no code implementations • 7 Jun 2022 • Tung Phan-Minh, Forbes Howington, Ting-Sheng Chu, Sang Uk Lee, Momchil S. Tomov, Nanxiang Li, Caglayan Dicle, Samuel Findler, Francisco Suarez-Ruiz, Robert Beaudoin, Bo Yang, Sammy Omari, Eric M. Wolff
In this paper, we introduce the first learning-based planner to drive a car in dense, urban traffic using Inverse Reinforcement Learning (IRL).
no code implementations • CVPR 2016 • Caglayan Dicle, Burak Yilmaz, Octavia Camps, Mario Sznaier
Many physical phenomena, within short time windows, can be explained by low order differential relations.
no code implementations • CVPR 2015 • Yin Wang, Caglayan Dicle, Mario Sznaier, Octavia Camps
Linear Robust Regression (LRR) seeks to find the parameters of a linear mapping from noisy data corrupted from outliers, such that the number of inliers (i. e. pairs of points where the fitting error of the model is less than a given bound) is maximized.