Justin Khim

According to our database, Justin Khim authored at least 13 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Optimal Binary Classification Beyond Accuracy.

Shashank Singh, Justin T. Khim

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Statistical Theory for Imbalanced Binary Classification.

Shashank Singh, Justin Khim

CoRR, 2021

Subseasonal climate prediction in the western US using Bayesian spatial models.

Vishwak Srinivasan, Justin Khim, Arindam Banerjee, Pradeep Ravikumar

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Multiclass Classification via Class-Weighted Nearest Neighbors.

Justin Khim, Ziyu Xu, Shashank Singh

CoRR, 2020

Improved Clinical Abbreviation Expansion via Non-Sense-Based Approaches.

Juyong Kim, Linyuan Gong, Justin Khim, Jeremy C. Weiss, Pradeep Ravikumar

Proceedings of the Machine Learning for Health Workshop, 2020

Class-Weighted Classification: Trade-offs and Robust Approaches.

Ziyu Xu, Chen Dan, Justin Khim, Pradeep Ravikumar

Proceedings of the 37th International Conference on Machine Learning, 2020

Uniform Convergence of Rank-weighted Learning.

Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Adversarial Influence Maximization.

Justin Khim, Varun S. Jog, Po-Ling Loh

Proceedings of the IEEE International Symposium on Information Theory, 2019

2018

Adversarial Risk Bounds for Binary Classification via Function Transformation.

Justin Khim, Po-Ling Loh

CoRR, 2018

2017

Confidence Sets for the Source of a Diffusion in Regular Trees.

Justin Khim, Po-Ling Loh

IEEE Trans. Netw. Sci. Eng., 2017

Permutation Tests for Infection Graphs.

Justin Khim, Po-Ling Loh

CoRR, 2017

2016

Computationally Efficient Influence Maximization in Stochastic and Adversarial Models: Algorithms and Analysis.

Justin Khim, Varun S. Jog, Po-Ling Loh

CoRR, 2016

Computing and maximizing influence in linear threshold and triggering models.

Justin T. Khim, Varun S. Jog, Po-Ling Loh

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016