Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades. - Aaron K. Baughman; Daniel Bohm; Micah Forster; Eduardo Morales; Jeff Powell; Shaun McPartlin; Raja Hebbar; Kavitha Yogaraj; Yoshika Chhabra; Sudeep Ghosh; Rukhsan Ul Haq; Arjun Kashyap (CoRR, 2021)

Study of Feature Importance for Quantum Machine Learning Models. - Aaron K. Baughman; Kavitha Yogaraj; Raja Hebbar; Sudeep Ghosh; Rukhsan Ul Haq; Yoshika Chhabra (CoRR, 2022)

Quadratic quantum speedup in evaluating bilinear risk functions. - Gabriele Agliardi; Corey O'Meara; Kavitha Yogaraj; Kumar Jang Bahadur Ghosh; Piergiacomo Sabino; Marina Fernández-Campoamor; Giorgio Cortiana; Juan Bernabé-Moreno; Francesco Tacchino; Antonio Mezzacapo; Omar Shehab (CoRR, 2023)

A Survey of Classical and Quantum Sequence Models. - I-Chi Chen; Harshdeep Singh; V. L. Anukruti; Brian Quanz; Kavitha Yogaraj (COMSNETS, 2024)

A Machine Learning Approach to Boost the Vehicle-2-Grid Scheduling. - Gabriele Agliardi; Giorgio Cortiana; Anton Dekusar; Kumar Jang Bahadur Ghosh; Naeimeh Mohseni; Corey O'Meara; Víctor Valls; Kavitha Yogaraj; Sergiy Zhuk (iSPEC, 2024)

Mitigating exponential concentration in covariant quantum kernels for subspace and real-world data. - Gabriele Agliardi; Giorgio Cortiana; Anton Dekusar; Kumar Jang Bahadur Ghosh; Naeimeh Mohseni; Corey O'Meara; Víctor Valls; Kavitha Yogaraj; Sergiy Zhuk (CoRR, 2024)