Lesia Semenova

According to our database, Lesia Semenova authored at least 15 papers between 2019 and 2025.

Collaborative distances:

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

2025

The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning.

Ethan Hsu, Harry Chen, Chudi Zhong, Lesia Semenova

CoRR, November, 2025

Many Ways to be Right: Rashomon Sets for Concept-Based Neural Networks.

Shihan Feng, Cheng Zhang, Michael Xi, Ethan Hsu, Lesia Semenova, Chudi Zhong

CoRR, November, 2025

Fast and interpretable mortality risk scores for critical care patients.

Chloe Qinyu Zhu, Muhang Tian, Lesia Semenova, Jiachang Liu, Jack Xu, Joseph Scarpa, Cynthia Rudin

J. Am. Medical Informatics Assoc., 2025

ElliCE: Efficient and Provably Robust Algorithmic Recourse via the Rashomon Sets.

Bohdan Turbal, Iryna Voitsitska, Lesia Semenova

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

The Rashomon Set Has It All: Analyzing Trustworthiness of Trees under Multiplicity.

Ethan Hsu, Tony Cao, Lesia Semenova, Chudi Zhong

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

This EEG Looks Like These EEGs: Interpretable Interictal Epileptiform Discharge Detection With ProtoEEG-kNN.

Dennis Tang, Jon Donnelly, Alina Jade Barnett, Lesia Semenova, Jin Jing, Peter Hadar, Ioannis Karakis, Olga Selioutski, Kehan Zhao, M. Brandon Westover, Cynthia Rudin

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025

2024

Amazing Things Come From Having Many Good Models.

Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo I. Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner

CoRR, 2024

Using Noise to Infer Aspects of Simplicity Without Learning.

Zachery Boner, Harry Chen, Lesia Semenova, Ronald Parr, Cynthia Rudin

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Position: Amazing Things Come From Having Many Good Models.

Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo I. Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges.

Dennis Tang, Frank Willard, Ronan Tegerdine, Luke Triplett, Jon Donnelly, Luke Moffett, Lesia Semenova, Alina Jade Barnett, Jin Jing, Cynthia Rudin, M. Brandon Westover

CoRR, 2023

A Path to Simpler Models Starts With Noise.

Lesia Semenova, Harry Chen, Ronald Parr, Cynthia Rudin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

On the Existence of Simpler Machine Learning Models.

Lesia Semenova, Cynthia Rudin, Ronald Parr

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

Multitask Learning for Citation Purpose Classification.

Alex Oesterling, Angikar Ghosal, Haoyang Yu, Rui Xin, Yasa Baig, Lesia Semenova, Cynthia Rudin

CoRR, 2021

Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges.

Cynthia Rudin, Chaofan Chen, Zhi Chen, Haiyang Huang, Lesia Semenova, Chudi Zhong

CoRR, 2021

2019

A study in Rashomon curves and volumes: A new perspective on generalization and model simplicity in machine learning.

Lesia Semenova, Cynthia Rudin

CoRR, 2019