Kevin Kuo

According to our database, Kevin Kuo authored at least 18 papers between 2013 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2026

Open-Weight LLM Fine-Tuning Defenses are Susceptible to Simple Attacks.

Kevin Kuo, Chhavi Yadav, Virginia Smith

CoRR, May, 2026

Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation.

Haozhan Tang, Xiuqi Zhu, Xinyin Zhang, Boxun Li, Virginia Smith, Kevin Kuo

CoRR, May, 2026

FLASC: Federated LoRA with Sparse Communication.

Kevin Kuo, Arian Raje, Kousik Rajesh, Virginia Smith

Proceedings of the ACM Conference on AI and Agentic Systems, 2026

2025

Research in Collaborative Learning Does Not Serve Cross-Silo Federated Learning in Practice.

Kevin Kuo, Chhavi Yadav, Virginia Smith

CoRR, October, 2025

Exact Unlearning of Finetuning Data via Model Merging at Scale.

Kevin Kuo, Amrith Setlur, Kartik Srinivas, Aditi Raghunathan, Virginia Smith

CoRR, April, 2025

NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA.

Marlon Tobaben, Mohamed Ali Souibgui, Rubèn Tito, Khanh Nguyen, Raouf Kerkouche, Kangsoo Jung, Joonas Jälkö, Lei Kang, Andrey Barsky, Vincent Poulain D'Andecy, Aurélie Joseph, Aashiq Muhamed, Kevin Kuo, Virginia Smith, Yusuke Yamasaki, Takumi Fukami, Kenta Niwa, Iifan Tyou, Hiro Ishii, Rio Yokota, Ragul N, Rintu Kutum, Josep Lladós, Ernest Valveny, Antti Honkela, Mario Fritz, Dimosthenis Karatzas

Trans. Mach. Learn. Res., 2025

2024

Federated LoRA with Sparse Communication.

Kevin Kuo, Arian Raje, Kousik Rajesh, Virginia Smith

CoRR, 2024

2023

On Noisy Evaluation in Federated Hyperparameter Tuning.

Kevin Kuo, Pratiksha Thaker, Mikhail Khodak, John Nguyen, Daniel Jiang, Ameet Talwalkar, Virginia Smith

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

2021

Building an Accessible, Usable, Scalable, and Sustainable Service for Scholarly Big Data.

Jian Wu, Shaurya Rohatgi, Sai Raghav Reddy Keesara, Jason Chhay, Kevin Kuo, Arjun Manoj Menon, Sean Parsons, Bhuvan Urgaonkar, C. Lee Giles

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning.

Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-yeh Chiang, Tom Goldstein, John P. Dickerson

CoRR, 2020

Towards Explainability of Machine Learning Models in Insurance Pricing.

Kevin Kuo, Daniel Lupton

CoRR, 2020

Individual Claims Forecasting with Bayesian Mixture Density Networks.

Kevin Kuo

CoRR, 2020

HATSUKI : An anime character like robot figure platform with anime-style expressions and imitation learning based action generation.

Pin-Chu Yang, Mohammed Al-Sada, Chang-Chieh Chiu, Kevin Kuo, Tito Pradhono Tomo, Kanata Suzuki, Nelson Yalta, Kuo-Hao Shu, Tetsuya Ogata

Proceedings of the 29th IEEE International Conference on Robot and Human Interactive Communication, 2020

Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays.

Kevin Kuo, Marine Carpuat

Proceedings of the Second Workshop on Figurative Language Processing, 2020

An Empirical Study of an Open Ecosystem Model for Inclusive Financial Services.

Ko-Yang Wang, Grace Lin, Kevin Kuo, Han-Chao Lee, Brick Tsai, Webster Peng

Proceedings of the 2020 IEEE International Conference on Services Computing, 2020

2019

Generative Synthesis of Insurance Datasets.

Kevin Kuo

CoRR, 2019

2018

DeepTriangle: A Deep Learning Approach to Loss Reserving.

Kevin Kuo

CoRR, 2018

2013

Infant cry classification integrated ANC system for infant incubators.

Lichuan Liu, Kevin Kuo, Sen M. Kuo

Proceedings of 10th IEEE International Conference on Networking, Sensing and Control, 2013