Li Ding

According to our database, Li Ding authored at least 26 papers between 2017 and 2024.

Collaborative distances:

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

2024

Pareto-Optimal Learning from Preferences with Hidden Context.

Ryan Boldi, Li Ding, Lee Spector, Scott Niekum

CoRR, 2024

Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization.

Li Ding, Jenny Zhang, Jeff Clune, Lee Spector, Joel Lehman

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

Solving Deceptive Problems Without Explicit Diversity Maintenance.

Ryan Boldi, Li Ding, Lee Spector

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

DALex: Lexicase-Like Selection via Diverse Aggregation.

Andrew Ni, Li Ding, Lee Spector

Proceedings of the Genetic Programming - 27th European Conference, 2024

2023

CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild.

Li Ding, Jack Terwilliger, Aishni Parab, Meng Wang, Lex Fridman, Bruce Mehler, Bryan Reimer

ACM Trans. Comput. Hum. Interact., December, 2023

Multi-Objective Evolutionary Architecture Search for Parameterized Quantum Circuits.

Li Ding, Lee Spector

Entropy, January, 2023

Objectives Are All You Need: Solving Deceptive Problems Without Explicit Diversity Maintenance.

Ryan Boldi, Li Ding, Lee Spector

CoRR, 2023

Quality Diversity through Human Feedback.

Li Ding, Jenny Zhang, Jeff Clune, Lee Spector, Joel Lehman

CoRR, 2023

Particularity.

Lee Spector, Li Ding, Ryan Boldi

Proceedings of the Genetic Programming Theory and Practice XX [GPTP 2023], 2023

Probabilistic Lexicase Selection.

Li Ding, Edward R. Pantridge, Lee Spector

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

Value of Temporal Dynamics Information in Driving Scene Segmentation.

Li Ding, Jack Terwilliger, Rini Sherony, Bryan Reimer, Lex Fridman

IEEE Trans. Intell. Veh., 2022

Optimizing Neural Networks with Gradient Lexicase Selection.

Li Ding, Lee Spector

Proceedings of the Tenth International Conference on Learning Representations, 2022

Evolutionary quantum architecture search for parametrized quantum circuits.

Li Ding, Lee Spector

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Lexicase selection at scale.

Li Ding, Ryan Boldi, Thomas Helmuth, Lee Spector

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Going faster and hence further with lexicase selection.

Li Ding, Ryan Boldi, Thomas Helmuth, Lee Spector

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

2021

Perceptual Evaluation of Driving Scene Segmentation.

Li Ding, Rini Sherony, Bruce Mehler, Bryan Reimer

Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

Evolving neural selection with adaptive regularization.

Li Ding, Lee Spector

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020

MIT DriveSeg (Manual) Dataset.

Li Ding, Jack Terwilliger, Rini Sherony, Bryan Reimer, Lex Fridman

Dataset, June, 2020

MIT DriveSeg (Semi-auto) Dataset.

Li Ding, Michael Glazer, Jack Terwilliger, Bryan Reimer, Lex Fridman

Dataset, June, 2020

MIT-AVT Clustered Driving Scene Dataset: Evaluating Perception Systems in Real-World Naturalistic Driving Scenarios.

Li Ding, Michael Glazer, Meng Wang, Bruce Mehler, Bryan Reimer, Lex Fridman

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

2019

Object as Distribution.

Li Ding, Lex Fridman

CoRR, 2019

MIT Advanced Vehicle Technology Study: Large-Scale Naturalistic Driving Study of Driver Behavior and Interaction With Automation.

Lex Fridman, Daniel E. Brown, Michael Glazer, William Angell, Spencer Dodd, Benedikt Jenik, Jack Terwilliger, Aleksandr Patsekin, Julia Kindelsberger, Li Ding, Sean Seaman, Alea Mehler, Andrew Sipperley, Anthony Pettinato, Bobbie D. Seppelt, Linda Angell, Bruce Mehler, Bryan Reimer

IEEE Access, 2019

Arguing Machines: Human Supervision of Black Box AI Systems That Make Life-Critical Decisions.

Lex Fridman, Li Ding, Benedikt Jenik, Bryan Reimer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment.

Li Ding, Chenliang Xu

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

MIT Autonomous Vehicle Technology Study: Large-Scale Deep Learning Based Analysis of Driver Behavior and Interaction with Automation.

Lex Fridman, Daniel E. Brown, Michael Glazer, William Angell, Spencer Dodd, Benedikt Jenik, Jack Terwilliger, Julia Kindelsberger, Li Ding, Sean Seaman, Hillary Abraham, Alea Mehler, Andrew Sipperley, Anthony Pettinato, Bobbie Seppelt, Linda Angell, Bruce Mehler, Bryan Reimer

CoRR, 2017

TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation.

Li Ding, Chenliang Xu

CoRR, 2017