Available here.
Awasthi, P., Tang, A.K., & Vijayaraghavan, A. (2021). Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations. ArXiv, abs/2107.10209.
Available here.
Jafarov, J., Kalhan, S., Makarychev, K.; Makarychev, Y. (2021). Local Correlation Clustering with Asymmetric Classification Errors. Proceedings of the 38th International Conference on Machine Learning in Proceedings of Machine Learning Research 139:4677-4686. ArXiv, abs/2108.05697.
Available here.
Makarychev, K.; Shan, L.. (2021). Near-Optimal Algorithms for Explainable k-Medians and k-Means. Proceedings of the 38th International Conference on Machine Learning, in Proceedings of Machine Learning Research 139:7358-7367. ArXiv, abs/2107.00798.
Available here.
Makarychev, Y. & Vakilian, A.. (2021). Approximation Algorithms for Socially Fair Clustering. Proceedings of Thirty Fourth Conference on Learning Theory, in Proceedings of Machine Learning Research 134:3246-3264. ArXiv, abs/2103.02512.
Available here.
Chao Gao and John Lafferty. Model Repair: Robust Recovery of Over-Parameterized Statistical Models, 2020. ArXiv, abs/2005.09912
Available here.
Pinhan Chen, Chao Gao and Anderson Zhang. Partial Recovery for Top-k Ranking: Optimality of MLE and Sub-Optimality of Spectral Method, 2020. ArXiv, abs/2006.16485.
Available here.
P. Poojary and R. Berry. Observational Learning with Fake Agents, 2020. IEEE International Symposium on Information Theory (ISIT), Los Angeles, CA, 2020. ArXiv, abs/2005.05518.
Available here.
Nasir, Y.S., & Guo, D. (2020). Deep Reinforcement Learning for Joint Spectrum and Power Allocation in Cellular Networks. ArXiv, abs/2012.10682.
Available here.
Auerbach, E. (2020). Testing for Differences in Stochastic Network Structure. ArXiv, abs/1903.11117.
Available here.
Our Sponsors
The Phase II operations of the IDEAL is supported by the National Science Foundation through the TRIPODS HDR program (under the awards EECS 2216970, 2217023, 2216926, 2216912, 2216899). The IDEAL Phase II institute builds on the activities of two NSF TRIPODS Phase 1 institutes: IDEAL Phase 1 (supported by the NSF award CCF 1934931) and UIC TRIPODS Institute (supported by the NSF award CCF 1934915).